Patent Publication Number: US-2022236402-A1

Title: Object tracking device

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is the U.S. bypass application of International Application No. PCT/JP2020/038150 filed on Oct. 8, 2020, which designated the U.S. and claims priority to Japanese Patent Application No. 2019-188667 filed on Oct. 15, 2019, the contents of both of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to an object tracking device for tracking an object. 
     BACKGROUND 
     A target motion estimation device as described in JP 3629328 B generates a target based on a radar signal from a radar device, and performs tracking of the target. More specifically, the above device calculates a predicted value for the position of a target in a current processing cycle based on an estimated value of the target in a previous processing cycle, and sets a prediction gate centered on the predicted value. The above device then, from among observed values of observed positions in the current cycle, correlates an observed value that is within the set prediction gate and that is closest to the predicted value with the predicted value, and calculates an estimated value in the current processing cycle based on the correlated observed value and the predicted value. In this kind of device for tracking an object, when there is an observed value that is not correlated with the predicted value, that observed value is handled as a new target. 
     SUMMARY 
     An object tracking device according to one aspect of the present disclosure estimates a state quantity of at least one target for each preset processing cycle, and includes: a detection unit, a prediction unit, a first region setting unit, a selection unit, an estimation unit, a registration unit, a prohibition region setting unit, and a registration prohibition unit. The detection unit is configured to detect at least one observed value from an observation signal observed by a sensor. At least one observed value is information about at least one target around a vehicle. The prediction unit is configured to calculate a predicted value of a current state quantity from an estimated value of a past state quantity for each target included in the at least one target. The first region setting unit is configured to set a first region based on the predicted value for each predicted value calculated by the prediction unit. The first region is a region where it is estimated an observed value will be obtained this time. The selection unit is configured to select an observed value from at least one observed value detected by the detection unit for each of the predicted values calculated by the prediction unit, the observed value being within the first region set by the first region setting unit. The estimation unit is configured to calculate the estimated value of the current state quantity based on the observed value selected by the selection unit for each predicted value calculated by the prediction unit. The registration unit is configured to register the observed value of at least one observed value detected by the detection unit that is not correlated with any predicted value as a new target. The prohibition region setting unit is configured to set a prohibition region for each predicted value calculated by the prediction unit. The prohibition region is a region where observed values are prohibited from being registered as new targets. The registration prohibition unit is configured to prohibit the observed values of at least one observed value detected by the detection unit within the prohibition region set by the prohibition region setting unit from being registered as new targets by the registration unit. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above features of the present disclosure will be made clearer by the following detailed description, given referring to the appended drawings. In the accompanying drawings: 
         FIG. 1  is a block diagram illustrating the configuration of an object tracking device according to a first embodiment; 
         FIG. 2  is a block diagram illustrating the configuration of an object tracking device according to the first embodiment; 
         FIG. 3  is a flowchart illustrating an object tracking process executed by the object tracking device according to the first embodiment; 
         FIG. 4  is a flowchart of a subroutine illustrating a registration prohibition determination process executed by the object tracking device according to the first embodiment; 
         FIG. 5  is a diagram illustrating a first region for correlating a predicted value and an observed value, and a prohibition region for prohibiting registration of a new target according to the first embodiment; 
         FIG. 6  is a flowchart illustrating an object tracking process executed by the object tracking device according to a second embodiment; 
         FIG. 7  is a flowchart of a subroutine illustrating a prohibition region setting process according to the second embodiment; 
         FIG. 8  is a diagram illustrating an example of first to fourth regions that are the prohibition region for prohibiting registration of a new target according to the second embodiment; 
         FIG. 9  is a diagram illustrating a different example of first to fourth regions that are prohibition regions for prohibiting registration of a new target according to the second embodiment; 
         FIG. 10  is a diagram illustrating a first region that is a prohibition region for prohibiting the registration of a new target, and a noise region for prohibiting the registration of noise according to the second embodiment; 
         FIG. 11  is a diagram illustrating a third region that is a prohibition region for prohibiting the registration of a new target, and a noise region for prohibiting the registration of noise according to the second embodiment; 
         FIG. 12  is a diagram illustrating a state of estimating a shape of a target according to the second embodiment; 
         FIG. 13  is a diagram illustrating the shape of the first region, the prohibition region, and the noise region according to another embodiment; and 
         FIG. 14  is a diagram illustrating the shape of the first region, the prohibition region, and the noise region according to another embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     In a case of using a high-resolution radar, by obtaining a plurality of observed values from the same object, a plurality of targets may be generated from the same object. As a result of detailed examination, the inventors discovered a problem in that in a case where in a processing cycle following a processing cycle in which a plurality of targets are generated, when the number of obtained observations becomes less than the number of recognized targets, competition for observed values occurs between the targets currently being tracked and generated from the same object and new targets. When an observed value is correlated with a new target as a result of the occurrence of competition for the observed value, it is no longer possible to continue to track the target that is currently being tracked, and tracking of a new target will begin. 
