Patent Publication Number: US-11647685-B2

Title: Implement position control system and method for same

Description:
RELATED APPLICATIONS 
     This application is a continuation of U.S. Patent Application Ser. No. 17,084,044, filed Jul. 12, 2018, which is a continuation of U.S. patent application Ser. No. 16/510,828, filed. Jul. 12, 2019, which claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 62/697,195, filed Jul. 12, 2018, which applications are incorporated by reference herein in their entirety. 
    
    
     COPYRIGHT NOTICE 
     A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to the software and data as described below and in the drawings that form a part of this document: Copyright Raven Industries, Inc.; Sioux Falls, S. Dak. All Rights Reserved. 
     TECHNICAL FIELD 
     This document pertains generally, but not by way of limitation, to control of agricultural implements. 
     BACKGROUND 
     Agricultural vehicles include one or more implements configured to interact with features in a field including the ground (e.g., soil), crops, grass, hay, brush or the like. Implements, such as harvester heads, sprayer booms and nozzles, planter disks, seed tubes, balers or the like are positioned a specified distance relative to one or more of these features. For instance, harvester heads are positioned in proximity to the ground to ensure harvesting of the specified portion of the crop (e.g., stalk, ears, grain or the like) while at the same time sufficiently elevated to avoid a collision with the ground. In other examples, a sprayer boom, including one or more spray nozzles, is positioned a specified distance from the crop to apply one or more agricultural products in a specified manner (e.g., according to manufacturer prescription for the product). 
     In some examples, the implement is controlled based on input from one or more sensors, such as ultrasound sensors. For instance, a sprayer vehicle includes one or more sensors configured to measure the distance from the sensors to the ground. The height of the crop is subtracted from the measured distance to the ground as is the specified distance for application of the agricultural product (e.g., an atomized fertilizer, herbicide, water or the like). The sprayer boom and one or more nozzles are correspondingly raised or lowered to apply the agricultural product based on the distance remaining after the calculation. 
     In other examples, the implement includes one or more sensors, such as ultrasound sensors, configured to measure the distance from the sensors to the crop, such as the leafy canopy of the crop. In a sprayer vehicle, the sprayer boom is raised or lowered to position the sprayer boom and one or more nozzles at the specified distance for application of the agricultural product. 
     OVERVIEW 
     The present inventors have recognized, among other things, that a problem to be solved includes automatically controlling the position of an implement for an agricultural vehicle in response to variations in one or more features, including, but not limited to, crop height or uneven terrain while at the same time compensating for inconsistent and sometimes unreliable measurements. For instance, a sprayer vehicle includes one or more sensors configured to measure the distance to the ground from the sensor. Ground measurements are, in some examples, inconsistent. Terrain varies in elevation and angle, ground is obscured by the crop (e.g., corn leaves, stalks, grain, grass, weeds or the like), and reliable measurements of distance from the sensor to the ground are accordingly difficult. In other examples, the one or more sensors measure the distance from the sensor to portions of the crop, such as the canopy of the crop (e.g., leaves). Depending on spacing between each plant the distance measured varies significantly as the sensors alternate between measuring a distance to the canopy and immediately transitioning to measuring the intervening (exposed) ground having a distance significantly different relative to the distance to the canopy. In other examples, the crop is dry and is poorly detected by the sensors. 
     In automated systems including these sensors the sprayer boom may, in some examples, incorrectly raise and lower based on these unreliable sensor measurements. The incorrectly positioned sprayer boom and nozzles may apply the agricultural product below the canopy (thereby decreasing its efficacy), collide with the ground or crop (causing damage to one or more of the crop or the sprayer boom) or the like. Alternatively, the sprayer boom attempts to compensate for the fluctuating inaccurate measurements and rocks upwardly and downwardly in an attempt to follow the measurements, applies the product in a less than ideal manner, and in some examples the sprayer boom, actuators or the like are damaged by the rocking movement. 
     The present subject matter helps provide a solution to this problem, such as by an automated implement control system that measures multiple distances, assesses the measured distances and selects at least one of the measured multiple distances to base control of the implement upon. The control system includes one or more distance sensors having ground and canopy sensing elements. An implement control module of the system determines confidence values for each of the respective ground distance and canopy distance measured with the ground and canopy sensing elements of the one or more distance sensors. A selection module selects one of the measured ground distance or measured canopy distance to serve as a control basis (e.g., a verified distance from the implement or sensor to one of the ground or the canopy), and control of the implement, such as positioning, is premised on the selected distance (ground or canopy). 
     The determination of the confidence values includes a comparison of one or more values based on the measured ground and canopy distances. For instance, rates of change of the ground and canopy distances (e.g., velocities, accelerations including angular versions of the same) are compared with thresholds including but not limited to static thresholds (e.g., operator set thresholds for rates of change) and dynamic thresholds based on the rates of change of the measurement assessed. In one example, a ground confidence value is determined with a comparison of the ground distance rate of change with the canopy distance rate of change. 
     In another example, the ground distance rate of change for measured ground distance at a first sensor is compared with a plurality of rates of change including, but not limited to, one or more of the canopy distance rate of change for measured canopy distance at the first sensor, ground distance rates of change of a plurality of sensors, canopy distance rates of change of the plurality of sensors, or one or more predicted ground distance rates of change at one or more of the plurality of sensors. In an example including a predicted ground distance rate of change, the predicted ground distance (the basis used for determining the predicted ground distance rate of change) is kinematically determined. For instance, an implement profile including one or more of implement dimensions, sensor positions and implement orientation is used to determine the predicted ground distance at the first sensor (or distances at the plurality of sensors). The rate (or rates) of change of the predicted ground distance (distances) is used as another value for comparison with the ground distance rate of change. 
     Comparison of the canopy distance rate of change is similarly conducted, for instance with one or more plurality of rates of change including, but not limited to, one or more of the ground distance rate of change for measured ground distance at the first sensor, canopy distance rates of change of a plurality of sensors, ground distance rates of change of the plurality of sensors, or one or more predicted ground distance rates of change at one or more of the plurality of sensors. In another example, the predicted ground distance is similarly compared (e.g., the predicted ground distance rate of change is compared with one or more of the rates of change described herein). 
     The comparisons provide confidence values for each of the respective measured distances indicating the reliability of the respective distances. A comparison indicating the measured or predicted distance under evaluation corresponds (e.g., the rate of change is similar) with the other distances (including one or more of the rates of changes of the other distances) receives a higher confidence value. While a compared measured or predicted distance that differs from the other distances (including their respective rates of change) receives a lower confidence value. The confidence value (e.g., a comparative confidence value) for the respective measured distance is accordingly variable based on the comparison and varies between a one and zero (corresponding to 100 percent to 0 percent confidence). 
     In still other examples, a kinematic model of the vehicle (e.g., agricultural implement, chassis or the like) is analyzed to generate one or more predictive windows and window shifts for the measured ground and canopy distances. The kinematic model of the vehicle includes uses one or more position measurements (distance or angle), rates of change of the same or the like to generate the predictive window and window shift. In one example, the kinematic model determines a combined angular velocity of the vehicle based on an implement angle, chassis roll rate and implement rack angle. The kinematic model generates a corresponding predicted height change for the implement (e.g., a portion of the implement) based on the combined angular velocity and one or more optional supplemental kinematic inputs. The predicted height change provides a range of values, the predictive window, and shifts the predictive window according to the total height change and one or more time constants to provide the predictive window shift. Each of the distances is compared with the predictive windows and window shifts to assess the reliability of the measured distances relative to the predicted values and assign an initial confidence value (e.g., a comparative confidence value) for the ground or canopy measurement that is compared with the opposed confidence value for the canopy or ground measurement. 
     The selection module selects one of the measured ground distance, measured canopy distance (and in some examples the predicted ground distance) as a control basis (e.g., a verified or confirmed distance) according to the highest comparative ground or canopy confidence value. Optionally, where the confidence values of each of the measured ground distance or canopy distance have a low confidence value (e.g., 50 percent, 40 percent, 30 percent, 25 percent or lower) the selection module selects the predicted ground distance as the agricultural implement value. In another example, the selection module includes a distance priority (e.g., ground distance is prioritized higher than the canopy distance, for instance with a confidence weight). Optionally, with low confidence values for each of the measured ground distance and measured canopy distances (e.g., below a base confidence threshold) the selection module selects the measured distance having the highest priority (e.g., the measured ground distance in an example). 
     The automated implement control system is thereby configured to select one or more measured distances or predicted distances (e.g., the predicted ground distance) for use as a reference value for implement control based on determination and evaluation of confidence values for the various measurements and predictions. Inconsistent measurements (e.g., unreliable, noisy, poor measurements) because of obscured or partially obscured ground, gaps in the canopy, poorly detected dry canopies or the like are accordingly disregarded in favor of measurements having higher confidence values. For instance, the automated implement control system evaluates the various measured distances (and optionally the predicted distances) described herein and selects the best (highest confidence) measurement for use in controlling the implement while disregarding, for the time being, the lower confidence measured distance. The implemental control module of the system operates in an ongoing manner and accordingly conducts the evaluation (e.g., confidence value determination, comparison of confidence values, and selection based on the confidence) automatically. If the confidence values change and indicate that another measured distance (e.g., canopy instead of ground or ground instead of canopy) has a higher confidence value the selection module accordingly hands off the control basis from the previous measured distance to the updated higher confidence measured distance. 
     The agricultural implement is thereafter controlled based on the higher confidence measured distance (e.g., a sprayer boom is raised, lowered or maintained based on the selected distance). For instance, ground or canopy based distance measurements selected depending on the confidence values, are used to detect deviation (e.g., canopy error or ground error) from a corresponding target distance (e.g., a specified ground target distance or specified canopy target distance associated with the selected measured ground or canopy distances), and the implement control module accordingly guides the implement toward the respective target distance. In one example, the implement control module transitions the implement toward a minimal deviation (e.g., including an error of zero) indicating the implement is positioned proximate the target distance. Implement control is thereby enhanced including, for instance, reliable positioning of a sprayer boom at a specified application distance relative to a crop canopy or ground, avoidance of collisions between the sprayer boom and the crop or ground or the like. 
     Further, as the automated implement control system evaluates the respective confidences of the measured distances and switches between use of the ground and canopy measured distances, the system also updates target distances, such as target distance from the implement or sensor to either of the ground or the canopy, used with implement height determinations. For instance, an example target distance from ground (a target distance from the sensor to the ground with the ground as the reference, or origin) for applying a sprayed agricultural product is 60 inches. This is the specified target distance (or height) of the implement relative to ground. In the example, this may correspond to a user estimated crop canopy height of 40 inches (from ground) and a specified application spacing of 20 inches between the sensor (and implement feature, such as a sprayer nozzle, bottom of the implement or the like) and the crop canopy, or 60 inches total. This target distance (e.g., an ideal target distance) is used with implement control having measured ground distance as the control basis. 
     In another example, for instance with the measured canopy distance having the higher confidence value, and accordingly selected as the control basis, the target distance from ground (e.g., 60 inches in the example) is not used without modification. Instead, a target distance from the canopy is used. In this example, the target distance from the canopy is 20 inches (e.g., a specified application spacing between the canopy and the implement, such as a sprayer boom). Accordingly, with the measured canopy distance as the agricultural implement reference the target distance is updated to a canopy target distance, such as an agricultural product application spacing of 20 inches. 
     In another example, the target distance includes a substitute target distance that is a variable value based on the distance form a preceding measurement before switching. For instance, as the system transitions from using measured ground distance and a user specified target ground distance to measured canopy distance the target canopy distance is in one example determined from the preceding ground measurements, the specified target ground distance and deviations relative to the target ground distance. For instance, a Canopy Target Substitute (based on preceding ground measurements and a ground target) equals a Measured Canopy Distance (Dc or distance to canopy filtered, DCF) plus the previous Distance to Ground Error (Dge or ground error). The previous Distance to Ground Error equals Target Ground Distance (e.g., a specified target distance to ground set by the operator) minus the preceding measured Distance to Ground (Dg or DGF). Accordingly, the Canopy Target Substitute is variable and based on the previously measured distance to the ground, for instance immediately before transition to use of the measured distance to the canopy. Conversely, as the system transitions from using the measured canopy distance to the measured ground distance the target ground distance (Ground Target Substitute) is determined from the preceding canopy measurements and deviations relative to the specified target canopy distance. For instance the Ground Target Substitute equals a Measured ground Distance (Dg or distance to ground filtered, DGF) plus the previous Distance to Canopy Error (Dce or canopy error). The previous Distance to Canopy Error equals the Target Canopy Distance (e.g., specified target distance to canopy) minus the previous measured Distance to canopy (Dc or DGF)). These determinations of target ground and target canopy substitutes facilitate the transition from use of one of the measured ground or canopy distance to the opposing measured canopy or ground distance, while also accounting for previously noted deviations from target values prior to the transition. 
     This overview is intended to provide an overview of subject matter of the present patent application. It is not intended to provide an exclusive or exhaustive explanation of the disclosure. The detailed description is included to provide further information about the present patent application. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the drawings, which are not necessarily drawn to scale, like numerals may describe similar components in different views. Like numerals having different letter suffixes may represent different instances of similar components. The drawings illustrate generally, by way of example, but not by way of limitation, various embodiments discussed in the present document. 
