Patent Publication Number: US-11656350-B2

Title: Radar proximity detection with flexible FOV

Description:
RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Application No. 62/858,597, filed Jun. 7, 2019, entitled “RADAR PROXIMITY DETECTION WITH FLEXIBLE FOV,” and claims the benefit of U.S. Provisional Application No. 62/932,176, filed Nov. 7, 2019, entitled “RADAR PROXIMITY DETECTION WITH FLEXIBLE FOV,” both of which are assigned to the assignee hereof, and incorporated by reference herein in their entirety. 
    
    
     BACKGROUND 
     Proximity sensing involves detecting objects at small distances from an electronic device. Radar-based proximity detection can use radio frequency (RF) signals to perform the proximity sensing. Although radar-based proximity detection can offer advantages over proximity sensing using other technologies, it is not without drawbacks. Traditional implementations of radar-based proximity detection can use a relatively large amount of power, which may be beyond the power budget of certain applications. 
     SUMMARY 
     Power-saving techniques for radar-based proximity sensing can include conducting proximity scans with a radar system in an omnidirectional proximity-sensing mode in which signals are transmitted without directionality. Once an object is detected within a threshold proximity, the radar system can then switch to a directional proximity-sensing mode to provide accurate directional detection capabilities in a desired field of view (FOV). 
     An example method of operating a radar system to perform radar proximity detection, according to this disclosure, comprises, in an omnidirectional proximity sensing mode: transmitting, with a transmitter of the radar system, a first set of radio frequency (RF) pulses, the first set of RF pulses comprising one or more pulses, receiving, with a receiver of the radar system, at least one first reflected pulse, determining, with a processing unit, an object&#39;s presence within a threshold distance of the radar system, based on the receiving the at least one first reflected pulse, and in response to determining the object&#39;s presence, operating in a directional proximity sensing mode. The method further comprises, in the directional proximity sensing mode: transmitting, with a transmitter antenna array of the transmitter, a second set of RF pulses, the second set of RF pulses comprising a plurality of pulses, receiving, with a receiver antenna array of the receiver, at least one second reflected pulse, the at least one second reflected pulse comprising at least one RF pulse from the second set of RF pulses reflected off of the object, and determining, based on the transmitting of the second set of RF pulses and the receiving of the at least one second reflected pulse a proximity of the object, and whether the object is within a predetermined field of view (FOV). 
     An example device for performing radar proximity detection, according to this disclosure, comprises a memory and one or more processing units communicatively coupled with the memory and configured to, in an omnidirectional proximity sensing mode: transmit, with a transmitter of a radar system, a first set of radio frequency (RF) pulses, the first set of RF pulses comprising one or more pulses, receive, with a receiver of the radar system, at least one first reflected pulse, determine an object&#39;s presence within a threshold distance of the radar system, based on the receiving the at least one first reflected pulse, and in response to determining the object&#39;s presence, operate in a directional proximity sensing mode. The one or more processing units are further configured to, in the directional proximity sensing mode, transmit, with a transmitter antenna array of the transmitter, a second set of RF pulses, the second set of RF pulses comprising a plurality of pulses, receive, with a receiver antenna array of the receiver, at least one second reflected pulse, the at least one second reflected pulse comprising at least one RF pulse from the second set of RF pulses reflected off of the object, and determine, based on the transmitting of the second set of RF pulses and the receiving of the at least one second reflected pulse a proximity of the object, and whether the object is within a predetermined field of view (FOV). 
     Another example device, according to this disclosure, comprises means for transmitting, in an omnidirectional proximity sensing mode, a first set of radio frequency (RF) pulses, the first set of RF pulses comprising one or more pulses, means for receiving, in the omnidirectional proximity sensing mode, at least one first reflected pulse, means for determining, in the omnidirectional proximity sensing mode, an object&#39;s presence within a threshold distance of the device, based on the receiving the at least one first reflected pulse, means for operating in a directional proximity sensing mode in response to determining the object&#39;s presence, and means for transmitting, in the directional proximity sensing mode, a second set of RF pulses, the second set of RF pulses comprising a plurality of pulses. The device further comprises means for receiving, in the directional proximity sensing mode, at least one second reflected pulse, the at least one second reflected pulse comprising at least one RF pulse from the second set of RF pulses reflected off of the object, and means for determining, based on the transmitting of the second set of RF pulses and the receiving of the at least one second reflected pulse a proximity of the object, and whether the object is within a predetermined field of view (FOV). 
     An example non-transitory computer-readable medium, according to this disclosure, comprises instructions embedded therewith for operating a radar system to perform radar proximity detection. The instructions, when executed by one or more processing units, cause the one or more processing units to, in an omnidirectional proximity sensing mode: transmit, with a transmitter of the radar system, a first set of radio frequency (RF) pulses, the first set of RF pulses comprising one or more pulses, receive, with a receiver of the radar system, at least one first reflected pulse, determine an object&#39;s presence within a threshold distance of the radar system, based on the receiving the at least one first reflected pulse, and in response to determining the object&#39;s presence, operate in a directional proximity sensing mode. The instructions, when executed by one or more processing units, further cause the one or more processing units to, in the directional proximity sensing mode: transmit, with a transmitter antenna array of the transmitter, a second set of RF pulses, the second set of RF pulses comprising a plurality of pulses, receive, with a receiver antenna array of the receiver, at least one second reflected pulse, the at least one second reflected pulse comprising at least one RF pulse from the second set of RF pulses reflected off of the object, and determine, based on the transmitting of the second set of RF pulses and the receiving of the at least one second reflected pulse a proximity of the object, and whether the object is within a predetermined field of view (FOV). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of a radar system performing radar-based directional proximity sensing, according to an embodiment. 
         FIG.  2    is an illustration of how radar proximity detection may be used by a radar system, according to an embodiment. 
         FIG.  3    is a graph showing an elevation-azimuth response of radar scanning performed by the radar system in the scenario shown in  FIG.  2   . 
         FIGS.  4  and  5    are example graphs plotting in omnidirectional channel impulse response (CIR) across various taps, after leakage cancellation. 
         FIG.  6 A  is a graph showing the elevation-azimuth response of directional proximity sensing in an example in which the directional proximity sensing senses an object. 
         FIG.  6 B  is a graph related to the elevation-azimuth response of  FIG.  6 A . 
         FIGS.  7 - 10    are illustrations of the geometry of an ellipse, which can be used to more accurately determine object distance, according to some embodiments. 
         FIG.  11    is a flow diagram of a method of operating a radar system to perform radar proximity detection, according to an embodiment. 
         FIG.  12    is a block diagram of an embodiment of an electronic device. 
     