     On the other hand, as a driving support system for a vehicle, there are driving support systems in which the longer that tracking of a target continues, the reliability of the tracking result increases, and when the reliability becomes equal to or greater than a threshold value, the tracking result is used for performing control of the vehicle. In such driving support systems, when the tracking of a target is lost and tracking has to begin again, a delay in vehicle control may result. 
     One aspect of the present disclosure is that it is desirable to be able to stably track a target. 
     An object tracking device according to one aspect of the present disclosure estimates a state quantity of at least one target for each preset processing cycle, and includes: a detection unit, a prediction unit, a first region setting unit, a selection unit, an estimation unit, a registration unit, a prohibition region setting unit, and a registration prohibition unit. The detection unit is configured to detect at least one observed value from an observation signal observed by a sensor. At least one observed value is information about at least one target around a vehicle. The prediction unit is configured to calculate a predicted value of a current state quantity from an estimated value of a past state quantity for each target included in the at least one target. The first region setting unit is configured to set a first region based on the predicted value for each predicted value calculated by the prediction unit. The first region is a region where it is estimated an observed value will be obtained this time. The selection unit is configured to select an observed value from at least one observed value detected by the detection unit for each of the predicted values calculated by the prediction unit, the observed value being within the first region set by the first region setting unit. The estimation unit is configured to calculate the estimated value of the current state quantity based on the observed value selected by the selection unit for each predicted value calculated by the prediction unit. The registration unit is configured to register the observed value of at least one observed value detected by the detection unit that is not correlated with any predicted value as a new target. The prohibition region setting unit is configured to set a prohibition region for each predicted value calculated by the prediction unit. The prohibition region is a region where observed values are prohibited from being registered as new targets. The registration prohibition unit is configured to prohibit the observed values of at least one observed value detected by the detection unit within the prohibition region set by the prohibition region setting unit from being registered as new targets by the registration unit. 
     According to an aspect of the present disclosure, for each target, a predicted value for the current state quantity is calculated based on an estimated value of the past state quantity, and for each calculated predicted value, a first region is set based on the predicted value. Then, of acquired observed values detected for each predicted value, an observed value is selected from among the observed values within the first region to be correlated with the predicted value, and based on the selected observed value and predicted value, an estimated value is calculated for the current state quantity. Furthermore, a prohibition region is set for each predicted value, and of the acquired observed values, an observed value that is not correlated with any of the predicted values and that is outside the prohibition region is registered as a new target. On the other hand, even in the case of an observed value that is not correlated with any predicted value, there is a high probability that an observed value that is within the prohibition region was observed from the same object as an observed value that is correlated with a predicted value. Accordingly, an observed value that is within the prohibition region is prohibited from being registered as a new target. Therefore, it is possible to prohibit the generation of a plurality of targets from the same object. As a result, it is possible to stably track a target. 
     In the following, exemplary embodiments for implementing the present disclosure will be described with reference to the drawings. 
     First Embodiment 
     &lt;1-1. Configuration&gt; 
     First, the configuration of a driving support system  100  according to the present embodiment will be described with reference to  FIG. 1 . The driving support system  100  includes a radar device  10 , an object tracking device  20 , and a driving support device  50 . 