         FIG.  1    is a schematic rear view of one example of a vehicle navigating terrain with an agricultural implement. 
         FIG.  2    is a schematic side view of the agricultural implement of  FIG.  1    and an oncoming agricultural crop. 
         FIG.  3    is a plot of measured canopy and ground distances along with a predicted ground distance relative to an implement. 
         FIG.  4    is a schematic diagram of a vehicle and one example of automated implement control system. 
         FIG.  5    is a schematic diagram of another example of an automated implement control system. 
         FIG.  6    is a perspective view of one example of a distance sensor. 
         FIG.  7    is a schematic diagram of one example of an implement control module architecture for the automated implement control system. 
         FIG.  8    is a schematic diagram of another example of an implement control module architecture for the automated implement control system. 
         FIG.  9 A  is a schematic diagram of one example of an implement analysis module with vehicle and implement kinematic inputs. 
         FIG.  9 B  is another schematic diagram of the implement analysis module of  FIG.  9 A  with an example kinematic output. 
         FIG.  10    is a schematic diagram of an example implement prediction module with an example predictive window output. 
         FIG.  11 A  is a schematic diagram of an example ground reliability module. 
         FIG.  11 B  is another schematic diagram of the ground reliability module of  FIG.  11 A . 
         FIG.  11 C  is a schematic diagram of an example ground confidence module. 
         FIG.  12 A  is a schematic diagram of an example canopy reliability module. 
         FIG.  12 B  is another schematic diagram of the canopy reliability module of  FIG.  12 A . 
         FIG.  12 C  is a schematic diagram of an example canopy confidence module. 
         FIG.  13    is a schematic diagram of an example target selection module. 
         FIG.  14 A  is a schematic diagram of a portion of the target selection module of  FIG.  13   . 
         FIG.  14 B  is a schematic diagram of a portion of the target selection module of  FIG.  13   . 
         FIG.  15    is a schematic diagram of an example target and deviation module. 
         FIG.  16 A  is a schematic diagram of a portion of the target and deviation module of  FIG.  15   . 
         FIG.  16 B  is a schematic diagram of another portion of the target and deviation module of  FIG.  15    with example substitute ground and canopy targets. 
         FIG.  17 A  is a schematic diagram of an example substitute ground target filter. 
         FIG.  17 B  is a schematic diagram of an example substitute canopy target filter. 
     
    
    
     DETAILED DESCRIPTION 
       FIG.  1    is a schematic view of one example of a vehicle  100  and an associated agricultural implement  102 . In this example, the agricultural implement is coupled to the chassis  101  of the vehicle  100 , for instance by way of an implement rack  103  (a component of the implement  102 ). As further shown in  FIG.  1   , the agricultural implement  102  includes one or more booms  106 , such as sprayer booms extending away from the vehicle  100 . The booms  106  are coupled with the chassis  101 , for instance with the intervening implement rack  103  (e.g., a center rack for a sprayer assembly). The booms  106  are movable relative to the chassis  101  and terrain  110  to facilitate interaction with one or more of the terrain  110  or a crop. For instance, implement actuators are coupled with the agricultural implement  102 , between the booms  106  and the implement rack  103  to actuate the booms  106  into position for the application of one or more agricultural products, such as herbicides, insecticides, fertilizer, water or the like. 
     As described herein, examples of automated implement control systems (e.g., system  420  in  FIG.  4   ) are described that facilitate the control of the implement position, for instance of the booms  106 ) to achieve an application position or specified target height relative to features, such as the ground (terrain  110 ) or crop canopy. The control systems described herein allow for control of the implement relative to one or more control bases, such as relative to the ground or canopy and their respective ground distance and canopy distance. Further, the control systems described herein facilitate control of the implement, including guidance toward a specified target, such as target height of the boom  106  of 60 inches (e.g., a specified target distance) relative to the ground (e.g., a specified target designation). Additionally, the systems described herein facilitate guidance of the implement  102 , such as the boom  106 , toward the target height (the specified target distance) even where the control basis is different from the specified target designation, for instance where the ground is not readily detectable but the crop canopy is detectable. In this scenario the system generates an alternative or substitute specified target distance based on the specified target distance to facilitate use of the different control basis for measurement, in this example the crop canopy, while still guiding the boom  106  to the specified target (e.g., 60 inches above the ground). 
     Referring again to  FIG.  1   , the agricultural implement  102  includes one or more distance sensors  108  along the boom  106  that measure the distance from the implement (e.g., the sensors) to the ground, such as the terrain  110  having the terrain contour  112  (shown in broken lines in  FIG.  1   ). As shown in  FIG.  1   , the terrain contour  112  varies, in some examples, significantly. The distance sensors  108  sense the terrain contour  112  and generate a varying signal corresponding to the variations in the terrain  110  (e.g., showing changes in distance caused by the terrain variation). Additionally, the distance sensors  108  measure distance to one or more additional features, such as the crops or crop canopy between the ground (terrain  110 ) and the sensors  108 . In some examples, as described herein, the crop canopy obscures sensing and measurement of distance to the ground and in other examples, the ground is dry and difficult to sense with the sensor  108 . 
       FIG.  2    is a schematic side view of the vehicle  100  and the agricultural implement  102  including one of the booms  106  relative to a crop  202 . As shown in  FIG.  2   , the boom  106  (e.g., the implement  102 ) includes an implement tool  200  including, but not limited to, one or more of spray nozzles, row sections of a planter, components of a harvester head, plow blades or the like. A distance sensor  108  is coupled with the implement, for instance along the boom  106 . As previously described, the distance sensor  108  measures one or more distances including, for example, the distance to the ground (terrain  110 ) and the distance to the crop (e.g., a crop canopy, shown for instance with the dashed canopy contour line  214 ). 
     As shown in  FIG.  2   , the vehicle  100  is moving from left to right relative to the page. The boom  106  and the associated distance sensor  108  pass over the crop  202  having the crop canopy, in this example shown with a canopy contour line  214 . As shown the crop  202  generally has a similar degree of growth among the component plants with some variations. For instance, the crop  202  includes mature and immature crops  208 ,  210  having corresponding heights and varying fullness of the corresponding leaves, stems or the like. Additionally, there are variations in the hydration of the crops hydrated crops  204  and dehydrated crops  206  (shown with a lighter line weight) of the crop  202 . In some examples, distance sensors  108  partially sense or fail to sense dehydrated crops  206  and the dehydrated crops  206  accordingly are not sensed as part of the canopy. Further, there are crop gaps  212  between one or more of the crops corresponding to a plant that has died, failed to emerge or a gap in the row. Each of these and other variations in the crop  202  accordingly modulate the height of the crop canopy so that the crop canopy, shown with the canopy contour line  214 , varies. Accordingly, each of the terrain  110  and the crop canopy (represented with the canopy contour  214 ) vary in their respective distances relative to the implement  102  and the distance sensors  108 . In other examples, for instance with dehydrated crops  206  or crop gaps  212  measured distance to the crop canopy will merge with the measured ground distance, in effect the canopy appears to disappear based on the distance measurements. In another example, the crop canopy is sufficiently dense that the ground (terrain  110 ) is partially sensed or is not sensed with the distance sensors  108 , and accordingly the ground appears to disappear as its distance measurements appear to merge with the measured crop canopy distances. 
     As described herein, the measurement of both ground (to the terrain  110  from the sensor or implement) and canopy distances (to the crop canopy from the sensor or implement) provides at least two potential bases for control of the agricultural implement position. The systems described herein, such as the agricultural implement control system  420  shown in  FIG.  4    select the control basis (e.g., ground or canopy) according to a variety of characteristics indicating the reliability or confidence in the corresponding measurements. For instance, the system assesses ground and canopy distance measurements (including changes in the measurements) relative to one or more predictive windows, described herein. Ground and canopy confidence values are determined based on the assessments and used to select either of ground distance or canopy distance control as a control basis (e.g., the implement is guided relative to selected corresponding measurements or preceding measurements if the measurements are deemed unreliable). The system  420  monitors the confidence values of ground and canopy distances in an ongoing manner and hands off control of the agricultural implement position (e.g., movement of the implement  102 , such as the booms  106 ) to either of ground distance control basis or canopy distance control basis on the assessment of confidence values, thereby ensuring the implement position is controlled according to the control basis having the greatest confidence. 
       FIG.  3    is a plot  300  of measured distances for each of the crop canopy and ground relative to one or more of the distance sensors  108 . The distance sensor  108  in this example is positioned at the origin proximate to the top of the measured and predicted distances. As shown, the plot  300  includes the measured canopy distances (canopy distance  302 ) as a fluctuating line extending along the time axis and having varying distance measurements. In one example, the fluctuations correspond to variations in height of the crop (based on maturity or growth), hydration, and voids or gaps in the canopy. One example of a crop gap  212  (in  FIG.  2   ) is shown in  FIG.  3    as a canopy void  310 . Alternatively, the canopy void  310  corresponds in other examples to one or more of a dehydrated crop  206 , poorly reflected signal from the crop (e.g., the leaves or stem are misaligned relative to the sensor) or the like. Further, at the canopy void  310  the canopy distances appear to merge (or disappear) with the measured ground distance  304 . The system  420  described herein is configured in one example to hand off control based on the canopy distance  302  (a preceding control basis) to control based on the ground distance  304  instead because of a higher confidence of the ground distance measurements while the canopy appears to disappear. 
     As further shown in  FIG.  3   , the plot  300  includes the previously described plot of ground distance measurements (ground distance  304 ). The measured ground distance  304  has generally greater distance measurements compared to the measured canopy distances  302  because the ground is further from the sensors and the interposed crop canopy. In a similar manner to the canopy measured canopy distances  302 , the ground distance  304  includes one or more ground voids  308  that appears as a merger of the associated measured ground distances with the canopy distance  302 . The ground void  308  corresponds in some examples to one or more of a portion of the ground concealed by crop canopy, poor quality of measurements, intervening obstacles or the like). As shown in the plot  300  the measured canopy distances are relatively consistent where the measured ground distances of the ground void  308  appear to disappear. In another example, the system  420  described herein hands off control based on the ground distance  304  (a preceding control basis) to control based on the canopy distance  302  because of a higher confidence of the canopy distance measurements while the ground appears to disappear. Accordingly, consistent control relative to a detectable target is maintained through switching to a higher reliability target (one of the ground or canopy distances  304 ,  302 ). 
     Referring again to  FIG.  3   , in another example a predicted ground distance  306  is plotted along with the measured canopy and ground distances  302 ,  304 . The predicted ground distance is determined as a series of predicted heights or distances of the boom sensor  108  or the associated agricultural implement  102  (e.g., the boom  106  having the sensor). One or more kinematic characteristics of the vehicle (e.g., a prime mover, tow behind implement) and the agricultural implement are known (such as dimensions of the vehicle and implement), measured (such as implement rack angle, roll rate of the chassis, boom angle) or determined (such as rate of change of the boom angle, angular acceleration of the boom angle or the like). The kinematic characteristics are, in one example, analyzed to predict a height of the sensor  108  (or associated implement  102 , such as the boom  106 ) relative to reference location, such as the ground, canopy or the like. In the example shown in  FIG.  3    the predicted ground distance  306  corresponds to a predicted height (including a change in height in another example) of the boom  106  relative to ground at a location of the distance sensor  108  along the boom. For example, with kinematic characteristics including a boom angle measurement (e.g., boom angle  902  in  FIG.  9 A ) of the boom  106  and the location (distance) of the distance sensor  108  along the boom  106  both the angle and hypotenuse of a corresponding triangle are known and the predicted height of the boom  106  at the sensor  108  location is readily determined (e.g., with the sin product of the angle and the hypotenuse). 
     As described herein, the predicted ground distance  306  (or change in the predicted ground distance from a prior value) is a component for generating a predictive window  1018  including an optional predictive window shift  1020  as shown in  FIG.  10   . One or more of ground or canopy distance measurements (including changes in the measurements relative to a prior measurement) are compared with the predictive window to assess the reliability of the measurements for assignment of confidence values. 
     In another example, predicted ground distance  306  is optionally used in place of the ground or distance measurements  304 ,  302  for control of the implement position (e.g., operation of an actuator, such as implement actuator  406 ). For instance, if each of the confidence values for the ground and distance measurements  304 ,  302  fall below a minimum threshold value the automated implement control system  420  selects the predicted ground distance at the control basis and accordingly determines the deviation of the implement  102  (such as the boom  106 ) relative to difference between the predicted ground distance and a specified target distance, such as an optimal boom height relative to the ground. 
       FIG.  4    is a schematic view of the vehicle  100 , such as an agricultural sprayer, tow behind sprayer, trailer or the like. The vehicle  100  includes the agricultural implement  102  having the boom  106  and the implement rack  103  coupling the boom  106  with the vehicle  100 . On or more implement tools  200  are spaced along the boom  106 . The implement tools  200  include, but are not limited to, sprayer nozzles, planter row assemblies, harvester rows or sections, baler intakes or the like. 