    
    
     Like reference symbols in the various drawings indicate like elements, in accordance with certain example implementations. In addition, multiple instances of an element may be indicated by following a first number for the element with a letter or a hyphen and a second number. For example, multiple instances of an element  110  may be indicated as  110 - 1 ,  110 - 2 ,  110 - 3 , etc. or as  110   a ,  110   b ,  110   c , etc. When referring to such an element using only the first number, any instance of the element is to be understood (e.g., element  110  in the previous example would refer to elements  110 - 1 ,  110 - 2 , and  110 - 3  or to elements  110   a ,  110   b , and  110   c ). 
     DETAILED DESCRIPTION 
     Several illustrative embodiments will now be described with respect to the accompanying drawings, which form a part hereof. The ensuing description provides embodiment(s) only and is not intended to limit the scope, applicability or configuration of the disclosure. Rather, the ensuing description of the embodiment(s) will provide those skilled in the art with an enabling description for implementing an embodiment. It is understood that alternative embodiments may include various changes may be made in the function and arrangement of elements. 
     As noted, radar sensors can be used in modern electronic devices for multiple applications, including proximity detection. The utilization of radar sensing in this manner can be useful for a variety of reasons. Of particular relevance is the fact that modems used for wireless communication in modern mobile devices (e.g., mobile phones, tablets) are capable of performing radar sensing, in addition to providing data communication functionality. As such, embodiments employing radar sensing for proximity determination may not need a separate proximity sensor for proximity determinations. Additionally, radar has an ability to implement a flexible FOV (e.g., a flexible range of azimuth, elevation, distance, velocity (Doppler), and signal-to-noise ratio (SNR)) for which the radar will detect proximity objects (also referred to herein as “proximity targets”). The flexible/parametric FOV can be obtained using beamforming (BF) and Digital Signal Processing (DSP) techniques (e.g., digital BF, analog BF, or hybrid BF). Thus, unlike other proximity detection technologies, radar has the capability of determining directionality of an object, in addition to distance. 
     Although embodiments described herein are described in the context of proximity applications, embodiments are not so limited. Embodiments may be used for other object-sensing applications (e.g., the sensing of location, distance, velocity, etc. of objects). A person of ordinary skill in the art will appreciate other such applications. 
       FIG.  1    is a block diagram of a radar system  105  performing radar-based directional proximity sensing, according to an embodiment. As used herein, the terms “waveform” and “sequence” and derivatives thereof are used interchangeably to refer to RF signals generated by a transmitter of the radar system and received by a receiver of the radar system for object detection. A “pulse” and derivatives thereof are generally referred to herein as waveforms comprising a sequence or complementary pair of sequences transmitted and received to generate a CIR. The radar system  105  may comprise a standalone device or may be integrated into a larger electronic device, such as a mobile phone or other device. (Example components of such an electronic device are illustrated in  FIG.  12    and discussed in detail hereafter.) 
     With regard to the functionality of the radar system  105  in  FIG.  1   , the radar system  105  can detect the proximity of an object  110  by generating a series of transmitted RF signals  112  (comprising one or more pulses). Some of these transmitted RF signals  112  reflect off of the object  110 , and these reflected RF signals  114  are then processed by the radar system  105  using BF and DSP techniques (including leakage cancellation) to determine the object&#39;s location (azimuth, elevation, velocity, and range) relative to the radar system  105 . Because embodiments may implement a flexible FOV, the radar system  105  can detect an object  110  within a select volume of space. This volume of space can be defined by a range of azimuths, elevations, and distances from the radar system  105 . (As described below, this volume of space may also be defined by an FOV (a range of azimuths and elevations) and a range of distances within the FOV or from an area of interest corresponding to the FOV.) 
     To enable radar proximity detecting radar system  105  includes a processing unit  115 , memory  117 , multiplexer (mux)  120 , Tx processing circuitry  125 , and Rx processing circuitry  130 . (The radar system  105  may include additional components not illustrated, such as a power source, user interface, or electronic interface) It can be noted, however, that these components of the radar system  105  may be rearranged or otherwise altered in alternative embodiments, depending on desired functionality. Moreover, as used herein, the terms “transmit circuitry” or “Tx circuitry” refer to any circuitry utilized to create and/or transmit the transmitted RF signal  112 . Likewise, the terms “receive circuitry” or “Rx circuitry” refer to any circuitry utilized to detect and/or process the reflected RF signal  114 . As such, “transmit circuitry” and “receive circuitry” may not only comprise the Tx processing circuitry  125  and Rx processing circuitry  130  respectively, but may also comprise the mux  120  and processing unit  115 . In some embodiments, the processing unit may compose at least part of a modem and/or wireless communications interface. In some embodiments, more than one processing unit may be used to perform the functions of the processing unit  115  described herein. 
     The Tx processing circuitry  125  and Rx circuitry  130  may comprise subcomponents for respectively generating and detecting RF signals. As a person of ordinary skill in the art will appreciate, the Tx processing circuitry  125  may therefore include a pulse generator, digital-to-analog converter (DAC), a mixer (for up-mixing the signal to the transmit frequency), one or more amplifiers (for powering the transmission via Tx antenna array  135 ), etc. The Rx processing circuitry  130  may have similar hardware for processing a detected RF signal. In particular, the Rx processing circuitry  130  may comprise an amplifier (for amplifying a signal received via Rx antenna  140 ), a mixer for down-converting the received signal from the transmit frequency, an analog-to-digital converter (ADC) for digitizing the received signal, and a pulse correlator providing a matched filter for the pulse generated by the Tx processing circuitry  125 . The Rx processing circuitry  130  may therefore use the correlator output as the CIR, which can be processed by the processing unit  115  (or other circuitry) for leakage cancellation as described herein. Other processing of the CIR may also be performed, such as object detecting, range, speed, or direction of arrival (DoA) estimation. 