     The radar device  10  may be mounted in the center of the front (for example, the center of the front bumper) of a vehicle  80 , and may have a region in the center of the front of the vehicle  80  as a detection region. Moreover, a radar device  10  may be mounted on both the left front side and the right front side (for example the left end and right end of the front bumper) of the vehicle  80 , and may have both the front on the left and the front on the right of the vehicle  80  as detection regions. Furthermore, a radar device  10  may be mounted on both the left rear side and the right rear side (for example the left end and right end of the rear bumper) of the vehicle  80 , and may have both the rear on the left and the rear on the right of the vehicle  80  as detection regions. Not all of these five radar devices  10  need be mounted in the vehicle  80 . It is possible to mount only one of the five radar devices  10  in the vehicle  80 , and it is also possible to mount two or more of the five radar devices  10  in the vehicle. 
     The radar device  10  is a high-resolution millimeter wave radar. The radar device  10  has a transmitting array antenna that includes a plurality of antenna elements, and a receiving array antenna that includes a plurality of antenna elements. The radar device  10  repeatedly transmits a transmission wave at a specified cycle, and receives the reflected wave that is generated by reflecting the transmission wave by the object. Furthermore, the radar device  10  generates a beat signal by mixing the transmission wave and the reflected wave, and outputs a sampled beat signal (in other words, observation signal) to the object tracking device  20 . The radar device  10  may use any modulation method such as the FMCW method, multi-frequency CW method, or the like. 
     The object tracking device  20  includes a microcomputer having a CPU, and a semiconductor memory such as ROM, RAM or the like. The object tracking device  20  achieves various functions by the CPU executing various programs stored in the ROM. More specifically, as illustrated by the solid lines in  FIG. 2 , the object tracking device  20  achieves the functions of a detection unit  21 , a prediction unit  22 , a first region setting unit  23 , a selection unit  24 , an estimation unit  25 , a prohibition region setting unit  27 , a registration prohibition unit  29 , and a registration unit  30 , and executes an object tracking process. The object tracking device  20  outputs target information generated by executing the object tracking process to the driving support device  50 . Note that the object tracking process will be described in detail later. 
     The driving support device  50  uses the target information generated by the object tracking device  20 , and state information and behavior information of the vehicle  80  obtained from various sensors mounted in the vehicle  80  to control the vehicle  80  and achieve driving support. 
     &lt;1-2. Processing&gt; 
     Next, the object tracking process that is executed by the object tracking device  20  according to the first embodiment will be described with reference to the flowchart in  FIG. 3 . The object tracking device  20  repeatedly executes this process at a specified cycle. 
     First, in S 10 , the detection unit  21  detects observed values for targets existing around the vehicle  80  from observation signals that are acquired from the radar device  10 . The observed values include the electric power value of the observation signal, distance from the vehicle  80  to the target, orientation of the target with respect to the vehicle  80 , and relative speed of the target with respect to the vehicle  80 . Note that the observed values, instead of the relative speed of the target, may also include the ground speed of the target calculated from the relative speed and speed of the vehicle  80 . 
     Next, in S 20 , the prediction unit  22  determines whether there is any unprocessed target information. More specifically, determines whether there are any registered targets for which the following process from S 30  to S 80  has not been performed. When it is determined that there is an unprocessed target, processing advances to S 30 . 
     In S 30 , the prediction unit  22  calculates a predicted value for a state quantity of the target in the current processing cycle based on an estimated value for the state quantity of the target calculated in the previous processing cycle. The predicted value for the state quantity of the target, as in the case of the observed value, may have the electric power value P of the observation signal, the distance R to the target, the orientation θ of the target, and the velocity Vr of the target as elements, or may have the electric power P of the observation signal, the X-axis coordinate value Cx, the Y-axis coordinate value Cy, the velocity Vx in the X direction, and the velocity Vy in the Y direction as elements. The X-axis is an axis along the width direction of the vehicle  80 , the and the Y-axis is orthogonal to the X-axis and is an axis along the length direction of the vehicle  80 . Moreover, the velocity Vr may be a relative velocity with respect to the vehicle  80 , or may be the ground speed. The velocity Vx in the X direction may be the X-direction component of the relative velocity of the target with respect to the vehicle  80 , or may be the X-direction component of the ground speed of the target. The velocity Vy in the Y direction may be the Y-direction component of the relative velocity of the target with respect to the vehicle  80 , or may be the Y-direction component of the ground speed of the target. 