     As further shown, the implement, such as the boom  106  includes one or more distance sensors  108 . In this example a plurality of distance sensors are at a plurality of locations along the boom  106  between an implement proximal end  400  and an implement distal end  402 . Each of the distance sensors  108  is spaced from a pivot point of the boom  106  relative to the chassis  101  and, when included, the implement rack  103 . The one or more distance sensors  108  are located at known distances from the pivot point of the boom  106  to facilitate the determination of boom height (e.g., distance from either or both of the canopy or ground). For example, the spacing of each of the sensors  108  is used to generate a predicted ground distance  306  as shown in  FIG.  3   . In another example, the spacing of each of the sensors  108  is used to generate a corresponding predictive window  1018  and window shift  1020  (collectively a predictive window) as described herein. 
     An implement actuator  406 , such as a hydraulic cylinder, motor or the like is proximate to the pivot point, for instance with a first end of the actuator  406  coupled with the boom  106  and a second end of the actuator coupled with the implement rack  103  or the chassis  101 . The implement actuator  406  controls the implement position of the agricultural implement  102 , such as the boom  106 . The implement actuator  406  is in communication with one or more components of the automated control system  420  shown in  FIG.  4   . 
     Referring again to  FIG.  4   , an example automated implement control system  420  is shown schematically relative to the vehicle  100  and the implement  102 , such as the boom  106 . The automated implement control system  420  in this example configuration includes an implement control module  404  in communication with the implement actuator  406  and the one or more distance sensors  108  provided on the boom  106 , and optionally provided on an opposed boom  106  as another portion of the implement  102  (see  FIG.  1   ). In the example shown in  FIG.  4   , an interface  408  provides one or more wireless or wired interconnections between the components of the automated implement control system  420 . The interface  408  includes, but is not limited to, one or more of bus, CAN bus, blue tooth transceivers, radio frequency transceivers, hardwiring or the like. 
     The automated implement control system  420  measures distances with the one or more distance sensors  108  and selects a corresponding one of the measured distance types, such as ground distance or canopy distance, as a control basis. As described herein, the selection of ground or canopy distance as the control basis is conducted in an ongoing manner and the system  420  switches between each of these control types according to a confidence assessment of the respective distance measurements. Deviation of the selected ground or canopy distance as the control basis from a specified target distance (e.g., an ideal application distance relative to the canopy, boom height relative to the ground or the like) is determined with the system  420  and used for guiding the implement, such as the boom  106 , toward the specified target distance. 
     Referring now to  FIG.  5   , a schematic diagram of the automated implement control system  420  is shown. In this example, the interface  500  includes a CAN bus interconnecting each of the components including the implement control module  404  and the one or more distance sensors  108 . As further shown in  FIG.  5   , one or more operator interfaces including touchscreens installed on a vehicle, field computer interfaces, remote input devices such as tablet applications, mobile phone applications or the like interconnect with the system  420 . In one example, the interface  500  includes a wireless transceiver configured to receive and transmit instructions and data to the one or more operator interfaces  502 . 
     As further shown in  FIG.  5   , an interface module  504  is optionally provided as a component of the automated implement control system  420 . The interface module provides one or more hardware or software modules (e.g., circuits, processors, computer readable medium or the like) to facilitate an interface between one or more components of the implement  102 , such as the implement actuator  406 , shown in  FIG.  4   . For example, the interface module  504  includes, but is not limited to, signal conditioners, amplifiers or the like for the processing of control and sensor signals to and from one or more of the implement actuator  406  and distance sensors  108 . In one example the interface module includes AC/DC converters, DC/AC converters, GPS interfaces or the like. In another example, the interface module  504  is optionally included as a component of the implement control module  404 , and the implement control module  404  directly interfaces with one or more components, such as the implement actuator  406 . 
       FIG.  6    is a perspective view of an example sensor for the distance sensors  108  described herein. The distance sensor  108  includes a sensor housing  602  configured for mounting to the implement  102 , for instance a boom  106  or other movable component of the implement  102 . As shown in  FIG.  4   , a plurality of distance sensors  108  are installed along the boom  106  to accordingly sense the distance of the implement (e.g., the sensor  108  mounted to the implement) relative to one or more objects including the ground or canopy. 
     As shown in  FIG.  6   , the distance sensor  108  includes a power and data port  604  configured to interface with a power supply and one or more components of the automated implement control system  420 , such as the implement control module  404 . For example, the distance sensor  108  relays values corresponding to measurements and sensor confidence (described herein) to the implement control module  404  by way of wired connection at the power and data port  604  or wireless interface coupled at the power and data port  604 . 
     The distance sensor  108  further includes a sensor emanator  600 . In the example sensor  108  shown in  FIG.  6   , the sensor emanator  600  includes one or more sensor elements, such as radar, light, ultrasound generating elements or the like configured to generate the corresponding energy and direct the energy toward the objects of interest (e.g., ground and crop canopy). In one example, the sensor emanator  600  also includes a receiver configured to receive the reflected energy after engagement with the objects and convert the reflected energy into a signal, for instance corresponding to either of the canopy or ground distances  302 ,  304  shown in  FIG.  3    and used at the implement control module  404 . In another example, a separate receiver is proximate to the distance sensor  108  and receives the reflected energy and converts the energy into the signal. 
     In another example, the sensor emanator  600  includes a plurality of sensor elements each calibrated to measure one of the distance to a first object type, such as the ground (ground distance) or the distance to a second object type, such as the crop canopy (canopy distance). Optionally, the sensor emanator  600  includes sing element, such as a radar generator, configured to emit radio frequency energy that partially reflects from a first object, such as the canopy, and reflects from additional objects, such as a second object beneath the canopy, such as the ground. The reflected energy is interpreted at the sensor  108  and provides a signal indicating distance measurements to a plurality of objects, for instance shown in  FIG.  3    as both of the canopy and ground distances  302 ,  304 . 
       FIG.  7    is an example schematic diagram of the implement control module  404 . As shown, the implement control module includes a control housing  700  enclosing a plurality modules configured to receive the canopy and ground distances  302 ,  304  as signals (shown graphically in  FIG.  3   ) assess the signals for use as a control basis for controlling the implement position, for instance of a component of an implement, such as the boom  106  shown in  FIGS.  1  and  4   . 
     The implement control module  404  includes a plurality of modules (e.g., submodules) comprising circuitry, computer readable media, software modules or the like configured to carry out the analysis described herein and implement the control basis to facilitate guidance of the implement toward a specified target distance, such as an optimal spray application range relative to the canopy, ground, plow depth, harvester head position, planting depth or the like. In the context of the implement control module  404  and the automated implement control system  420  reference is made to ground and canopy distances (including measured distances and previous measured distances having a higher reliability) for use with controlling the position of a boom  106 , such as a sprayer boom. The system  420 , module  404  and associated submodules and methodologies described herein are also applicable to the control of implements, chassis position or the like relative to a sensed object or plurality of objects. 
     Referring again to  FIG.  7   , the implement control module  404  includes an interface  702  such as a BUS, hardwiring between components such as memory, circuits processors or the like that facilitates communication between the various modules (e.g., circuitry, computer readable media, software modules or the like). As further shown, the implement control module  404  includes a data and power interface  722  configured to provide an interface with a power supply and one or more of the other components of automated implement control system  420 , for instance through the interface  500  shown in  FIG.  5   . Additionally, the implement control module optionally includes an actuator interface configured to interconnect the module  404  with one or more actuators, such as the implement actuator  406  shown in  FIG.  4   . Optionally, the data and power interface  722  includes the actuator interface  720 . 
     The implement control module  404 , as shown in  FIG.  7   , includes a target selection module  708  that selects a control basis for used by the control module  404  to determine deviation relative to a specified target distance (e.g., 60 inches above the ground as an operator specified boom height, 20 inches above canopy as an operator specified application distance or the like). As described herein the target selection module  708 , in one example, receives confidence values from the confidence module  706  and the confidence module in turn determines the confidence values through assessment of measurements (or changes in measurements) of ground and canopy distance with the implement prediction module  704 . The target selection module  708  compares the confidence values and selects the potential control base (e.g., ground distance of canopy distance) having the highest confidence, and accordingly the most reliable distance measurements (including measured distances as well as previously retained distances from prior measurements as described herein). The target selection module  708  conducts the assessment of the ground and canopy distances (including changes in the distances) in an ongoing manner, and thereby facilitates handing off of the control basis designation between ground distance and canopy distance according to updated confidence values (e.g. based on forthcoming distance measurements, predictions of the implement position or the like). 
     As further shown in  FIG.  7   , a target and deviation module  712  is provided. In one example, the target and deviation module  712  includes a deviation module  716  that compares the ground or canopy distance (whichever is selected by the target selection module as the control basis) relative to a specified target distance and determines the deviation of the implement position relative to the specified target distance. The implement control module  404  uses the determined deviation to accordingly guide the implement  102 , such as the boom  106 , toward the specified target distance through minimizing of the deviation with corresponding actuator with the implement actuator  406  (e.g., with feedback control or the like, for instance with the actuator module  718 ). The actuator module  718  shown in  FIG.  7    optionally converts the measured deviation to a control signal (directed to eliminate the deviation) delivered through the actuator interface  720  to the implement actuator  406 . 
     In another example, where the selected control basis (ground or canopy in an example) does not match a specified target designation and target distance the substitute target module  714  provides a substitute specified target distance configured to guide movement of the implement toward a position corresponding to the specified target distance, while using a control basis that different from the preference of an operator. For example, the operator preference module  712  includes one or more input preferences, such as a preferred target type (e.g., ground or canopy) called a specified target designation. The module  712  further includes an input preference of a specified target distance to the specified target designation, such as an optimal height of the implement relative to the ground (if ground is the target designation) or an optimal application distance relative to the canopy (if canopy is the designation). In an example, the operator preferences are ground as the specified target designation and 60 inches as the specified target distance. The target selection module  708  selects a non-preferred control basis, in this example canopy based control using the canopy distance  302  shown in  FIG.  3    (instead of the ground distance  304 ). If the specified target distance of 60 inches is applied with canopy distance as the control basis the implement  102  (e.g., the boom  106 ) would ‘fly’ up as the actuator module  718  attempts to position the boom  106  60 inches above the canopy. The substitute target module  714  provides a substitute target distance based on the specified target distance usable with a control basis that does not match the operator preference (e.g., the specified target designation). Control of the implement, including guidance of the implement using the control basis (in this example canopy) and the substitute target distance instead of the specified target distance accordingly moves the implement toward the specified target distance corresponding to the operator preferred specified target designation. The deviation module  716  is configured to use the substitute target distance with the control basis (again canopy in this example) to determine the deviation of the implement position relative to the substitute target distance, and facilitate control of the implement position through the actuator module  718 . The boom  106  accordingly moves toward the original operator preferred specified target distance while using the non-preferred other control basis (canopy) that is selected as the control basis because of its higher confidence. 
       FIG.  8    is a schematic view of an example implement control module architecture  800  for the implement control module  404 . The schematic view provides an overview of the control schematics shown in  FIGS.  9 A- 17 B . Referring first to the implement prediction module  704 , the module includes a vehicle and implement model analysis component  802  and a predictive window component  804 . The model analysis component  802  receives and analyzes one or more kinematic characteristics of the vehicle and implement to generate predicted values (e.g., of implement position including change in implement position). The predictive window element  804 , as described herein generates predictive windows  1018  and window shifts  1020  for the predicted values to assess reliability of measurements. 
     The confidence module  804  includes ground and canopy measurement reliability components  806 ,  808  configured to compare each of respective ground and canopy distance measurements with the predictive windows. As shown in elements  810 - 814  varying confidence values are assigned to the measurements (including previously retained values if the measurements are deemed unreliable) based on the location of the measurements (or their previous value counterparts) within or outside of the predictive window  1018 . 
     The target selection module  708 , for instance with the element  818 , selects either of the ground distance or canopy distance as the control basis by comparing the confidence values assigned to the measured distance to ground  1106  and measured distance to canopy  1206  (and including previously retained values such as distance to ground filtered  1102  or distance to canopy filtered  1202 ) as shown in  FIGS.  11 B , C and  FIGS.  12 B , C. In one example, the target selection module chooses canopy distance (measured values and retained values) or ground distance (measured values and retained values) as the control basis according to whichever of of the distances has the higher comparative confidence value. Further, the target selection module reassigns the control basis to the other, previously not selected, distance type if the confidence comparison changes to favor the other distance type. The target selection module  708  is thereby configured to hand off control between each of the one or more distance types including, but not limited to, ground distance or canopy distance. Optionally, the target selection module  708  includes a potential target bias for one of the distance types. This bias, shown in  FIG.  14 B , corresponds to an operator or machine based preference for control based on one of ground or canopy distances. For instance, one of the comparative confidences is biased up or down to accordingly weight the control basis to one of ground or canopy based distance control. 