     BF is further enabled by a Tx antenna array  135  and Rx antenna array  140 . Each antenna array  135 ,  140  comprises a plurality of antenna elements. It can be noted that, although the antenna arrays  135 ,  140  of  FIG.  1    include two-dimensional arrays, embodiments are not so limited. Arrays may simply include a plurality of antenna elements along a single dimension that provides for spatial cancellation between the Tx and Rx sides of the radar system  105 . As a person of ordinary skill in the art will appreciate, the relative location of the Tx and Rx sides, in addition to various environmental factors can impact how spatial cancellation may be performed. 
     It can be noted that the properties of the transmitted RF signal  112  may vary, depending on the technologies utilized. Techniques provided herein can apply generally to “mmWave” technologies, which typically operate at 57-71 GHz, but may include frequencies ranging from 30-300 GHz. This includes, for example, frequencies utilized by the 802.11ad Wi-Fi standard (operating at 60 GHz). That said, some embodiments may utilize radar with frequencies outside this range. For example, in some embodiments, 5G frequency bands (e.g., 28 GHz) may be used. Because radar may be performed in the same busy bands as communication, hardware may be utilized for both communication and radar sensing, as previously noted. For example, one or more of the components of the radar system  105  shown in  FIG.  1    may be included in a wireless modem (e.g., Wi-Fi or 5G modem). Additionally, techniques may apply to RF signals comprising any of a variety of pulse types, including compressed pulses (e.g., comprising Chirp, Golay, Barker, or Ipatov sequences) may be utilized. That said, embodiments are not limited to such frequencies and/or pulse types. Additionally, because the radar system may be capable of sending RF signals for communication (e.g., using 802.11 communication technology), embodiments may leverage channel estimation used in communication for performing proximity detection as provided herein. Accordingly, the pulses may be the same as those used for channel estimation in communication. 
     As noted, the radar system  105  may be integrated into an electronic device in which proximity detecting is desired. For example, the radar system  105 , which can perform radar-based proximity detecting, may be part of communication hardware found in modern mobile phones. Other devices, too, may utilize the techniques provided herein. These can include, for example, other mobile devices (e.g., tablets, portable media players, laptops, wearable devices, virtual reality (VR) devices, augmented reality (AR) devices), as well as other electronic devices (e.g., security devices, on-vehicle systems). That said, electronic devices into which a radar system  105  may be integrated are not limited to mobile devices. Furthermore, radar-based proximity sensing as described herein may be performed by a radar system  105  that may not be otherwise used in wireless communication. 
     Although capable of providing a high degree of accuracy, directional proximity sensing shown in  FIG.  1   , if performed frequently, can be problematic in certain applications. For example, to perform a scan for a nearby object  110  the radar system  105  may transmit a large number of transmitted RF signals  112  such that each antenna element in the Rx antenna array  140  receives a reflected RF signal  114  corresponding to a transmitted RF signal  112  transmitted from each antenna element in the Tx antenna array  135 . Moreover, the radar system  105  may perform a scan very frequently (e.g., several times per second). And thus, the directional proximity sensing performed by the radar system  105  may consume a large amount of power. This may be problematic for low-power applications. 
     According to embodiments described herein, radar-based directional proximity sensing power-saving techniques can be implemented to help reduce the power consumption used in directional radar sensing. In particular, according to some embodiments, a radar system can first operate in a low-power, omnidirectional proximity sensing mode in which signals are transmitted having no directionality. Once an object is detected, the radar system can then operate in a higher-power directional proximity sensing mode to provide accurate directional detection capabilities in the desired FOV. 
       FIG.  2    is an illustration of how radar proximity detection may be used by an electronic device  205 , according to an embodiment. In this example, the electronic device  205  comprises a mobile phone having a radar system  105  with a Tx antenna array  135  and Rx antenna array  140  (not shown) embedded within the body of the electronic device  205 . The locations of the Tx antenna array and Rx antenna array are shown in  FIG.  2    by Tx antenna array location  220  and Rx antenna array location  230 , respectively. An area of interest  240  (corresponding to an FOV of the radar system of the radar system  105 ) is defined such that, if an object  110  (a finger) comes within a certain threshold distance of the area of interest  240 , the radar system  105  of the electronic device  205  indicates that an object has been detected. Before using directional proximity sensing, however, the radar system  105  can first perform radar scans in an omnidirectional proximity sensing mode to detect whether a nearby object  110  is within a threshold distance. If an object  110  is detected, the radar system  105  can then enter a directional proximity sensing mode to determine whether the object  110  is within a threshold distance of the area of interest  240 . 
       FIG.  3    is a graph showing an elevation-azimuth response  300  of radar scanning performed by the radar system  105  of the electronic device  205  in the scenario shown in  FIG.  2   . Here, because the object  110  in  FIG.  2    is within a threshold distance of electronic device  205 , the object is detected while the radar system  105  is performing radar scans in an omnidirectional proximity sensing mode. After switching to directional proximity sensing, the radar system  105  then performs radar scanning using BF and DSP to obtain the elevation-azimuth response  300 . In the elevation-azimuth response  300  illustrated in  FIG.  3   , each azimuth/elevation combination is represented as a “pixel” in the graph, where darker pixels represent reflections (higher detected maximum SNR). 