     Next, in S 40 , the first region setting unit  23  sets a first region based on at least one element of the predicted value calculated in S 30 . The first region is a region where it is estimated that the observed value will be acquired in the current processing cycle. An observed value that is detected from the same object as a predicted value should be a value close to the predicted value. Therefore, as illustrated in  FIG. 5 , a region centered on the predicted value calculated in S 30  and where it is estimated that the observed value will be detected from the same object as the predicted value is set as the first region. The first region setting unit  23  sets the first region by presuming, for example, that the object is a vehicle in front that is traveling in the same direction as the vehicle  80 . In this embodiment, a rectangular region centered on the predicted value is set as the first region based on two elements of the state quantity. A region based on three or more elements of the state quantity may also be set as the first region. 
     Next, in S 50  the selection unit  24  executes a correlation process. The selection unit  24 , from among the observed values detected in S 10 , selects an observed value to be correlated with the predicted value calculated in S 30 . More specifically, the selection unit  24  selects an observed value within the first region set in S 40  and that is the closest observed value to the predicted value calculated in S 30  as the observed value to be correlated with the predicted value. In the example illustrated in  FIG. 5 , an estimated value A 1  and an observed value A 2  are detected in the current processing cycle to be within the first region. Of the observed value corresponding to the estimated value A 1  and the observed value A 2 , the observed value corresponding to the estimated value A 1  is close to the predicted value, and therefore this observed value is selected to be the observed value that will be correlated with the predicted value. The observed value A 2  is not correlated with the predicted value. 
     Next, in S 60 , the estimation unit  25 , based on the predicted value calculated in S 30  and the observed value selected to be correlated in S 50 , and using a Kalman filter, calculates an estimated value in the current processing cycle. The estimated value for the state quantity of the target may have the electric power value P of the observation signal, the distance R to the target, the orientation θ of the target, and the velocity Vr of the target as elements, or may have the electric power P of the observation signal, the X-axis coordinate value Cx, the Y-axis coordinate value Cy, the velocity Vx in the X direction, and the velocity Vy in the Y direction as elements. The estimated value of the state quantity may have elements that are the same as those of the observed value or the predicted value, or may have elements that are different from those of the observed value and the predicted value. 
     Next, in S 70 , the prohibition region setting unit  27  sets a prohibition region. The prohibition region is a region of observed values for which registration of new targets is prohibited. In this example, the first region set in S 40  is taken to be a prohibition region. 
     Next. in S 80 , the registration prohibition unit  29  executes a registration prohibition determination process. More specifically, the registration prohibition unit  29  executes the subroutine illustrated in  FIG. 4 . First, in S 200 , the registration prohibition unit  29  determines whether there are any unprocessed observed values. More specifically, the registration prohibition unit  29  determines whether there are any observed values among the observed values detected in S 10  that are not correlated with the predicted value and for which the following process from S 210  to S 220  has not been executed. 
     Here, a high-resolution radar may detect a plurality of observed values from the same object. One observed value from among the plurality of observed values is correlated with the predicted value in S 340 , and the remaining observed values exist as unprocessed observed values. Moreover, in the current processing cycle, the observed value of the object that is detected first exists as an unprocessed observed value. 
     In S 200 , when it is determined that there are no unprocessed observed values, this subroutine ends and processing returns to S 20 . On the other hand, in S 200 , when it is determined that there is an unprocessed observed value, processing advances to S 210 . 
     In S 210 , the registration prohibition unit  29  determines whether one of the unprocessed observed values is an observed value that is within the prohibition region set in S 70 . In other words, the registration prohibition unit  29  determines whether an unprocessed observed value is an observed value of the plurality of observed values detected from the same object that is not correlated with the predicted value or is an observed value of an object that is detected for the first time. The prohibition region is a region for determining whether an observed value is an observed value detected from an object that is the same as the object corresponding to the predicted value. 