     Referring again to  FIG.  8   , the target and deviation module  710  is includes the target and deviation element  822  including the sub-elements of target deviation  824  and substitute target generation  826 . Determination of target deviation and substitute target generation  826  are discussed herein in  FIGS.  15 - 16 B , and previously discussed in regard to the controller schematic shown in  FIG.  7   . The target and deviation module  710  further includes a substitute target refinement element  828  configured refine and thereby smooth the substitute target distances determined with the substitute target element  826 . 
       FIGS.  9 A , B are schematic diagrams of one example of an implement analysis module  900  (a sub-module) of the implement control module  404 . The implement analysis module  900  receives kinematic characteristics about the vehicle  100  including one or more of dimensions, speed, location, rotation or the like to determine one or more predictive values (and optionally measured or calculated values) associated with the agricultural implement  102 . For instance, as provided in the example herein, the implement analysis module  900  analyzes the motion of the vehicle  100  to determine one or more characteristics, such as a composite angular velocity of the implement  102 . Another component of the implement control module  404 , the implement prediction module  1000 , receives the values from the implement analysis module  900  to generate predictive windows and shifts in windows to assess the reliability of measurements from the one or more distance sensors  108  (e.g., shown in  FIG.  4   ). 
     Referring first to  FIG.  9 A , the implement analysis module  900  includes one or more inputs associated with corresponding segments (there are three segments in  FIG.  9 A ). In this example, the inputs and their segments include, but are not limited to, the boom angle  902  (e.g., implement angle), chassis roll rate  904  of the vehicle chassis  101  and the implement rack angle  906 , an optional second component value associated with the implement  102 . The inputs correspond to measurements provided with associated sensors including one or more of accelerometers, speedometers, encoders or the like configured to measure characteristics associated with the respective chassis  101  (roll angle, change in roll angle, rate of roll angle change or the like) and the implement  102  (e.g., the angle of one or more of the booms  106  or the implement rack  103 , changes in angles, rates of change of the same or the like). 
     As further shown in  FIG.  9 A , derivative elements  907  are provided with one or more of the characteristic inputs in the first and third segments. In this example, derivative elements  907  are associated with the boom angle  902  and implement rack angle  906  segments. The derivative elements generate rates of change (speeds or velocities) for each of these characteristic values to facilitate summation with the chassis roll rate  904  and thereby determine a composite characteristic value for the implement  102  (e.g., one or more of the booms  106 ). The corresponding derived values as well as the chassis roll rate  904  are, in another example, subject to low pass filters  908  of the implement analysis module  900  to smooth the values prior to summation, for instance by removing spikes, errant values or the like in the velocities or angles that otherwise skew the values used to generate the predictive values (e.g., windows and shifts in the windows). Accordingly, each of the segments generates a corresponding value including, for this example, filtered boom velocity  912 , a filtered roll rate  910  and a filtered center rack (implement rack) velocity  914 , for instance in units of degrees per second, radians per second or the like. 
     Referring now to  FIG.  9 B , the determined values  910 ,  912 ,  914  having common units are summed with the summation element  918  to generate a composite angular velocity  916  of the implement  102  (e.g., a composite implement kinematic value). The composite angular velocity  916  corresponds to the angular velocity of the implement, for instance one or more of the booms  106  (see  FIG.  4   ). When analyzed in combination with the position of each of the sensors  108  corresponding height change values for the implement, for instance proximate to the sensors  108 , are generated to accordingly provide predictive windows and predictive window shifts for analysis of measured values of the implement  102 . The composite angular velocity  916  is delivered to an implement prediction module  1000  shown in  FIG.  10   . In an example, the predictive window collectively includes the predictive window shift as well as the predictive window. 
     As shown in  FIG.  8   , the implement control module  404  (at  804 ) generates a predictive window for use in assessing the reliability of measured values, for instance taken with the distance sensors  108  associated with the implement  102 .  FIG.  10    is a schematic view of one example of an implement prediction module  1000 . The prediction module  1000  receives the composite angular velocity  916  of the implement  102 . In an example including the implement  102  as a rotating component, a predicted height change is determined based on the input composite angular velocity  916 . For instance, the length of the distance sensor from a joint, implement actuator  406  or the like is an example kinematic input  1002 . In the example shown in  FIG.  4   , the distance of one or more of the distance sensors  108  relative to the implement actuator  406  (or rotation joint for the boom  106 ) is a hypotenuse for a triangle extending between the actuator  406  and the sensor with the angle of the boom  106  as the acute angle of the triangle. As shown in  FIG.  10   , a predicted height change element receives the composite angular velocity  916  and the at least one kinematic input  1002  corresponding to an angle or change in angle of the implement  102  and the hypotenuse, respectively. The sine function determines a predicted height change value based on the composite angular velocity  916  and the kinematic input  1002 . As a convention and an example, the predicted height change is relative to a prior position of the implement  102 , for instance the last value corresponding to the height of the boom  106 . 
     As further shown in  FIG.  10   , the predicted height change value is received at the summation element  1008  and optionally added to one or more supplemental kinematic inputs  1006 . In one example, the supplemental kinematic inputs  1006  are distinct from the kinematic input  1002  and include, but are not limited to, changes in an implement rack height, changes in vehicle suspension height, and changes in vehicle suspension (e.g., changes to damping coefficients or spring constants) or the like. The height changes (kinematic inputs  1006 ) are optionally received at the summation element  1008  to provide a total predicted height change for further analysis. 
     Referring again to  FIG.  10   , the predicted height change (or total predicted height change) is used to determine a predictive window for analysis of the reliability of distances measured with the distance sensors  108 . The predictive window provides a range of values position measurements (e.g., distance measurements from the sensors  108 ) should be within. As described herein, measurements outside of the predictive window are in various examples disregarded or further analyzed, for instance with modification of the predictive window. 
     As shown in  FIG.  10    the example predictive window includes a predictive window  1018  and a predictive window shift  1020  (for the window  1018 ). A composite predictive window adds these values to a window size modification  1130  input (see  FIG.  11 A  having the summation element  1134 ). As shown in  FIGS.  11 A , B and  12 A, B actual measured distances (including changes in distance or height from a prior value) that fall within the shifted window determined with the implement prediction module  1000  have a higher reliability, and are accordingly considered ‘good’ data. These measured distances (e.g., of the distance sensors  108 ) thereby have a higher likelihood for use as the values for control of the implement position including height. Conversely, actual measured distances (changes in distance or height from a prior value) outside of the modified window (e.g., shifted, expanded or contracted) have a lower reliability, may be ‘bad’ data, and as described herein are disregarded (e.g., in favor of a previous ‘good’ value of implement position) or further analyzed, for instance, to determine if the measurements are in fact ‘good’ data and modification of the predictive window is warranted to capture forthcoming measurements. 
     The predictive window  1018  (the kinematic portion of the composite window generated with the summation element  1134  in  FIG.  11 A ) is determined with a predictive window element  1014 . As shown in  FIG.  10   , a reliability gain  1010  is received at the predictive window element  1014  along with the predicted height change (or total predicted height change). As previously described, the predicted height change is, in one example, a value corresponding to a predicted height change relative to a prior position (height) of the implement, such as the boom  106 . The predicted height change is multiplied by the reliability gain  1010  at the predictive window element  1014  to determine the predictive window  1018  (e.g., a window size or range of values). In an example, the predictive window corresponds to a range of predictive height change values (i.e., predicted height changes of ±6 inches, 12 to −3 inches, 0 to −10 inches relative to the previous boom height or the like) that are maintained (or contracted) according to the reliability gain  1010 . 
     In one example, the reliability gain  1010  is a static value, for instance set by an operator based on known variations in the terrain (e.g., the reliability gain is low for rough terrain or relatively higher for planar or consistent terrain). A higher reliability gain  1010  (e.g., a value closer to 1) corresponds to an assessment of higher reliability that the predicted height change is reasonable. In contrast, a lower reliability gain  1010  (e.g., a value less than 1, such as 0.12 or the like) corresponds to a lower assessment of reliability because of the unpredictability of rough (e.g., broken, uneven, shifting or angled) terrain and thereby indicates the predicted height change is less reliable. Accordingly, a higher reliability gain  1010  (e.g., 0.75 or more) maintains a large predictive window  1018  (including maintaining the predicted height change value or modestly contracting the value) and accordingly facilitates the capture of measured distance values within the window. In contrast, a lower reliability gain  1010  (e.g., 0.25 or less) contracts the predictive window  1018  and thereby minimizes the capture of measured distances to those values within the smaller window. In another example, the maintained (larger) and contracted (smaller) windows ensure corresponding measured values are captured in either of a broad high reliability window and thereby deemed reliable or, in the case of a narrow low reliability window only measured values that fall within the narrow (contracted) band of the low reliability gain modified window are deemed reliable. 
     As further shown in  FIG.  10   , another branch of the predicted window determination includes the predictive window shift  1020 . The predictive window shift  1020  corresponds to a shift in location of the predictive window  1018 . For instance, as previously described the predictive window  1018  includes a range of values, such as ±6 inches, 12 to −3 inches relative to the a prior implement position or height. The predictive window shift  1020  is additive and shifts the range to account for changes in the terrain, for instance including inclination, declination, change in pitch or roll or the like. The predictive window shift element  1016  controls the location of the predictive window by changing the ceiling and floor values of the range while maintaining the breadth of the range. In an example, the predictive window shift is included as a component of the predictive window, and accordingly the predictive window, in this example, collectively includes the predictive window shift as well as the predictive window. 
     For example, with the predictive windows  1018  described above, ±6 inches, 12 to −3 inches, the predictive window shift element  1016  uses another example reliability gain  1012  (a static or dynamic gain) to determine the predictive window shift  1020 . In one example, as the terrain is inclining the predicted window for the implement height (or height change) trends down as the implement moves closer to the rising terrain and a low gain is needed because of the unpredictability of the terrain variation (including a gain of 0 or proximate to 0). Accordingly, the predictive window shift element  1016  with a reliability gain moves the predictive window  1018  down (closer to the inclined ground). The reliability gain  1012  decreases the predictive window shift  1020  according to its value. For instance, the predictive window of ±6 inches may change to −11 to 1 inches, a net change of 5 inches downward while the range of the predictive window  1018  remains 12 total inches. With a reliability gain of 0.5 the shift is instead 2.5 inches, and the corresponding predictive window −8.5 to 3.5 inches (and the range remains 12 total inches) and less than the shift otherwise specified. In another example, for instance, as the implement is deployed from a stowed position to an initial application height the boom moves a large distance and possibly at a relatively high velocity. In this example, the reliability gain is optionally higher, such 1, 0.9 or the like because deployment is consistent has a limited risk of collision with the ground or flying up of the boom. 
     The determination of ground measurement reliability at  806  is conducted in one example with a ground reliability module, such as the ground reliability module  1100  shown in  FIGS.  11 A , B. The ground reliability module  1100  analyzes the reliability of the measured position of the implement  102 , for instance the distance of the boom  106  (shown in  FIG.  4   ) relative to the ground. In contrast,  FIGS.  12 A , B show an example canopy reliability module  1200  configured to analyze the measured position of the implement  102  relative to the canopy. The reliability modules  1100 ,  1200  assess the reliability of the respective measurements (distance to ground or distance to crop canopy) relative to the predictive window previous described herein including the predictive window  1018  and optionally the predictive window shift  1020 . 
     Referring first to  FIG.  11 A , the module  1100  uses a previous filtered value  1102  (e.g., distance to ground filtered or DGF) for implement position, for instance determined at the opposed end of the module  1100  proximate to the  1114  condition element described herein. The previous filtered value  1102  corresponds to a previous implement position (in this example relative to the ground), such as a preceding height of the boom  106 . The predictive window shift  1020  determined with the implement prediction module  1000  is added to the previous filtered value  1102  at the summation element  1104  to adjust the previous filtered value  1102  according to the predicted intervening change (if any) to an adjusted filtered value. 
     The ground reliability module includes a difference element  1105  (e.g., a comparator) that assess a difference between the adjusted filtered value provided by the summation element  1104  and a measured distance to ground  1106 . The measured distance to ground is the measurement value returned by one or more of the distance sensors  108  associated with the implement  102 , such as the boom  106 . The difference element  1106  generates a ground error between the adjusted filtered value and the measured distance to ground. The ground error corresponds to the variation of the measured distance relative to the preceding filtered value (adjusted based on the predictive window shift  1020 ). 
     The ground error is delivered to another difference element  1108  for assessment relative to the predictive window  1018  generated with the implement prediction module (e.g., a range of values corresponding to a predicted range of movement for the implement) shown in  FIG.  10   . The difference element  1108  assesses whether the ground error (based on the measured distance to ground) is within the predictive window  1018  to determine the reliability of the distance to ground measurement. According to the convention shown in  FIG.  11 A , if the value generated by the difference element  1105  is less than or equal to zero (0) the ground error and the corresponding measured distance to ground are within the predictive window  1018 . The measured distance to ground is thereby indicated as reliable. If the value generated by the difference element  1105  is greater than zero (0) the ground error and its corresponding measured distance to ground are outside of the predictive window  1018  and thereby indicated as unreliable. In an example described herein, a measured distance to ground having the unreliability indication is further analyzed including, in one example, modification of the predictive window. For example, the ground reliability module  1100  shown in  FIG.  11 A  optionally includes a window size modification  1130  input interrelated with a window size modification submodule  1116  shown in  FIG.  11 B . 