     In this example, the omnidirectional scanning is capable of detecting an object  110  within an omnidirectional detection range  310  across various elevations (ranging from −90° to 90°) and azimuths (ranging from −100° to 100°). The use of a backplane or other physical barrier can help exclude the detection of objects in certain areas (e.g., behind the electronic device  205 ) in which object detection in the omnidirectional proximity sensing mode is not desired. And thus, the omnidirectional detection range  310  may be different in different applications. 
     The elevation-azimuth response  300  obtained after directional proximity sensing is performed reveals that the object reflections  320  (corresponding to object  110  in  FIG.  2   ) fall outside a directional mode FOV  330  (which, as noted, corresponds to the area of interest  240  of the radar system  105  in  FIG.  2   ). As such, the radar system  105  can conclude that the object  110  is not located within a threshold proximity of the area of interest  240 . It can be noted that the object reflections  320  are provided in  FIG.  3    to illustrate where the object reflections  320  may be located with respect to the directional mode FOV  330 . In some embodiments, the elevation-azimuth response may be limited to the directional mode FOV  330 . That said, as noted below, information outside the directional mode FOV  330  may be used to help increase the accuracy of object detection (e.g., reducing false positives) in directional proximity sensing mode. 
     Because the directional mode FOV  330  is configurable, the radar system  105  can define an area of interest  240  suited to a particular application. Furthermore, when an object is detected to be within a threshold distance of the area of interest  240 , the radar system  105  can respond in any of a variety of ways, depending on desired functionality. In some embodiments, the physical layer performing the radar scanning can provide a notification of the proximity detection to a higher layer (e.g., software layer, such as the operating system), which can respond appropriately. 
     In omnidirectional proximity sensing mode, BF is not used by the radar system. And thus, a scan may be performed by a single antenna element from each of the Tx antenna array  135  and the Rx antenna array  140  (although multiple elements from either or both arrays may be optionally used). A scan in the omnidirectional proximity sensing mode may comprise, for example, one or more pulses of RF signals sent periodically in a manner that helps facilitate low-power operation. In some embodiments, for example, a four-pulse burst of signals is transmitted every 50 ms (e.g., repeated at 20 Hz). Other embodiments may use a larger or smaller amount of pulses and/or a different periodicity, depending on the desired balance between performance and power savings. (The fewer pulses used, the more power savings the radar system may have. However, decreasing the number of pulses may also decrease the SNR, which may result in false positives. 
       FIG.  4    is an example graph plotting in omnidirectional CIR  410  across various taps, after leakage cancellation. The omnidirectional CIR  410  (e.g., the mean CIR for multiple reflected signals) is plotted over a tap index, which is indicative of when reflected RF signals are sampled. As a person of ordinary skill in the art will appreciate, the initial point of the tap index may be chosen arbitrarily. (This point can be accounted for when determining a distance of a detected object from the electronic device  110 .) 
     To ignore objects beyond a threshold distance, the omnidirectional CIR may take a limited number of taps. The threshold distance can be established, based on desired functionality. In some embodiments, for example, taps above 10 cm may be ignored. Other embodiments may set a higher or lower threshold distance, depending on desired functionality. As discussed in more detail below, because the distance between taps may be large relative to a range for which proximity detection is desired interpolation techniques may be used to help determine the distance of an object with more precision. In some embodiments, for example, the distance between taps may exceed 4 cm. Although this resolution may be sufficient for certain applications, interpolation techniques can be used to increase the resolution to less than 1 cm. 
     The detection of an object in omnidirectional proximity sensing mode may be based on both amplitude (SNR) and fine range. Thus, omnidirectional proximity sensing may depend on determining whether, for taps corresponding to a range of interest (7 cm to 15 cm, as an example), SNR exceeds an omnidirectional detection threshold  420 . Depending on desired functionality, this threshold may be set at a value that sufficiently cancels out noise while also reliably detecting objects. In this example, because a maximum value of the omnidirectional CIR  410  (for the taps of interest) does not exceed the omnidirectional detection threshold  420 , no object is detected from the omnidirectional scan, and the electronic device  110  can continue scanning in the omnidirectional proximity sensing mode. 
       FIG.  5    is a graph, similar to the graph in  FIG.  4   , in which an omnidirectional CIR  510  is plotted across various taps. This may comprise an omnidirectional scan performed by the same electronic device  110 , with the same omnidirectional detection threshold  420 . Here, however, the maximum value  520  of the omnidirectional CIR  510  exceeds the omnidirectional detection threshold  420 . And thus, an object is detected, and the electronic device can perform directional proximity sensing to determine a more accurate location of the detected object. 
     As illustrated in  FIG.  3   , directional proximity sensing can provide an elevation-azimuth response that allows for determination of whether an object is within a desired range of a desired FOV. Just as the FOV can be adjusted depending on desired functionality, so too can the desired range. For example, in some applications, a desired range may comprise a maximum (e.g., proximity sensing for an object less than 10 cm away). Other applications may include a desired minimum and maximum (e.g., proximity sensing foreign object between 7 cm and 15 cm away). 