     In the example illustrated in  FIG. 5 , the observed value A 2  is determined to be an observed value that is within the prohibition region. In S 210 , when it is determined that an observed value is an observed value within the prohibition region, processing advances to S 220 . On the other hand, in S 210 , when it is determined that an observed value is an observed value that is outside the prohibition region, processing returns to S 200 , and this subroutine is executed for the next unprocessed observed value. 
     In S 220 , the registration prohibition unit  29  sets a prohibition flag for observed values that were determined in S 210  to be within the prohibition region. The prohibition flag is a flag for prohibiting the registration of an observed value as a new target. 
     For example, in addition to target T 1  that is currently being tracked and that was generated for object O 1 , it is presumed that targets T 2  and T 3  are generated from observed values B 1  and B 2  that were detected from object O 1 . In the next and subsequent processing cycles, when two observed values C 1  and C 2  are detected from the object O 1 , three targets T 1 , T 2  and T 3  will compete for the two observed values C 1  and C 2 . Then, when the predicted values for the targets T 2  and T 3  are correlated with the observed values C 1  and C 2 , tracking of the target T 1  ends, and tracking of targets T 2  and T 3  begins. Therefore, it becomes impossible to continue to track the target T 1 . In other words, in a case where a plurality of targets is generated from one object and a number of observed values less than the number of targets are detected in the subsequent processing cycles, it may become impossible to continuously track the targets. 
     Therefore, in order that a plurality of targets is not generated from the same target, prohibition flags are set for observed values among the plurality of observed values that are estimated as being detected from the same object and that are correlated with the predicted value. In the example illustrated in  FIG. 5 , a prohibition flag is set for the observed value A 2 . 
     However, the registration prohibition unit  29  does not set prohibition flags for observed values of the observed values determined in S 210  to be observed values within the prohibition region and whose distance to the target is equal to or less than a preset distance threshold value. The registration prohibition unit  29  stops prohibiting the registration of observed values detected from an object at a relatively close distance from the vehicle  80  as new targets. In other words, at distances relatively close to the vehicle  80 , the registration prohibition unit  29  prioritizes the performance of generating targets over prohibiting the generation of a plurality of targets from one object. After that, processing returns to S 200 . 
     After the subroutine illustrated in  FIG. 4  is completed, processing returns to the process of S 20  in the object tracking process illustrated in  FIG. 3 . Then, as long as there is unprocessed target information, the process from S 20  to S 80  is repeatedly executed. On the other hand, when there is no longer any unprocessed target information, and it is determined in S 20  that there is no unprocessed target information, processing advances to S 90 . 
     In S 90 , the registration unit  30  determines whether there are any unused observed values among the observed values detected in S 10 . In other words, the registration unit  30  determines whether there are any observed values among the observed values detected in S 10  that are not correlated with a predicted value. In S 90 , when it is determined that there are no unused observed values, this process ends. On the other hand, in S 90 , when it is determined that there is an unprocessed observed value, processing advances to S 100 . 
     In S 100 , the registration unit  30  determines whether one of the unused observed values is an observed value for which registration is not prohibited. More specifically, when a prohibition flag is set for an observed value, it is determined that registration of that observed value is prohibited, and when a prohibition flag is not set for an observed value, it is determined that registration of that observed value is not prohibited. 
     In S 100 , when it is determined that registration of the observed value is prohibited, processing returns to S 90 , and when it is determined that registration of the observed value is not prohibited, processing advances to S 110 . 
     In S 110 , the registration unit  30  registers the observed value for which registration is not prohibited as a new target. After that, processing returns to S 90 , and as long as there are unused observed values the have not undergone the process from S 90  to S 110 , the process from S 90  to S 110  is repeatedly executed. This process is then completed. 
     &lt;1-3. Effects&gt; 
     With the first embodiment described above, the following effects are obtained. 