     Referring again to  FIG.  11 A , the ground reliability module  1100  in this example includes a condition element that provides a notification of ‘true’ if the comparison of the ground error corresponding to the measured distance to ground is within the predictive window  1018 , in this example, if the value returned by the difference element  1105  is less than or equal to zero (0). The condition element provides a ‘false’ notification if the value is greater than zero (0) corresponding to the ground error and the corresponding measured distance to ground are outside of the predictive window  1018 . The true of false indication is a window capture condition  1112 . 
     The assessment of the distance to ground measurement (measured distance  1106 ) by way of comparison of the ground error with the predictive window  1018  determines whether the measured distance  1106  or the previous filtered value  1102  is more reliable. The corresponding window capture condition  1112  (true or false) indicates the higher reliability and is used within the condition element  1114  in  FIG.  11 B  to update the previous filtered value  1102  (e.g., distance to ground or DGF). If the window capture condition  1112  is true the ground error for the measured value  1106  is within the predictive window  1018  and the previous filtered value  1102  is updated to  1102 ′ and matches the measured value  1106 . If the window capture condition is false, and thereby corresponds to the measured value outside the predictive window, the previous filtered value  1102  remains at the present value (e.g., as value  1102 ′). For instance, the measured value  1106  is ignored, at least for the time being, in favor of the previous filtered value  1102 . As previously described the previous filtered value  1102  (now  1102 ′ whether updated or maintained at the previous value) is returned to the beginning of the ground reliability module  1100  for use in assessment of ongoing distance measurements  1106 . 
     In another example, the distance sensors  108  are configured to measure one or more types of object, such as the ground, canopy, furrow depth, crop residue height and a comparison of confidences as shown in forthcoming  FIGS.  11 C,  12 C and  13    is not performed, and a control basis is not handed off (e.g., from canopy to ground or ground to canopy). Instead, the reliability module  1100  (and similarly the reliability module  1200 ) provides a control basis having the retained or updated values of the measured distance  1106  and distance to ground filtered  1102 . The predictive window  1018  is used to retain measurements within the window and discard measurements outside of the window  1018  (although the discarded measurements are used to iteratively adjust the window as described herein). The distance to ground filtered  1102  (e.g.,  1102 ′) on the right side of the condition element  1114  corresponds to either the newly retained measured distance  1106  or the previous distance to ground filtered. The implement control module  404  thereby uses the conditioned distance to ground filtered  1102  for control of implement position without handing off control to another target type (e.g., canopy distance). 
     In some examples the measured distance  1106  (e.g., distance to ground) measured by the distance sensor  108  is outside of the predictive window  1018 , but is not a ‘bad’ unreliable measurement as is otherwise the determination when outside the window. For example, the terrain sensed with the distance sensors  108  includes significant variation caused by declination, inclination, holes, furrows or the like. Alternatively, in the example including the measured distance to the canopy  1206 , described herein, the crops constituting the canopy include widely varying heights, variations in hydration that obscure canopy measurement, gaps in the crops or canopy or the like. In these examples, the measured distances to these features are in fact ‘good’ measurements that in other systems are errantly ignored or discarded. In the present system, the ground reliability module  1100  includes an optional window size modification submodule configured to further analyze these distance measurements (and forthcoming distance measurements) through modification of the predictive window. 
     As shown in  FIG.  11 B , the window size modification submodule  1116  (shown in dashed lines) receives the window capture condition  1112 . The ‘false’ condition at the condition element  1132  triggers an expansion prompt  1120 . As described herein the expansion prompt  1120  (a positive one (1)) initiates a graduated expansion of the predictive window  1018  to facilitate capture of potentially ‘good’ measured distances  1106 . A tracking time constant  1122  corresponding to a rate of change for the window modification and the expansion prompt  1120  are received at a modification element  1124 . The modification element  1124  multiplies the tracking time constant  1122  and the expansion prompt to provide a graduated expansion factor. A repetition loop  1128  including a summation element  1126  then develops a window size modification  1130  by adding the expansion factor to itself until the ground error (shown in  FIG.  11 A  as the output of the difference element  1105 ) is within the modified window including the predictive window  1018  and the window size modification  1130 . For example the window size modification  1130  is iteratively increased until the ground error is within the updated window (including the original predictive window  1018  and the modification  1130 ). Suspension of the iterative increase is shown with the saturation block (having floor and ceiling values for contraction and expansion) in the repetition loop  1128  of  FIG.  11 B . As shown in  FIG.  11 A , the window size modification  1130  is provided to a summation element  1134  and added to the predictive window  1018 . The updated and now larger predictive window is compared with the ground error with the difference element  1108  to determine if the measured distance  1106  (such as the next or forthcoming measured value after the triggering measurement) is within the updated window. In one example, if the ground error for the measured distance  1106  is not within the updated window a ‘false’ condition from the condition element  1110  triggers another expansion prompt  1120  and a corresponding expanding window size modification  1130 . Accordingly, measured distances  1106  that are ‘good’ but initially outside of the predictive window  1018  and thereby indicated as unreliable are accurately reclassified (or later measured distances are classified) as reliable with the window size modification submodule  1116  with modification of the predictive window by the window size modification  1130 . 
     In another example, the window size modification submodule  1116  is used with measured distances  1106  having corresponding ground errors within the predictive window  1018  (or previously updated window including a window size modification) in contrast to being outside the window as described above. In this example, the predictive window  1018  is contracted around the previous ground error to refine capture of forthcoming measured distances  1106 . For instance, a contraction prompt  1118  is triggered with the condition element  1132  according to a preceding ‘true’ (within the predictive window) capture condition  1112 . As shown in  FIG.  11 B , the contraction prompt  1118  is a negative one (−1) and is multiplied by the modification time constant  1122  at the modification element  1124  to accordingly generate a contracting window size modification  1130 . The contracting window size modification  1130  is provided to the summation element  1134  (in  FIG.  11 A ) to accordingly contract the predictive window  1018 . Measured distances  1106  within the contracted window accordingly have a higher reliability than values in the previous larger window. The measured distances  1106  assessed in the contracted window and having higher reliability thereby refine and enhance the maintenance of the previous filtered value  1102  (if the distances  1106  are outside the contracted window) and updating the value  1102  to the measured distance  1106  (if the distances  1106  are within the contracted window) at the condition element  1114 . 
     An example ground confidence module  1150  for the implement control module  404  is shown in  FIG.  11 C . In the example shown, the condition element  1138  uses the window capture condition  1112  (e.g., having ‘true’ or ‘false’ values) previously determined with the ground reliability module  1100  to provide a comparative ground confidence  1144  for comparison with a corresponding comparative canopy confidence  1244  (see  FIG.  12 C ). In this example, the ground confidence value  1136  of the ground confidence module  1150  corresponds to a confidence value provided by the one or more distance sensors  108  (e.g., a sensor confidence). In addition to the base measurement value (e.g., 40 inches, 52 inches or the like) the distance sensors  108 , in examples, provide a confidence value for the measurement. The confidence value provided by the sensor in various examples corresponds to one or more of a number of clustered reflections at the target (e.g., the ground), standard deviation, resolution of the measurement, signal strength or the like that are represented with a numerical confidence value as the ground confidence value  1136 . 
     Referring to  FIG.  11 C , the window capture condition  1112  is received at the condition element  1138 . The condition element  1138  chooses a first ground confidence value  1136  (the upper or ‘true’ branch) or a second ground confidence value  1136  further modified with a confidence weight  1140  (the lower of ‘false’ branch). For instance, if the ground error corresponding to the measured distance  1106  is within the predictive window  1018  as shown in  FIG.  11 A , the window capture condition  1112  is ‘true’ and accordingly the condition element  1138  updates the comparative ground confidence  1144  to the ground confidence value  1136  (e.g., corresponding to the sensor confidence described herein). Conversely, if the ground error is outside of the predictive window  1018 , the window capture condition  1112  is ‘false’ and accordingly the condition element  1138  selects from the lower branch including the ground confidence value  1136  further modified downward with the difference element  1142  by the confidence weight  1140 . The confidence weight  1140  is optionally static or dynamic. In one example, the confidence weight  1140  is varied in a graduated manner according to the relative deviation of the measured ground distance  1106  relative to the predictive window  1018  (e.g., the composite window including the window modification  1130  and the predictive window  1018 ). For instance, a larger deviation from the window may prompt an increase in the confidence weight  1140 . The comparative ground confidence  1144  is updated to the lower confidence value, the ground confidence value  1136  (e.g., a sensor based confidence) minus the confidence weight  1140 . As described herein, the comparative ground confidence  1144  is compared with the comparative canopy confidence  1244  to thereby select the distance measurement (ground or canopy) deemed most reliable (see  FIGS.  13  and  14 A , B). 
       FIGS.  12 A-C  provide another example of reliability analysis and confidence generation. In this example, the implement control module  404  includes a canopy reliability module  1200  configured to determine the reliability of distance measurements from the sensor  108  to the canopy of the crop. Features shown in  FIGS.  12 A-C  are similar in at least some regards to those previously shown in  FIGS.  11 A-C  and described herein. For instance, the module  1200  receives as an input a previous filtered value  1202  corresponding in this example to a distance to canopy (e.g., distance to canopy filtered or DCF). The previous filtered value  1202  corresponds to a previous implement position (in this example relative to the canopy), such as a preceding height of the boom  106  or sensor relative to the canopy. The predictive window shift  1020  determined with the implement prediction module  1000  is added to the previous filtered value  1202  at the summation element  1204  to adjust the previous filtered value  1102  according to the predicted intervening change (if any) to an adjusted filtered value. 
     The canopy reliability module  1200  includes a difference element  1205  (e.g., a difference element is an example of a comparator) that assesses a difference between the adjusted filtered value provided by the summation element  1204  and a measured distance to canopy  1206 . The measured distance to canopy  1206  is the measurement value returned by one or more of the distance sensors  108  associated with the implement  102 , such as the boom  106 . The measured distance corresponds to the distance from the canopy to the sensor optionally offset to account for vertical position differences between the sensor and the implement  102 . The difference element  1205  generates a canopy error between the adjusted filtered value and the measured distance to ground  1206 . The ground error corresponds to the variation of the measured distance relative to the preceding filtered value  1202  (adjusted based on the predictive window shift  1020 ). 
     The predictive window  1018 , generated with the implement prediction module (e.g., a range of values corresponding to a predicted range of movement for the implement) shown in  FIG.  10   , is received at the difference element  1208  to assess whether the canopy error is within the predictive window  1018  to determine the reliability of the distance to canopy measurement  1206 . As in the ground reliability module  1100 , the canopy reliability module  1200  is optionally configured to further analyze canopy measurements outside of the predictive window  1018 , for instance with modification of the predictive window. 
     Referring again to  FIG.  12 A , the canopy reliability module  1100  includes a condition element  1210  having a ‘true’ notification if the comparison of the canopy error corresponding to the measured distance to canopy  1206  is within the predictive window  1018 . The condition element  1210  provides a ‘false’ notification if the value is outside of the predictive window  1018 . The true of false indication is a window capture condition  1212 . 
     The assessment of the distance to canopy measurement (measured distance  1206 ) by way of comparison of the canopy error with the predictive window  1018  determines whether the measured distance  1206  or the previous filtered value  1202  is more reliable. The corresponding window capture condition  1212  (true or false) indicates the higher reliability and is used within the condition element  1214  in  FIG.  12 B  to update the previous filtered value  1202  (e.g., distance to canopy or DCF). If the window capture condition  1212  is true the canopy error for the measured value  1206  is within the predictive window  1018  and the previous filtered value  1202  is updated to  1202 ′ to match the measured value  1206 . If the window capture condition  1212  is false, and thereby corresponds to the measured value outside the predictive window, the previous filtered value  1202  remains at the present value (e.g., as value  1202 ′). For instance, the measured value  1206  is ignored, at least for the time being, in favor of the previous filtered value  1202 . As previously described the previous filtered value  1202  (now  1202 ′ whether updated or maintained at the previous value) is returned to the beginning of the canopy reliability module  1200  for use in assessment of ongoing distance measurements  1206 . 
     As with the ground measured distance  1106  (e.g., distance to ground) described herein the measurements are ‘good’ but outside of the predictive window  1018 . In a similar manner ‘good’ canopy measured distances  1206  are in some examples also outside of the predictive window  1018 , but still ‘good’ (or true) measurements that happen to fall outside of a predictive window  1018  predicated on earlier measurements and stored values without taking into account instant or contemporaneous measurements. In the example including the measured distance to the canopy  1206  the crops constituting the canopy include widely varying heights, variations in hydration that obscure canopy measurement, gaps in the crops or canopy or the like. In these examples, the measured distances to these features are in fact ‘good’ measurements that in other systems are errantly ignored or discarded. In the present system (e.g., with the implement control module  404 ), the canopy reliability module  1200  includes an optional window size modification submodule  1216  configured to further analyze these distance measurements (and forthcoming distance measurements) through modification of the predictive window  1018 . 