     Depending on desired functionality, directional proximity sensing can be performed over a predetermined period of time (e.g., for a predetermined window of time after the omnidirectional proximity sensing has detected an object). Additionally or alternatively, embodiments may perform directional proximity sensing contingent on whether an object is detected within a desired range and FOV. If so, the radar system  105  can continue conducting directional proximity sensing. Otherwise, if an object is not detected within the desired range and FOV (e.g., as shown in the elevation-azimuth response  300  in  FIG.  3   ), the radar system  105  can revert back to omnidirectional proximity sensing. 
       FIG.  6 A  is a graph showing the elevation-azimuth response  600  of the directional proximity sensing in an example in which the directional proximity sensing senses an object. Similar to the elevation-azimuth response  300  of  FIG.  3   , the elevation-azimuth response  600  of  FIG.  6 A  includes object reflections  610 . Here, however, the object reflections  610  fall within the directional proximity sensing mode FOV  620 . And thus, a final outcome of the proximity sensing is that an object has been detected within the desired range of a desired area of interest. 
       FIG.  6 B  is a graph  650  related to the elevation-azimuth response  600  of  FIG.  6 A . The graph  650  plots SNR and range measurements over time and shows additional related measurements and thresholds. In this example, a detected omnidirectional SNR maximum was 22 dB, which exceeded the 12 dB SNR threshold, and therefore directional proximity sensing was performed. (It can be noted directional threshold may differ from the omnidirectional threshold by the expected BF gain plus some margin for error.) At the azimuth and elevation at which directional SNR was determined to have a peak value within the directional mode FOV  620  (15° azimuth and 35° elevation), the directional SNR  660  is plotted, as is the range  670 . In this example, the final values at frame  29  for directional SNR  660  and range  670  are 27.2 dB and 7.4 cm, respectively. The 27.2 dB value for the directional SNR  660  exceeds the 15 dB threshold in this example, and the 7.4 cm range falls within the desired range of 7-15 cm. 
     As previously mentioned, measurements outside the directional mode FOV can be used to help increase the accuracy of object detection within the directional mode FOV. To help ensure that a side lobe of an object outside the directional mode FOV of the directional proximity sensing does not create a false detection of a proximity target within the directional mode FOV, various schemes may be employed to filter out such side lobes. Using a larger BF range (e.g., the entire range of the elevation-azimuth response  600  of  FIG.  6 A ) and percentile/max-to-mean power ratio, side lobes may be identified as such, and false positives can be reduced. For example, a ratio can be calculated from a maximum or mean amplitude within the directional mode FOV  620  in  FIG.  6 A  and a mean amplitude outside the directional mode FOV  620 . If the ratio exceeds a threshold, it may confirm that an object is detected within the directional mode FOV  620  (if other thresholds are met). A similar solution may be conducted using a histogram of the BF output. Additionally or alternatively, other adaptive knowing schemes may be utilized. 
     Depending on desired functionality, various techniques may be employed to help improve the accuracy of range and/or SNR measurements in omnidirectional proximity sensing mode, directional proximity sensing mode, or both. 
       FIG.  7    is an illustration of the geometry of an ellipse, which can be used to more accurately determine distance in omnidirectional and/or directional proximity sensing mode, according to some embodiments. Because proximity sensing can involve sensing objects at close distances, the distance between the detected object and a Tx antenna may be different than the distance between the object and an Rx antenna. The utilizing the geometry of an ellipse, embodiments may account for these differences. 
     In  FIG.  7   , the ellipse is defined as the a of points having the same sum of distances, |PF 1 |+|PF 2 |, relative to foci, F 1  and F 2 . Similarly, an ellipse may be determined from a time-of-flight measurement made in an omnidirectional proximity sensing mode to indicate a distance to a detected object. For example, a time-of-flight measurement between a Tx antenna array (e.g., Tx antenna array  135  of  FIG.  1   ) located at F 1  and an Rx antenna array (e.g., Rx antenna array  140 ) located at F 2 , in which the RF signal reflected off of an object at point P would result in a distance measurement of |PF 1 |+|PF 2 |. The ellipse can then be calculated, and a distance of the object from a center point, C, can be estimated based on the geometry of the ellipse. 
     For example, according to some embodiments in which a radar system  105  detects an object in an omnidirectional proximity sensing mode, the object can be assumed to be at azimuth and elevation zero, as shown in  FIG.  8   . If azimuth and elevation are assumed to be zero, the object may be assumed to be equidistant from the transmitting and receiving elements (i.e., |PF 1 |=|PF 2 |). The distance, m, between the object and the center point, C, can then be determined from the geometry of the ellipse. (It can be noted that in some embodiments, antenna elements may be offset from the coordinate system used to establish azimuth and elevation. In such embodiments, the determination of the ellipse and the distance can account for this offset.) After determining the distance, m, of the object, the radar system  105  can then switch to directional proximity sensing, as detailed in the previously-described embodiments. 
       FIG.  9    illustrates how the geometry of an ellipse can be leveraged to determine a more accurate position of a detected object in directional proximity sensing. Because directional proximity sensing can provide an angle, θ, to the object, an accurate determination for distance, m, can be calculated using the following equations for ellipse geometry: 
                       (     x   ,   y     )     =     m   ·     (       sin   ⁡   (   θ   )     ,     cos   ⁡   (   θ   )       )         ,           (   1   )                   and                           x   2       a   2       +       y   2       b   2         =         m   2     (           sin   2     (   θ   )       a   2       +         cos   2     (   θ   )       b   2         )     =   1       ,           (   2   )               
where, variables a and b are respectively the semi-major axis and semi-minor axis of the ellipse, as illustrated in  FIG.  9   .
 