     (1) For each target, a predicted value for the current state quantity is calculated based on an estimated value of the past state quantity, and for each calculated predicted value, a first region is set based on the predicted value. Then, of acquired observed values, an observed value is selected from among the observed values within the first region to be correlated with the predicted value, and based on the selected observed value and predicted value, an estimated value is calculated for the current state quantity. Furthermore, a prohibition region is set for each predicted value, and of the acquired observed values, an observed value that is not correlated with any of the predicted values and that is outside the prohibition region is registered as a new target. On the other hand, even in the case of an observed value that is not correlated with any predicted value, there is a high probability that an observed value that is within the prohibition region was observed from the same object as an observed value that is correlated with a predicted value. Accordingly, an observed value that is within the prohibition region is prohibited from being registered as a new target. Therefore, it is possible to prohibit the generation of a plurality of targets from the same object. As a result, it is possible to stably track a target. 
     (2) There is a high probability that observed values that are within the first region, which is a region of observed values correlated with a predicted value, that are not correlated with a predicted value are observed values that were observed from the same object as an observed value that is correlated with a predicted value. Therefore, by setting the first region as a prohibition region, it is possible to properly prohibit the generation of a plurality of targets from the same object. 
     (3) It is possible to set a region of observed values to be correlated with a predicted value, and to set a region of observed values to be prohibited from being registered as new targets based on physical quantities that are observable by a radar device  10 . 
     (4) An observed value that is at a short distance less than a distance threshold value from the vehicle  80  is not prohibited from being registered as a new target even though the observed value is within a prohibition region. As a result, at short distances, target performance is prioritized over prohibiting the generation of a plurality of targets from the same object. 
     Second Embodiment 
     &lt;2-1. Differences from the First Embodiment&gt; 
     The basic configuration of a second embodiment is similar to that of the first embodiment, and thus a description of configuration that is similar between the two will be omitted, and the description will be centered on the differences. Note that reference signs that are the same as those in the first embodiment indicate identical configuration and reference the preceding description. 
     As indicated by the dashed lines in  FIG. 2 , the object tracking device  20  according to the second embodiment differs from the object tracking device  20  according to the first embodiment in that in addition to the function of the object tracking device  20  according to the first embodiment, functions of a determination unit  26 , a noise region setting unit  28 , and a shape estimation unit  31  are further achieved. The determination unit  26 , the noise region setting unit  28  and the shape estimation unit  31  will be described in detail later. 
     &lt;2-2. Processing&gt; 
     Next, the object tracking process that is executed by the object tracking device  20  according to the second embodiment will be described with reference to the flowchart in  FIG. 6 . The object tracking device  20  repeatedly executes this process at a specified cycle. 
     First, in S 300  to S 350 , the object tracking device  20  executes the same processing as in S 10  to S 60 . 
     Next, in S 360 , the determination unit  26  determines the type of object corresponding to the target. More specifically, the determination unit  26  determines the type of object using any one of an observed value, an estimated value, and a predicted value of the velocity Vr, the distance R, and the orientation θ of the target. Instead of the velocity Vr, the distance R, and the orientation θ, it is also possible to use the X-axis coordinate value Cx, the Y-axis coordinate value Cy, the velocity Vx in the X direction, and the velocity Vy in the Y direction. Types of objects include pedestrians, bicycles crossing in front of the vehicle  80 , and automobiles crossing in front of the vehicle  80 . 
     Next, in S 370 , the prohibition region setting unit  27  sets a prohibition region according to the type of object determined in S 360 . More specifically, the prohibition region setting unit  27  executes the subroutine illustrated in  FIG. 7 . 
     First, in S 500 , the prohibition region setting unit  27  determines whether the type of object is a pedestrian. In S 500 , when it is determined that the type of object is a pedestrian, processing advances to the process of SS 10 . 
     In SS 10 , as illustrated in  FIG. 8  and  FIG. 9 , the prohibition region setting unit  27  sets a second region that is larger than the first region as a prohibition region. A pedestrian swings his/her arms and legs, and thus the spread of the velocity Vr, or the velocity Vx in the X direction and the velocity Vy in the Y direction is greater than that of a vehicle in front. Therefore, the second region is a region in which the spread of the region of velocity Vr, or the region of velocity Vx in the X direction and velocity Vy in the Y direction is larger than in the first region. After the process of SS 10 , this subroutine ends and processing advances to S 380 . 