     As shown in  FIG.  12 B , the window size modification submodule  1216  (shown in dashed lines) receives the window capture condition  1212  with the ‘false’ condition at the condition element  1232  triggering an expansion prompt  1220 . A tracking time constant  1222  corresponding to a rate of change for the window modification and the expansion prompt  1220  are received at a modification element  1224 . The modification element  1224  multiplies the tracking time constant  1222  and the expansion prompt to provide a graduated expansion factor. A repetition loop  1228  including a summation element  1226  then develops a window size modification  1230  by adding the expansion factor to itself until the canopy error (shown in  FIG.  12 A  as the output of the difference element  1205 ) is within the modified window including the predictive window  1018  and the window size modification  1230 . For example the window size modification  1230  is iteratively increased until the ground error is within the updated window (including the original predictive window  1018  and the modification  1230 ). Optionally, the increase (or decrease) is suspended with a saturation block having a floor and ceiling value to limit expansion and contraction as shown in the repetition loop  1228 . As shown in  FIG.  12 A , the window size modification  1230  is provided to a summation element  1234  and added to the predictive window  1018 . The updated and now larger predictive window is compared with the canopy error with the difference element  1208  to determine if the measured distance  1206  (e.g., the next or forthcoming value or measurement of the canopy distance  1206 ) is within the updated window. In one example, if the ground error for the measured distance  1206  is not within the updated window a ‘false’ condition from the condition element  1210  triggers another expansion prompt  1220  and a corresponding expanding window size modification  1230 . Accordingly, measured distances  1206  that are ‘good’ but initially outside of the predictive window  1018  and thereby indicated as unreliable are accurately reclassified as reliable with the window size modification submodule  1216  with modification of the predictive window by the window size modification  1230 . 
     In another example, the window size modification submodule  1216  is used with measured distances  1206  having (corresponding canopy errors) within the predictive window  1018 . In this example, as with the ground errors described above the predictive window  1018  is contracted around the previous canopy error to refine capture of forthcoming measured distances  1206 . For instance, a contraction prompt  1218  is triggered with the condition element  1232  according to a preceding ‘true’ (within the predictive window) capture condition  1212 . The contraction prompt  1218  is negative and is multiplied by the modification time constant  1222  at the modification element  1224  to accordingly generate a contracting window size modification  1230 . The contracting window size modification  1230  is provided to the summation element  1234  (in  FIG.  12 A ) to accordingly contract the predictive window  1018 . Measured distances  1206  within the contracted window accordingly have a higher reliability than values in the previous larger window. The measured distances  1206  assessed in the contracted window and having higher reliability thereby refine and enhance the maintenance of the previous filtered value  1202  (if the distances  1206  are outside the contracted window) and updating the value  1202  to the measured distance  1206  (if the distances  1206  are within the contracted window) at the condition element  1214 . 
       FIG.  12 C  is an example canopy confidence module  1250  for the implement control module  404 . The condition element  1238  uses the window capture condition  1212  previously determined with the canopy reliability module  1200  to provide a comparative ground confidence  1244  for comparison with the corresponding comparative canopy confidence  1144  (see  FIG.  11 C ). In this example, the canopy confidence value  1236  of the canopy confidence module  1250  corresponds to a confidence value provided by the one or more distance sensors  108  (e.g., a sensor confidence). In addition to the base measurement value (e.g., 20 inches, 32 inches or the like) the distance sensors  108 , in examples, provide a confidence value for the canopy measurement. The confidence value provided by the sensor in various examples corresponds to one or more of a number of clustered reflections at the target (e.g., the canopy), standard deviation, resolution of the measurement, signal strength or the like that are represented with a numerical confidence value as the canopy confidence value  1236 . 
     Referring again to  FIG.  12 C , the window capture condition  1212  is received at the condition element  1238 . The condition element  1138  assigns a first canopy confidence value  1236  (the upper or ‘true’ branch) or a second canopy confidence value  1236  further modified with a confidence weight  1240  (the lower of ‘false’ branch). For instance, if the canopy error corresponding to the measured distance  1206  is within the predictive window  1018  as shown in  FIG.  12 A , the window capture condition  1212  is ‘true’ and accordingly the condition element  1238  updates the comparative canopy confidence  1244  to the canopy confidence value  1236  (e.g., corresponding to the sensor confidence described herein). Conversely, if the ground error is outside of the predictive window  1018  and thereby a ‘false’ window capture condition  1212  the condition element  1238  selects from the lower branch including the canopy confidence value  1236  further modified downward with the difference element  1242  by the confidence weight  1240 . The confidence weight  1140  is optionally static or dynamic. The comparative canopy confidence  1244  is updated to the lower confidence value, the canopy confidence value  1236  (e.g., a sensor based confidence) minus the confidence weight  1240 . As described herein, the comparative canopy confidence  1244  is compared with the comparative ground confidence  1144  to thereby select the distance measurement (ground or canopy) deemed most reliable (see  FIGS.  13  and  14 A , B). 
       FIGS.  13 ,  14 A and  14 B  show an example target selection module  1300  corresponding to element  818  (and optionally element  820 ) with the example implement control module architecture of  FIG.  8   . The target selection module  1300  compares the comparative ground and canopy confidences  1144 ,  1244  and, based on the comparison, selects either of the ground measured distance  1106  or the canopy measured distance  1206  for control of the implement  102 , for instance as the chosen signal for measurement of the implement relative to the ground or canopy, respectively. 
     Referring first to  FIG.  13   , as shown each of the ground and canopy comparative confidences  1144 ,  1244  are provided to a confidence filter  1302  in this example. The confidence filter  1302  smooths the input confidences to accordingly remove spikes and trough in confidence values corresponding to inconsistent sensor confidence values received from the sensors  108  (e.g., the ground confidence value  1136  or canopy confidence value  1236  of  FIGS.  11 C,  12 C ). Additionally, in the example shown in  FIG.  13   , the confidence filter  1302  includes a comparator, such as a difference element, that subtracts one of the confidences from the other. In this example, the comparative canopy confidence  1244  is subtracted from the comparative ground confidence  1144  to determine a confidence difference  1304  (confidence delta or the like). In one example, the confidence difference  1304  (if positive) indicates the comparative ground confidence  1144  is greater than the canopy confidence  1244  thereby indicating the ground measured distance  1106  is more reliable than the canopy measured distance  1206 . 
     In another example, shown in  FIG.  14 A , a target bias  1406  is provided to the target selection module  1300  to bias the confidence evaluation and corresponding target selection toward one of the measured distances  1106 ,  1206 . A difference element  1400  receives the target bias  1406  and the confidence difference  1304 . In an example favoring selection of the measured ground distance  1106  a negative target bias  1406  is provided to the difference element  1400 . When the negative target bias  1406  is subtracted (thereby making its value positive and prompting addition) from the confidence difference  1304  the confidence difference accordingly increases. In the convention provided in the target selection module  1300  the increased confidence difference favors the ground measured distance  1106 . 
     With a converse (positive) target bias  1406  the difference element  1400  decreases the confidence difference  1304  (the bias is subtracted) thereby biasing the target selection based on the confidence difference toward the canopy measured distance  1206 . In still other examples, the target bias  1406  is variable, and optionally changes according to location of the vehicle  100  in a field (e.g., elevations, previous indexed yield values or the like); the crop in the present row(s) under application; hydration of the crop (e.g., based on rainfall) or the like. For instance, after a heavy rain the target bias  1406  is optionally increased from a previous bias value to favor control based on the canopy measured distance  1206  because the crop is well hydrated and thereby readily sensed with the distance sensors  108 . In another example, the target bias  1406  is optionally decreased to a negative value less than the previous bias value because of decreased hydration, immaturity of the crop (and corresponding lesser canopy coverage) or the like to accordingly favor selection of the ground measured distance  1106  because the crop is difficult to detect, and accordingly the ground should (generally) provide a more reliable target. 
       FIG.  14 B  shows one example of a target bias input  1412  for use as the target bias  1406 . In another example, the target bias input  1412  includes an operator accessible feature (dial, touchscreen, toggles or the like) to facilitate variation of the target bias input  1412  and the corresponding the target bias  1406 . In still another example, the target bias input  1412  includes one or more functions, algorithms or the like configured to automatically control (e.g., change, maintain or the like) the target bias  1406 , for instance according to conditions described above such as hydration, crop maturity, crop identification, field conditions or the like. 
     Referring again to  FIG.  14 A , a condition element  1408  receives the confidence difference  1304  (or biased confidence difference) and designates either of the ground selection  1402  or the canopy selection  1404 . According to the convention shown a positive confidence difference  1304  or biased confidence difference triggers the ground selection  1402  by the condition element  1408  while a negative confidence difference (or biased confidence difference) triggers the canopy selection  1404 . The condition element  1408  updates the target selection  1410  (e.g., the control basis) and the implement control module  404  accordingly proceeds with control of the implement  102 , for instance of one or more booms  106 , based on the ground or canopy measured distances  1106 ,  1206  corresponding to the target selection  1410 . For instance, control of the implement actuator  406  to position the boom  106  (shown in  FIG.  4   ) at a specified height relative to the ground or the canopy (e.g., for ideal spray application to a crop) is conducted based on the selected ground or canopy measured distances  1106 ,  1206 . The control outlined in  FIG.  8    and shown in various examples in  FIGS.  9 A- 14 B  is conducted in an ongoing manner to accordingly automatically determine the reliability of ground and canopy measurements, compare confidences, and accordingly select the highest confidence (best) target and corresponding measured distances  1106 ,  1206  for control of the implement  102 . The implement control module  404  is thereby configured to automatically shift the selected target and corresponding measured distances automatically while the vehicle  100  moves through a field to accordingly control the implement  102  with the highest reliability measurements. 
     In another example, configuration, for instance with an implement including multiple distance sensors  108 , comparative confidence values are generated for each of the sensors (and optionally multiple confidence values for each sensor corresponding to ground and canopy comparative confidences). In this example, the target selection module  1300  compares each of these respective confidence values and according designates as the control basis one of the canopy or ground distance associated with one of the plural sensors  108 . Further, as the target selection module  1300  updates the target selection  1410  (the control basis), the module  1300  accordingly chooses the canopy or ground distance having the highest associated comparative confidence across the plural sensors  108 . 
     In still other examples the implement control module  404  conducts the assessments described herein (e.g., in  FIGS.  9 A- 14 B ) for one or more components of the implement. For example, separate booms  106 , different locations along a boom  106  or the implement  102  and their corresponding measured distances (e.g., measured by the sensors  108 ) are assessed for reliability and the targets selected based on the confidence comparisons. Optionally, a first boom  106  is controlled based on the ground measured distance  1106  while a second opposed boom  106  is controlled based on the canopy measured distance  1206  because of a higher canopy confidence relative to the ground confidence. In other examples, with booms  106  having multiple sensors  108 , as shown in  FIG.  4   , the selected confidences of each of the sensors  108  including ground and canopy confidences for each are compared and the highest confidence between the multiple sensors is designated as the target selection  1410 . Accordingly, the distance measurements from the corresponding sensor  108  are used as for control of the implement (e.g., relative to the selected canopy or ground) while the values from the other sensors  108  are ignored until the confidences change sufficiently to trigger reselection to a difference target, sensor or the like. In still other examples, the confidence differences  1304  from each of the sensors  108  are compared, and the largest (largest positive or least negative) value is chosen to select the appropriate sensor and its corresponding highest confidence target (ground or canopy). 
       FIGS.  15 - 17    include example control architecture for the implement control module  404  for control of the one or more implements  102  of the vehicle  100 . The example control architecture shown uses the target selection  1410  (see  FIG.  14 A ) corresponding to the selection of either of a ground or canopy target and its corresponding ground or canopy measured distances  1106 ,  1206  to control the implement  102 . For instance, the selected ground measured distance  1106  or canopy measured distance  1206  is used to determine the implement position relative to the target (ground or canopy) and control the implement, for instance with the implement actuator  406 , to position the implement at a specified distance to the specified target, for instance by way of a feedback control loop. For instance, the operator sets a specified target  1504  as the ‘canopy’ (in contrast to ‘ground’), and the specified distance to specified target  1506  is a distance, such as 20 inches. The specified target  1504  and the specified distance to specified target  1506  correspond to an operator chosen preference to position the implement  102 , such as the boom  106 , at 20 inches above the sensed canopy. In one example, the specified distance to specified target  1506  corresponds to an optimal application distance for an agricultural product sprayed from the booms  106 . Deviation from the specified distance to specified target because of implement movement (e.g., because of terrain or crop height variation) is measured as canopy error. The canopy error is used with a feedback control loop to move the implement  102  with the implement actuator  406  to minimize the canopy error and accordingly achieve the specified distance to specified target  1506 . 
       FIG.  15    provides one example of a schematic representation of a target distance submodule  1500  configured to receive the specified target  1504  and the specified distance to specified target  1506  as operator input preferences. The submodule additionally receives the measured distances from the sensor (or implement offset according to the position of the sensor) to each of the canopy and the ground. In one example, the distances provided to the target distance submodule  1508  corresponds to the distance to canopy filtered  1202  (e.g.,  1202 ′, DCF or the like) shown in  FIGS.  12 A , B and the distance to ground filtered  1102  (e.g.,  1102 ′, DGF or the like) shown in  FIGS.  11   , B. For instance, the distances correspond to actual measurements to the ground or canopy or previous values of the same based on the assessment at the example condition elements  1210 ,  1214  shown in  FIGS.  12 A , B. 