     In some embodiments, this can be expanded to three dimensions to determine an accurate distance, m, of an object detected at a given azimuth, Az, and elevation, El, from center point, C. The 3D equations used to solve for m are: 
     
       
         
           
             
               
                 
                   
                     
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                                   cos 
                                   2 
                                 
                                 ( 
                                 Az 
                                 ) 
                               
                               ⁢ 
                               
                                 
                                   cos 
                                   2 
                                 
                                 ( 
                                 El 
                                 ) 
                               
                             
                             + 
                             
                               
                                 sin 
                                 2 
                               
                               ( 
                               El 
                               ) 
                             
                           
                           
                             b 
                             2 
                           
                         
                       
                       ) 
                     
                     = 
                     1. 
                   
                 
               
               
                 
                   ( 
                   4 
                   ) 
                 
               
             
           
         
       
     
     As previously noted, interpolation techniques (e.g., parabolic interpolation) can be used to determine an accurate distance of an object located at a distance between two taps in a radar scan (for either or both omnidirectional and directional proximity sensing). Additionally or alternatively, some embodiments may use an SNR-averaged range estimation to determine a robust range estimate without angular information. Put briefly, SNR-averaged range estimation can take an average SNR value of two taps to determine the location of an object located between the two taps. This can be written mathematically as follows: 
                       a   ^     =           ρ     n   ⁢   1       ⁢     a     n   ⁢   1         +       ρ     n   ⁢   2       ⁢     a     n   ⁢   2               ρ     n   ⁢   1       +     ρ     n   ⁢   2             ,           (   5   )               
where ρ n1  and a n1  are respective SNR and range estimates for a first tap n1, ρ n2  and a n2  are respective SNR and range estimates for a second tap n2, and â is the SNR-averaged range estimation.
 
     An additional measure that may be implemented to help ensure accuracy in directional proximity sensing mode, according to some embodiments, comprises using near-field BF that accounts for differences in the location of Tx and Rx antenna arrays in. As previously noted, proximity detection can occur at close distances, where the difference in location between a Tx antenna and Rx antenna may be impactful to a range measurement. More specifically, an angle between an Rx antenna array and a detected object may be different than the angle between the Tx antenna array and the object.  FIG.  10   , which illustrates an ellipse similar to  FIG.  7   , provides an example of how angles θ 1  and θ 2  between antenna arrays respectively located at positions F 1  and F 2  and the object located at point P can be different. Embodiments may therefore take this angle into account when beamforming. 
     For example, embodiments that do not account for differences in the location of Tx and Rx antenna arrays may utilize the following equation to calculate an elevation-azimuth response at a given tap by combining CIRs for different transmit and receive antennas: 
                       a   ⁡   (     Az   ,   El     )     =     [               a     n     TX   ,   1         (     Az   ,   El     )     ⁢       a     n     RX   ,   1         (     Az   ,   El     )                     a     n     TX   ,   2         (     Az   ,   El     )     ⁢       a     n     RX   ,   2         (     Az   ,   El     )               …                 a     n     TX   ,   N         (     Az   ,   El     )     ⁢       a     n     RX   ,   N         (     Az   ,   El     )             ]       ,           (   6   )               
where azimuth and elevation (Az, El) in the elevation-azimuth response is computed by multiplying a transmit vector a n     TX    (Az, El) with a receive vector a n     TX    (Az, El) across all Tx antenna elements (1 to N) and Rx antenna elements (1 to N). The transmit a vector a n     TX    (Az, El) and receive vector a n     TX    (Az, El) can be computed analytically using the antenna array structure, or may be measured empirically.
 
     In contrast, embodiments that account for differences in the location of Tx and Rx antenna arrays may take into account the range, azimuth, and elevation (r Tx , Az Tx , El Tx ) of Tx antenna arrays relative to range, azimuth, and elevation (r Rx , Az Rx , El Rx ) of Rx antenna arrays as follows: 
                         a   ⁡   (     Az   ,   El     )     ≅     a   ⁡   (       r   TX     ,     Az   TX     ,     El   TX       )       =     [               a     n     TX   ,   1         (       r   TX     ,     Az   TX     ,     El   TX       )     ⁢       a     n     RX   ,   1         (       r   RX     ,     Az   RX     ,     El   RX       )                     a     n     TX   ,   2         (       r   TX     ,     Az   TX     ,     El   TX       )     ⁢       a     n     RX   ,   2         (       r   RX     ,     Az   RX     ,     El   RX       )               …                 a     n     TX   ,   N         (       r   TX     ,     Az   TX     ,     El   TX       )     ⁢       a     n     RX   ,   N         (       r   RX     ,     Az   RX     ,     El   RX       )             ]       ,           (   7   )               
where, as with other types of BF, the beamformer may be the normalized array response:
 