     Moreover, in S 500 , when it is determined that the type of object is not a pedestrian, processing advances to S 520 . In S 520 , the prohibition region setting unit  27  determines whether the type of object is a crossing bicycle. In S 520 , when it is determined that the type of object is a crossing bicycle, processing advances to S 530 . 
     In S 530 , as illustrated in  FIG. 8  and  FIG. 9 , the prohibition region setting unit  27  sets a third region that is larger than the first region as a prohibition region. A crossing bicycle has a length in the width direction of the vehicle  80  that is longer than that of a vehicle in front, and thus the spread of the orientation θ, or the spread of the X-axis coordinate value Cx is larger than that of a vehicle in front. Therefore, the third region is a region in which the spread of the region of orientation θ, or the region of the X-axis coordinate value Cx is larger than that in the first region. After the process of S 530 , this subroutine ends and processing advances to S 380 . 
     Moreover, in S 520 , when it is determined that the type of object is not a crossing bicycle, processing advances to S 540 . In S 540 , the prohibition region setting unit  27  determines whether the type of object is a crossing automobile. In S 540 , when it is determined that the type of object is a crossing automobile, processing advances to S 550 . 
     In S 550 , as illustrated in  FIG. 8  and  FIG. 9 , the prohibition region setting unit  27  sets a fourth region that is larger than the third region as a prohibition region. An automobile crossing in front has a length in the width direction of the vehicle  80  that is longer than that of a crossing bicycle, and thus the spread of the orientation θ, or the spread of the X-axis coordinate value Cx is larger than that of a crossing bicycle. Therefore, the fourth region is a region in which the spread of the region of orientation θ, or the region of the X-axis coordinate value Cx is larger than that in the third region. After the process of S 550 , this subroutine ends and processing advances to S 380 . On the other hand, in S 540 , when it is determined that the type of the object is not a crossing automobile, the first region is set as the prohibition region, then this subroutine ends, and processing advances to S 380 . 
     Next, in S 380 , the noise region setting unit  28  sets a noise region for predicted values calculated in S 320 . A noise region is a region for prohibiting the registration of a noise peak as a new target. As illustrated in  FIG. 10  and  FIG. 11 , a noise region is a region larger than a prohibition region set in S 370 . Of the observed values outside of the prohibition region and within the noise region, a prohibition flag is set for an observed value for which the electric power difference between the electric power value P included in the observed value and the electric power value P included in the predicted value is greater than or equal to a preset electric power threshold value. As a result, a noise peak that is detected near the object is prohibited from being registered as a new target. 
     Next, in S 390 , the same process as in S 80  is executed. 
     Next, in S 400 , the shape estimation unit  31  estimates the shape of the object indicated by the predicted value calculated in S 320 . More specifically, as illustrated in  FIG. 12 , before the current processing cycle, the shape estimation unit  31  estimates the shape of the object by using observed values that are prohibited from being registered as a new target. In other words, of the observed values that are within the prohibition region set for the predicted value, information about observed values that are not correlated with the predicted value is stored in memory in the subsequent processing cycles. Then, in subsequent processing cycles, the shape estimation unit  31  estimates the shape of the object based on the positions of all of the stored observed values that are correlated with the predicted value. 
     In the example illustrated in  FIG. 12 , estimated value A 10  detected in the current processing cycle, and observed values A 11  to A 14  that have been prohibited from being registered as new targets in the previous processing cycle are within the prohibition region set in S 370 . In this case, the shape estimation unit  31  estimates the shape of the object based on the positions of the stored observed values A 11  to A 14 . Observed values that have been prohibited from being registered as new targets in the current processing cycle may also be included in the observed values A 11  to A 14 . The information of observed values A 11  to A 14  is also stored for the next subsequent processing cycles. 
     Next, in S 410  to S 430 , the same processing as in S 90  to S 110  is executed. This process is then completed. 
     &lt;2-3. Effects&gt; 
     With the second embodiment described above, the following effects are obtained together with the effects (1) to (4) of the first embodiment described above. 
     (5) The type of object corresponding to the target is determined, and a prohibition region is set according to the type of object. Therefore, it is possible to set a proper prohibition region according to the type of object. 