     The target distance submodule  1508  receives the inputs and generates target distances, for instance one or more of a target ground distance  1510  and a target canopy distance  1512 . In an example including the operator input preferences  1502 , such as the specified target  1504  (ST) and the specified distance to specified target  1506  (SDST) one of the target distances corresponds to the specified distance to target  1506 . For instance, if the ST  1504  is the canopy and the SDST is 20 inches (e.g., an optimal application distance or the like) the target canopy distance  1512  corresponds to 20 inches, the input SDST. Conversely, if the ST  1504  is the ground the SDST is 60 inches the target ground distance  1510  is 60 inches. 
     The other target canopy distance, either of the target ground or target canopy distances  1510 ,  1512  not corresponding to the ST  1504  is determined by the target distance submodule  1508 . As described herein, the determined target distance is a component for the determination of a corresponding ground or canopy target substitute  1610 ,  1612  ( FIGS.  16 A- 18   ) that provides a substitute control for the implement  102  if the measured distance corresponding to the specified target  1504 , such as distance to ground or canopy  1102 ,  1202 , ‘disappears’. For instance, if the specified target  1504  is the canopy (e.g., with a specified distance of 20 inches from the canopy) ‘disappearance’ of the canopy occurs in various examples including, but not limited to, merging of a canopy signal (canopy measurements) with the ground signal (ground measurements), irregularity in the canopy signal or the like that decreases the canopy confidence, such as the comparative canopy confidence  1244  ( FIGS.  12 C and  13   ), relative to the comparative ground confidence  1144  ( FIGS.  11 C and  13   ) to trigger control of the implement based on the distance to ground  1102  (including  1102 ′). Because control is switched in this example from canopy to ground (or conversely in another example from ground to canopy) the specified distance to specified target  1506  is not, by itself, an accurate target. For instance, if the previous canopy SDST  1506  of 20 inches was used after having shifted to control based on distance to ground  1102  the implement  102  would lower to achieve the 20 inch height and in some examples crash into the crop, ineffectively apply the agricultural product below the canopy or the like. Accordingly, a substitute target value is used with the substitute control scheme to minimize inaccurate positioning with changes in control schemes. 
       FIGS.  16 A , B are example component submodules of the target distance submodule configured to determine control deviation from target values as well determine substitute target distances based on an input target distance, such as the specified distance to specified target  1506 . Referring first to  FIG.  16 A , a target deviation submodule  1600  is configured to determine deviations of the implement position relative to the ST  1504  and the SDST  1506 . For canopy error  1606  a comparator, such as a difference element  1602 , receives the SDST  1506  and the distance to canopy filtered  1202  (including  1202 ′ updated with either of the most recent measured distance  1206  or the previous filtered value  1202 ). In an example with the ST  1504  and the SDST  1506  corresponding to the canopy and a target distance relative to canopy, the canopy error  1606  corresponds to the deviation of the position of the implement  102 , such as a boom  106 , relative to the SDST. The difference element  1602  compares the SDST  1506  with the distance to canopy filtered  1202 , and the output deviation or canopy error  1606  corresponds to the difference in position of the implement  102 , such as the boom  106 , relative to the canopy SDST  1506 . The canopy error  1606  is readily used to control an actuator, such as the implement actuator  404 , to guide the boom  106  toward the SDST. 
     In a similar manner, where the ST  1504  and SDST  1506  correspond to a ground target and a specified distance to ground (e.g., 40 inches, 60 inches or the like) ground error  1604  is determined through comparison of the ground SDST  1506  with the distance to ground filtered  1102  at the difference element  1602  in the lower portion of the target deviation submodule  1600 . The deviation or ground error  1604  corresponds to the difference in position of the implement  102  relative to the ground SDST  1506 . 
     As previously described herein, in another example the distance measurement, for instance one of distance to canopy or distance to ground  1202 ,  1102 , does not match the specified target  1506  and the corresponding specified distance to specified target  1506 . For example, the comparative ground or canopy confidences  1144 ,  1244  trigger control with the other of the canopy or ground distances ( 1202 ,  1102 ). In this scenario the specified target  1504  and specified distance to specified target  1506  are different than the measured distance (e.g., the distance to canopy or distance to ground  1202 ,  1102 ), and the canopy or ground errors  1606 ,  1604  are not used (directly) for control of the implement because of the mismatch between the canopy or ground distance measurements  1202 ,  1102  and the ground or canopy ST  1504  and SDST  1506 . Instead, the canopy or ground error  1606 ,  1604  in that instance is used to determine a canopy target substitute  1612  or ground target substitute  1610  as an alternative target relative to the ST  1504  and SDST  1506 .  FIGS.  16 B,  17  and  18    show example determinations of the target canopy or target ground substitutes  1612 ,  1610 . 
     Referring first to  FIG.  16 B , two examples are provided for determination of ground and canopy target substitutes  1610 ,  1612  (e.g., example substitute specified target distances) as part of a substitute target submodule  1601  of the target and deviation submodule  1508 . In the first (upper) example a ground target substitute  1610  is determined where the specified target (ST or specified target designation)  1504  is ‘canopy’ and the specified distance to specified target (SDST or specified target distance to the specified target designation)  1506  is a specified target distance from the implement  102 , such as a distance sensor  108  on a boom  106 , to the canopy (e.g., an optimal application distance for a sprayed agricultural product of 20 inches). A summation element  1608  adds the canopy error  1606  from the target deviation submodule  1600  to the distance to ground filtered  1102  (DGF, including  1102 ′ for measured distance or a previous, higher reliability, value). The resulting ground target substitute  1610  (e.g., a substitute specified target distance) corresponds to the summation. Because the ground target substitute  1610  includes the canopy SDST  1506  in the canopy error  1606 , adjusted by the distance to ground filtered  1102 , the ground target substitute  1610  accounts for the differing (canopy) specified target  1604  with a value (the canopy SDST) used with control based on the ground measurements. Accordingly, if the comparative canopy confidence  1244  decreases beneath the comparative ground confidence  1144  (thereby initiating a handoff from canopy to ground control) a corresponding ground target substitute  1610  is readily provided to facilitate the alternative control based on the ground measurements (e.g., distance to ground filtered  1102 ,  1102 ′) while positioning the implement  102  (boom  106 ) proximate to the canopy SDST  1506 . Crashing of the boom  106  into the crop or flying of the boom  106  above an optimal application distance are according avoided, and instead the implement readily and smoothly transitions from canopy based control to the substitute ground based control. Conversely, as the comparative canopy confidence  1244  increases relative to the comparative ground confidence  1144  the system returns to canopy based control of the implement using the canopy SDST and the canopy error  1606  shown in the upper portion of  FIG.  16 A . 
     In a converse scenario shown in the second (lower) example, a canopy target substitute  1612  (another example substitute specified target distance) is determined where the specified target (ST)  1504  is ‘ground’ and the specified distance to specified target (SDST)  1506  is a specified target distance from the implement  102  (e.g., distance sensor  108  on the implement) to the ground, such as 40 inches. A summation element  1608  adds the ground error  1604  from the target deviation submodule  1600  to the distance to canopy filtered  1202  (DCF, including  1202 ′ for measured distance or a previous, higher reliability, value). The canopy target substitute  1612  corresponds to the summation. Because the canopy target substitute  1612  includes the ground SDST  1506  in the ground error  1604 , adjusted by the distance to canopy filtered  1202 , the canopy target substitute  1612  accounts for the differing (ground) specified target  1604  with a value (the ground SDST) used with control based on the canopy measurements. Accordingly, if the comparative ground confidence  1144  decreases beneath the comparative canopy confidence  1244  (thereby initiating a handoff from ground to canopy control) a corresponding canopy target substitute  1612  is readily provided to facilitate the alternative control based on the canopy measurements (e.g., distance to canopy filtered  1202 ,  1202 ′) while positioning the implement  102  (boom  106 ) proximate to the ground SDST  1506 . Flying of the boom  106  above an optimal application distance is accordingly avoided, and instead the implement readily and smoothly transitions from ground based control to the substitute canopy based control. Conversely, as the comparative ground confidence  1144  increases relative to the comparative canopy confidence  1244  the system returns to ground based control of the implement using the ground SDST and the ground error  1604  shown in the lower portion of  FIG.  16 A . 
       FIGS.  17 A,  17 B  are example filter modules for the ground and canopy target substitutes  1610 ,  1612  determined as shown in  FIGS.  16 A , B. As previously discussed the STSD  1506  is in one example a static value input by the operator, for instance as an optimal application distance, implement height or the like. In contrast, the ground and canopy target substitutes  1610 ,  1612  while based on the STSD are also based on the respective canopy error  1606  and ground error  1604 . Each of the canopy error  1606  and ground error  1604  vary according to changes in their respective distance to ground  1102  (e.g.,  1102 ′, DGF) and distance to canopy (e.g.,  1202 ′, DCF). The target and deviation module  1508  includes the substitute ground target filter  1700  in  FIG.  17 A  and the substitute canopy target filter  1750  in  FIG.  17 B  to smooth the variation in the respective substitute target distances otherwise included with these values based on the respective canopy and ground errors  1606 ,  1604 . Each of the filters  1700 ,  1750  operates in a similar manner to the previously described ground and canopy reliability modules  1100 ,  1200 . For instance, an initial ground target substitute  1610  is compared with a previous or retained value of the substitute  1610 ′ at the difference element  1702  (an example of a comparator). 
     The difference between these values is compared at the difference element  1704  with a corresponding ground window  1706 . The ground window  1706  is generated in a similar manner to the previously described iterative expansion or contraction of with a window for the predictive windows used for reliability analysis. In this filtering example, the ground window  1706  has an initial range, and the initial range is iteratively expanded or contracted according to the condition element  1710 , window gain  1712  and the corresponding repetition block and summation element  1714  having a saturation window to limit expansion or contraction of the ground window. The substitute ground window  1706 ′ is returned for comparison with forthcoming differences between the ground target substitute  1610  and  1610 ′ (a previous reliable value). 
     As further shown in  FIG.  17 A , after assessment with the ground window  1706  the ground target substitute  1610  or the previously retained value  1610 ′ is selected and delivered to a low pass filter  1726  and corresponding spikes the value are isolated and removed. For instance the filter  1726  conducts filtering of the value according to a variable time constant. The variable time constant is determined with the updated value for the ground target substitute  1610  and the preceding value  1610 ′ (if the updated value matches the preceding value the time constant is effectively zero and the value is not filtered and passes through. According to the difference between these values (e.g., determined with the difference element  1718 ) the time constant is modulated, for instance with first and second (optionally variable) filter values  1720 ,  1722 . For example, if the difference is negative then the lower (and smaller) second filter value  1722  is used, and if the difference is positive then the upper (and larger) first filter value  1720  is used. The smaller second filter value  1722 , in one example, corresponds to a decrease in the ground target substitute (e.g., an example substitute specified target distance) and is smaller to accordingly limit the decrease of the target distance to minimize the risk of collisions with the ground as the implement is guided to the lower target distance. Conversely an upward change of the ground target substitute (distance) in one example is preferred and accordingly the first filter value  1720  is larger and triggers more rapid filtering and change in the ground target substitute. 
     The value returned by the filter  1726 , an updated ground target substitute  1610 ′ is returned to the difference element  1702  for comparison with forthcoming values of the target ground substitute received from the summation element  1608  shown in  FIG.  16   . 
     In a similar manner, canopy target substitute  1612  evaluated and filtered with the substitute canopy target filter  1750 . For example, the filter  1750  includes a comparison between the canopy target substitute  1612  and a previous value that has been filtered  1612 ′. The difference between these values is evaluated relative to a canopy window (and the canopy window is optionally modified as described for the ground window). The updated canopy target substitute received from the condition element  1758  is then filtered at the low pass filter  1776  in a similar manner to the low pass filter  1726  shown in  FIG.  17 A . 
     Various Notes and Aspects 
     Aspect 1 can include subject matter such as an automated implement control system for controlling movement of an agricultural implement comprising: one or more distance sensors configured for coupling with an agricultural implement, the one or more distance sensors each include: a ground sensing element configured to measure a ground distance from the one or more sensors to the ground; and a canopy sensing element configured to measure a canopy distance from the one or more sensors to a crop canopy; an implement control module in communication with the one or more distance sensors, the implement control module controls movement of the agricultural implement, and the implement control module includes: at least one confidence module configured to determine a ground confidence value based on the measured ground distance and a canopy confidence value based on the measured canopy distance; a target selection module configured to select one of the measured ground distance or the measured canopy distance as a control basis for controlling movement of the agricultural implement, the target selection module selection based on a comparison of the ground and canopy confidence values; and an actuator module configured to control movement of the agricultural implement according to the selected control basis. 