     
       
         
           
             
               
                 
                   
                     
                       a 
                       BF 
                     
                     ( 
                     
                       Az 
                       , 
                       El 
                     
                     ) 
                   
                   = 
                   
                     
                       
                         a 
                         ⁡ 
                         ( 
                         
                           Az 
                           , 
                           El 
                         
                         ) 
                       
                       
                         
                           
                             
                               a 
                               H 
                             
                             ( 
                             
                               Az 
                               , 
                               El 
                             
                             ) 
                           
                           ⁢ 
                           
                             a 
                             ⁡ 
                             ( 
                             
                               Az 
                               , 
                               El 
                             
                             ) 
                           
                         
                       
                     
                     . 
                   
                 
               
               
                 
                   ( 
                   8 
                   ) 
                 
               
             
           
         
       
     
     In some embodiments, additional precision can be gained by similarly taking into account the location of individual antenna elements within the Tx antenna array and/or Rx antenna array. 
     Some embodiments may use the omnidirectional and directional proximity sensing techniques described herein in conjunction with machine learning algorithms to help ensure robust proximity detection. Machine learning models can be trained using inputs such as an elevation-azimuth response (which may be decimated, in some embodiments, by retaining only maximum values over range taps); SNR, azimuth, elevation, and range of a strongest target in a directional mode FOV; a ratio of power in the directional mode FOV to power outside the directional mode FOV; power distribution in the directional mode FOV; and/or similar features. In experiments, different types of support vector machine (SVM) models were trained on both positives (having an object present) and negatives (without an object), with a cubic SVM model achieving a 99% accuracy, and other SVM model types (linear, quadratic, Gaussian) also achieving high accuracies. 
     Because leakage can be particularly problematic for short range radar sensing, embodiments may employ any of a variety of leakage cancellation techniques. Leakage adaptation can be used to update and cancel leakage periodically (e.g., once per second, or more) when no object is detected. This can help ensure that leakage is accurately canceled. Other leakage cancellation techniques may employ trigger-based cancellation, based on sensor input or other information indicative of a change in conditions that may change leakage (e.g., a change in temperature, a change of a device cover, etc.). To employ leakage cancellation, a radar system receiver can detect leakage related to a transmission and, after verifying no object is present, use the detected leakage to adapt a leakage cancellation filter to filter out the leakage for subsequent proximity sensing transmissions. 
       FIG.  11    is a flow diagram of a method  1100  of operating a radar system to perform radar proximity detection, according to an embodiment. The method  1100  illustrates aspects of the functionality in the above-described embodiments. One or more of the functions described in the blocks illustrated in  FIG.  11    may be performed by software and/or hardware components of a radar system, such as the radar system  105  illustrated in  FIG.  1   , which may be incorporated into an electronic device, such as the electronic device  1200  illustrated in  FIG.  12   . Moreover, a person of ordinary skill in the art will appreciate that alternative embodiments may vary in the way they implement the functions illustrated in  FIG.  11    by adding, omitting, combining, separating, and otherwise varying the functions illustrated in the blocks of  FIG.  11   . 
     At block  1110 , the functionality includes operating in an omnidirectional proximity sensing mode by performing the operations illustrated in blocks  1110 - a  to  1110 - d . The functionality of block  1110 - a  comprises transmitting, with a transmitter a radar system, a first set of RF pulses, where the first set of RF pulses comprises one or more pulses. As previously noted, transmitted RF signals in omnidirectional proximity sensing can include multiple pulses, where the number of pulses can be based on a balance between achieving robust SNR values and maintaining a low power budget. Because sensing is omnidirectional, the pulses may be transmitted by a single transmitter antenna, which may be part of a larger transmitter antenna array. As such, means for performing the functionality at block  1110 - a  may include, for example, a Tx antenna array  135 , processing unit  115 , and/or other components of a radar system  105 . 
     At block  1110 - b  the functionality comprises receiving, with a receiver of the radar system, at least one first reflected pulse. Similar to the transmitting, this receiving can be done by a single antenna, which may be part of a larger receiver antenna array. As such, means for performing the functionality at block  1110 - b  may include, for example, an Rx antenna array  140 , processing unit  115 , and/or other components of a radar system  105 . 
     The functionality of block  1110 - c  comprises determining, with a processing unit, an object&#39;s presence within a threshold distance of the radar system, based on the receiving and the at least one first reflected pulse. As noted with regard to  FIGS.  4  and  5   , this determination may be based on whether a CIR exceeds a threshold. As such, in some embodiments of the method  1100 , determining the object&#39;s presence further comprises determining a CIR from the at least one first reflected pulse. Embodiments may further comprise performing leakage cancellation on the CIR, as noted, and/or determining whether a maximum value of the CIR exceeds a threshold value. Means for performing the functionality at block  1110 - c  may include, for example, a processing unit  115  and/or other components of a radar system  105 . 
     The functionality of block  1110 - d  comprises, in response to determining the object&#39;s presence, operating the radar system in a directional mode. This leads to the functionality of block  1120 . 