     (6) A pedestrian swings his/her arms and legs, and thus the spread of the velocity Vr, or the velocity Vx in the X direction and the velocity Vy in the Y direction is greater than that of a vehicle in front. Therefore, when it is determined that the type of object is a pedestrian, the region of velocity Vr of the prohibition region, or the region of the velocity Vx in the X direction and the velocity Vy in the Y direction is larger than in the first region. As a result, when the type of object is a pedestrian, it is possible to properly prohibit a plurality of targets from being generated from the same object. 
     (7) A crossing bicycle has a length in the width direction of the vehicle  80  that is larger than a vehicle in front, and thus when it is determined that the type of object is a crossing bicycle, the region in the width direction or the region of the orientation θ of the vehicle  80  in the prohibition region is larger. As a result, when the type of object is a crossing bicycle, it is possible to properly prohibit a plurality of targets from being generated from the same object. 
     (8) A crossing automobile has a length in the width direction of the vehicle  80  that is even longer than that of a crossing bicycle, and thus when it is determined that the type of object is a crossing automobile, the region in the width direction or the region of the orientation θ of the vehicle  80  in the prohibition region is even larger. As a result, when the type of object is a crossing automobile, it is possible to properly prohibit a plurality of targets from being generated from the same object. 
     (9) Of the observed values outside of the prohibition region and within the noise region, an observed value for which the electric power difference between the electric power value P included in the observed value and the electric power value P included in the predicted value is greater than or equal to a preset electric power threshold value is prohibited from being registered as a new target. Therefore, even observed values that are outside of the prohibition region can be prohibited from being registered as a new target when the noise peak is near the object. 
     (10) For the same predicted value, observed values that have been prohibited from being registered as new targets are observed from different positions of the same object as an observed value that is correlated with the predicted value. Therefore, it is possible to detect positions of a plurality of positions within the same object and estimate the shape of the object by storing a plurality of observed values that have been prohibited from being registered as new targets, and using the plurality of stored observed values. In other words, it is possible to effectively use observed values that have been prohibited from being registered as new targets. 
     OTHER EMBODIMENTS 
     Forms for implementing the present disclosure have been described above; however, the present disclosure is not limited to the embodiments described above, and may undergo various modifications. 
     (a) In the embodiments described above, the first region and prohibition region are set as rectangular regions; however, the shape of the regions are not limited to being rectangular. For example, the first region and the prohibition region may be set to be a shape such as region R 1  illustrated in  FIG. 13 , or may be set to be a shape such as region R 2  illustrated in  FIG. 14 . 
     (b) The object tracking device  20  and methods described in the present disclosure may be achieved by a dedicated computer that is provided by configuring a processor and memory programmed to execute one or a plurality of functions embodied by a computer program. Alternatively, the object tracking device  20  and methods described in the present disclosure may be achieved by a dedicated computer that is provided by configuring a processor using one or more dedicated hardware logic circuits. Moreover, the object tracking device  20  and methods described in the present disclosure may be achieved by one or more dedicated computers configured by a combination of processors and memory that execute one or a plurality of functions, and one or more hardware logic circuits. Furthermore, the computer program may be stored in a computer-readable, non-transitory tangible storage medium as instructions to be executed by a computer. The methods for achieving the functions of each part included in the object tracking device  20  does not necessarily need to include software, and all of the functions may be realized using one or a plurality of kinds of hardware. 
     (c) A plurality of functions of one component in the above embodiment may be realized by a plurality of components, or a single function of one component may be achieved by a plurality of components. Moreover, a plurality functions of a plurality of components may be achieved by a single component, or a single function achieved by a plurality of components may be achieved by a single component. It is also possible to omit part of the configuration of the embodiments described above. Furthermore, at least part of the configuration of the embodiments described above can be added to or substituted for other embodiments described above. 
     (c) In addition to the object tracking device  20  described above, the present disclosure can be achieved in various forms, such as a system including the object tracking device  20 , a program for making a computer function as the object tracking device  20 , a non-transitory tangible storage medium such as semiconductor memory on which the program is recorded, and an object tracking method.