     Aspect 2 can include, or can optionally be combined with the subject matter of Aspect 1, to optionally include wherein the ground sensing element and the canopy sensing element are components of a unitary sensor. 
     Aspect 3 can include, or can optionally be combined with the subject matter of one or any combination of Aspects 1 or 2 to optionally include wherein the unitary sensor includes a radar instrument. 
     Aspect 4 can include, or can optionally be combined with the subject matter of one or any combination of Aspects 1-3 to optionally include wherein the ground sensing element and the canopy sensing element are separate components of the one or more distance sensors. 
     Aspect 5 can include, or can optionally be combined with the subject matter of one or any combination of Aspects 1-4 to optionally include the agricultural implement; and wherein the agricultural implement includes a sprayer boom. 
     Aspect 6 can include, or can optionally be combined with the subject matter of Aspects 1-5 to optionally include wherein the target selection module is configured to select the measured ground distance or the measured canopy distance according to the greater of the ground and canopy confidence values. 
     Aspect 7 can include, or can optionally be combined with the subject matter of Aspects 1-6 to optionally include wherein the confidence module includes: a predictive comparator configured to compare the measured ground or canopy distances to a predictive window corresponding to one or more of a predicted implement position or predicted change in implement position; and a confidence assignment element configured to: determine the ground confidence value according to the comparison of the measured ground distance to the predictive window; and determine the canopy confidence value according to the comparison of the measured canopy distance to the predictive window. 
     Aspect 8 can include, or can optionally be combined with the subject matter of Aspects 1-7 to optionally include wherein the one or more distance sensors are configured to provide a respective sensor confidence; and the confidence assignment element is configured to determine the ground confidence value and the canopy confidence value based on the sensor confidence. 
     Aspect 9 can include, or can optionally be combined with the subject matter of Aspects 1-8 to optionally include wherein the implement control module includes an implement prediction module configured to predict one or more of an implement position or change in implement position according to one or more kinematic inputs for the agricultural implement. 
     Aspect 10 can include, or can optionally be combined with the subject matter of Aspects 1-9 to optionally include wherein the kinematic inputs include one or more of implement angle, chassis roll rate of a vehicle chassis or implement rack angle of an implement rack between another component of the agricultural implement and the vehicle chassis. 
     Aspect 11 can include, or can optionally be combined with the subject matter of Aspects 1-10 to optionally include wherein the implement prediction module is configured to generate a predictive window corresponding to one or more of the predicted implement position or predicted change in implement position. 
     Aspect 12 can include, or can optionally be combined with the subject matter of Aspects 1-11 to optionally include wherein the one or more distance sensors includes a plurality of component distance sensors, the at least one confidence module includes a plurality of component confidence modules, wherein each of the component confidence modules is associated with a respective component distance sensor, and the component confidence module is configured to: determine the ground and canopy confidence values for the respective distance sensor; and the target selection module is configured to select one of the measured ground distances or the measured canopy distances of the plurality of component distance sensors as the control basis for controlling movement of the agricultural implement according to a comparison of the ground and canopy confidence values of the component confidence modules. 
     Aspect 13 can include, or can optionally be combined with the subject matter of Aspects 1-12 to optionally include wherein the target selection module is configured to select the measured ground distance or the measured canopy distance according to the greater of the corresponding ground and canopy confidence values of the component confidence modules. 
     Aspect 14 can include, or can optionally be combined with the subject matter of Aspects 1-13 to optionally include wherein the implement control module includes an actuator interface in communication with the actuator module, and the actuator interface is configured to couple the implement control module with the agricultural implement. 
     Aspect 15 can include, or can optionally be combined with the subject matter of Aspects 1-14 to optionally include wherein the implement control module includes an actuator module configured to control movement of the sprayer boom according to the control basis and a specified target distance to at least one of the ground or canopy, and the specified target distance corresponds to an operator preferred specified target. 
     Aspect 16 can include, or can optionally be combined with the subject matter of Aspects 1-15 to optionally include wherein the implement control module includes a substitute target module configured to determine a substitute specified target distance to the canopy or ground based on the specified target distance corresponding to the operator preferred specified target; and wherein the actuator module is configured to control movement of the sprayer boom according to the substitute specified target distance and an updated control basis different than the operator preferred specified target. 
     Aspect 17 can include, or can optionally be combined with the subject matter of Aspects 1-16 to optionally include an automated implement control system for controlling an implement position comprising: one or more distance sensors configured for coupling with an agricultural implement, the one or more distance sensors are configured to measure a ground distance to ground and a canopy distance to a crop canopy relative to the one or more distance sensors; an implement control module in communication with the one or more distance sensors, the implement control module includes: a target selection module configured to select one of ground distance or canopy distance as a control basis; and a target and deviation module configured to implement the selected ground distance or canopy distance as the control basis, the target and deviation module includes: an operator preference module having a specified target designation and a specified target distance relative to the specified target designation; a substitute target module configured to determine a substitute specified target distance if the control basis is different than the specified target designation; and a deviation module configured to determine deviation of an implement position based on the control basis and the specified target distance if the control basis corresponds to the specified target designation or the substitute specified target distance if the control basis is different than the specified target designation. 
     Aspect 18 can include, or can optionally be combined with the subject matter of Aspects 1-17 to optionally include wherein the one or more distance sensors include a radar instrument. 
     Aspect 19 can include, or can optionally be combined with the subject matter of Aspects 1-18 to optionally include the agricultural implement; and wherein the agricultural implement includes a sprayer boom. 
     Aspect 20 can include, or can optionally be combined with the subject matter of Aspects 1-19 to optionally include wherein the implement control module includes an actuator module configured to control implement position of the agricultural implement according to the determined deviation of the selected control basis from the corresponding specified target distance or substitute specified target distance. 
     Aspect 21 can include, or can optionally be combined with the subject matter of Aspects 1-20 to optionally include wherein the implement control module includes an actuator module configured to guide the implement position of the agricultural implement toward the specified target distance including: controlling the implement position according to the determined deviation based on the control basis and the specified target distance if the control basis corresponds to the specified target designation; and controlling the implement position according to the determined deviation based on the control basis and the substitute specified target distance if the control basis is different than the specified target designation. 
     Aspect 22 can include, or can optionally be combined with the subject matter of Aspects 1-21 to optionally include wherein the deviation module includes a comparator configured to determine the deviation of the agricultural implement as a difference of the measured ground or canopy distance as the control basis relative to one of the specified target distance or the substitute specified target distance. 
     Aspect 23 can include, or can optionally be combined with the subject matter of Aspects 1-22 to optionally include wherein the substitute target module includes a summation element configured to determine the substitute specified target distance based on the summation of: a preceding determined deviation of the control basis corresponding to the specified target relative to the specified target distance; and a proceeding ground or canopy distance of the control basis different than the specified target designation. 
     Aspect 24 can include, or can optionally be combined with the subject matter of Aspects 1-23 to optionally include wherein the implement control module includes a confidence module configured to determine a ground confidence value based on the measured ground distance and a canopy confidence value based on the measured canopy distance. 
     Aspect 25 can include, or can optionally be combined with the subject matter of Aspects 1-24 to optionally include wherein the target selection module includes a comparator configured to compare the ground and canopy confidence values; and the target selection module is configured to select one of the ground distance or the canopy distance as the control basis having the greater respective ground or canopy confidence value. 
     Aspect 26 can include, or can optionally be combined with the subject matter of Aspects 1-25 to optionally include wherein the confidence module includes: a predictive comparator configured to compare the measured ground or canopy distances to a predictive window corresponding to a predicted implement position or predicted change in implement position; and a confidence assignment element configured to: determine the ground confidence value according to the comparison of the measured ground distance to the predictive window; and determine the canopy confidence value according to the comparison of the measured canopy distance to the predictive window. 
     Aspect 27 can include, or can optionally be combined with the subject matter of Aspects 1-26 to optionally include wherein the one or more distance sensors provide a sensor confidence; and the confidence assignment element is configured to determine the ground confidence value and the canopy confidence value based on the sensor confidence. 
     Aspect 28 can include, or can optionally be combined with the subject matter of Aspects 1-27 to optionally include a method for controlling an implement position of an agricultural implement comprising: measuring a ground distance from one or more distance sensors to ground; measuring a canopy distance from the one or more distance sensors to a crop canopy; selecting a control basis for controlling movement of an agricultural implement, selecting includes: determining a ground confidence value based on the measured ground distance, and determining a canopy confidence value based on the measured canopy distance; comparing the ground and canopy confidence values; and assigning one of the ground distance or the canopy distance as the control basis according to the comparison; repeating selection of the control basis with ongoing measurements of ground and canopy distance; and controlling the implement position according to either of the ground distance or the canopy distance assigned as the control basis. 
     Aspect 29 can include, or can optionally be combined with the subject matter of Aspects 1-28 to optionally include wherein assigning one of the ground distance or the canopy distance as the control basis according to the comparison includes assigning the ground distance or the canopy distance as the control basis according to the greater of the ground and canopy confidence values. 
     Aspect 30 can include, or can optionally be combined with the subject matter of Aspects 1-29 to optionally include wherein determining the ground and canopy confidence values includes: comparing each of the ground distance and the canopy distance to a predictive window, the predictive window corresponding to one or more of a predicted implement position or predicted change in implement position; and establishing the ground confidence value according to the comparison of the ground distance to the predictive window; and establishing the canopy confidence value according to the comparison of the canopy distance to the predictive window. 
     Aspect 31 can include, or can optionally be combined with the subject matter of Aspects 1-30 to optionally include wherein establishing the ground confidence value includes establishing a greater ground confidence value if the ground distance is within the predictive window; and establishing the canopy confidence value includes establishing a greater canopy confidence value if the canopy distance is within the predictive window. 
     Aspect 32 can include, or can optionally be combined with the subject matter of Aspects 1-31 to optionally include wherein establishing the ground and canopy confidence values includes establishing the ground and canopy confidence values according to a sensor confidence provided by the one or more distance sensors. 
     Aspect 33 can include, or can optionally be combined with the subject matter of Aspects 1-32 to optionally include generating the predictive window with one or more kinematic inputs, generating the predictive window includes: determining a composite implement kinematic value based on the summation of the one or more kinematic inputs; determining the predictive window based on the composite implement kinematic value. 
     Aspect 34 can include, or can optionally be combined with the subject matter of Aspects 1-33 to optionally include wherein controlling the implement position according to either of the ground distance or the canopy distance assigned as the control basis includes: comparing the control basis to a specified target designation having an associated specified target distance; determining a substitute specified target distance if the control basis is different than the specified target designation; and assessing a deviation of the implement position, assessing the deviation includes: determining the deviation relative to the specified target distance and the control basis if the control basis corresponds with the specified target designation; and determining the deviation relative to the substitute specified target distance and the control basis if the control basis is different than the specified target designation; and guiding the implement position to minimize the determined deviation and move toward one of the specified target distance or the substitute specified target distance according to respective correspondence or difference of the control basis relative to the specified target designation. 
     Aspect 35 can include, or can optionally be combined with the subject matter of Aspects 1-34 to optionally include wherein guiding the implement position to minimize the determined deviation and move toward the substitute specified target distance with the control basis different than the specified target designation moves the implement position toward the specified target distance associated with the specified target designation. 
     Aspect 36 can include, or can optionally be combined with the subject matter of Aspects 1-35 to optionally include wherein determining the substitute specified target distance includes summing: a preceding determined deviation relative to the specified target distance and the control basis corresponding to the specified target designation; and a proceeding ground or canopy distance different than the specified target designation. 
     The above detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show, by way of illustration, specific embodiments in which the disclosure can be practiced. These embodiments are also referred to herein as “examples.” Such examples can include elements in addition to those shown or described. However, the present inventors also contemplate examples in which only those elements shown or described are provided. Moreover, the present inventors also contemplate examples using any combination or permutation of those elements shown or described (or one or more aspects thereof), either with respect to a particular example (or one or more aspects thereof), or with respect to other examples (or one or more aspects thereof) shown or described herein. 
     In the event of inconsistent usages between this document and any documents so incorporated by reference, the usage in this document controls. 
     In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In this document, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, composition, formulation, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. 
     Method examples described herein can be machine or computer-implemented at least in part. Some examples can include a computer-readable medium or machine-readable medium encoded with instructions operable to configure an electronic device to perform methods as described in the above examples. An implementation of such methods can include code, such as microcode, assembly language code, a higher-level language code, or the like. Such code can include computer readable instructions for performing various methods. The code may form portions of computer program products. Further, in an example, the code can be tangibly stored on one or more volatile, non-transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of these tangible computer-readable media can include, but are not limited to, hard disks, removable magnetic disks, removable optical disks (e.g., compact disks and digital video disks), magnetic cassettes, memory cards or sticks, random access memories (RAMs), read only memories (ROMs), and the like. 
     The above description is intended to be illustrative, and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. Other embodiments can be used, such as by one of ordinary skill in the art upon reviewing the above description. The Abstract is provided to comply with 37 C.F.R. § 1.72(b), to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. This should not be interpreted as intending that an unclaimed disclosed feature is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that such embodiments can be combined with each other in various combinations or permutations. The scope of the disclosure should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.