     At block  1120 , the functionality includes operating in a directional proximity sensing mode by performing the operations illustrated in blocks  1120 - a  to  1120 - c . The functionality of block  1120 - a  comprises transmitting, with a transmitter antenna array of the transmitter, a second set of RF pulses, where the second set of RF pulses comprises a plurality of pulses. Here, in contrast to the functionality at  1110 - a , directional proximity sensing comprises BF. And thus, multiple antenna elements of an antenna array can be utilized, and multiple pulses can be transmitted. Means for performing the functionality at block  1120 - a  may include, for example, a Tx antenna array  135 , processing unit  115 , and/or other components of a radar system  105 . 
     At block  1120 - b , the functionality comprises receiving, with a receiver antenna array of the receiver, at least one second reflected pulse, where the at least one second reflected pulse comprises at least one RF from the second set of RF pulses reflected off of the object. Here again, as part of BF, multiple antenna elements of a receiver antenna array can be used to sense multiple RF pulses. Means for performing the functionality at block  1120 - b  may include, for example, an Rx antenna array  140  and/or other components of a radar system  105 . 
     The functionality of block  1120 - c  comprises determining, based on the transmitting of the second set of RF pulses in the receiving of the at least one second reflected pulse, (1) a proximity of the object, and (2) whether the object is within a predetermined FOV. As previously noted, object detection in the directional proximity sensing mode can be based on proximity (range) and SNR/amplitude within an FOV. As noted with regard to  FIG.  9   , because angular information can be determined from directional proximity sensing, a more precise range of an object can be determined. Thus, in some embodiments, determining the proximity of the object may comprise accounting for a difference in a location of the transmitter antenna array and a location of the receiver antenna array. SNR-averaged range estimation may additionally or alternatively be used to determine proximity of the object. Thus, according to some embodiments of the method  1100 , determining the proximity of the object may comprise determining an SNR averaged range estimation. Means for performing the functionality at block  1120 - c  may include, for example, a processing unit  115  and/or other components of a radar system  105 . 
     As noted, embodiments may also help reduce false positives using side lobe filtering techniques. This can include, for example, comparing a value of an SNR sensed within the predetermined FOV to a mean of values sensed outside the predetermined FOV. The value of the SNR sensed within the predetermined FOV may comprise a maximum or a mean of values within the predetermined FOV. 
     Some embodiments may employ leakage cancellation when no object is detected. Thus, in some embodiments of the method  1100 , the method may further comprise transmitting, with the transmitter of the radar system, a third set of RF pulses, where the third set of RF pulses comprises one or more pulses, measuring, with the receiver of the radar system, a leakage related to the transmitting of the third set of RF pulses, determining, in response to transmitting the third set of RF pulses, that the object is no longer within the threshold distance of the radar system, and adapting a leakage cancellation filter based on the measured leakage related to the transmitting the third set of RF pulses. 
     Operating a radar system in the manner illustrated in  FIG.  11    can further result in providing a proximity detection output in response to determining that the proximity of the object is within a predetermined detection range and the object is within the predetermined FOV. This output may comprise an output to an application, operating system, or hardware layer of an electronic device (e.g., electronic device  205  of  FIG.  2   ). In some embodiments, the proximity detection output may further comprise a location of the detected object (e.g., range and/or location of the detected object relative to a point of reference on the electronic device). Additionally or alternatively, because velocity (Doppler) may be determined from reflected signals in either mode, some embodiments may further comprise providing a velocity of the object, wherein the velocity of the object is determined based on the at least one first reflected pulse in the omnidirectional proximity sensing mode, the at least one second reflected pulse in the directional proximity sensing mode, or both. Moreover, as noted, the predetermined FOV may be configurable. And thus, the radar system may receive an input (e.g., from an application layer or a hardware layer) indicative of an area of interest from which the FOV may be determined. 
       FIG.  12    is a block diagram of an embodiment of an electronic device  1200 , which may incorporate a radar system  105  that can be operated in the manner discussed in the previously-described embodiments. Although some embodiments of an electronic device  1200  may correspond to the particular type of electronic device  205  of  FIG.  2    (e.g., a mobile phone), embodiments are not so limited. It should be noted that  FIG.  12    is meant only to provide a generalized illustration of various components, any or all of which may be utilized as appropriate.  FIG.  12   , therefore, broadly illustrates how individual system elements may be implemented in a relatively separated or relatively more integrated manner. In addition, it can be noted that components illustrated by  FIG.  12    can be localized to a single device and/or distributed among various networked devices, which may be disposed at different physical or geographical locations. The electronic device  1200  may comprise and/or be integrated into any of a variety of devices, including a mobile phone, tablet, personal computer (PC), laptop, and/or the like. 
     The electronic device  1200  is shown comprising hardware elements that can be electrically coupled via a bus  1205  (or may otherwise be in communication, as appropriate). The hardware elements may include processing unit(s)  1210 , which can include without limitation one or more general-purpose processors, one or more special-purpose processors (such as a DSP, graphics processing unit (GPU), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), and/or the like), and/or other processing structure, which can be configured to perform one or more of the methods described herein, including the method described in relation to  FIG.  11   . The electronic device  1200  also can include one or more input devices  1215 , which can include without limitation a mouse, a keyboard, a camera, a microphone, a touchscreen, and/or the like; and one or more output devices  1220 , which can include without limitation a display device, a speaker, and/or the like. 
     The electronic device  1200  may further include (and/or be in communication with) one or more non-transitory storage devices  1225 , which can comprise, without limitation, local and/or network accessible storage, and/or can include, without limitation, a disk drive, a drive array, an optical storage device, a solid-state storage device (such as a random access memory (RAM) and/or a read-only memory (ROM)), which can be programmable, flash-updateable, and/or the like. Such storage devices may be configured to implement any appropriate data stores, including without limitation, various file systems, database structures, and/or the like. 
     The electronic device  1200  may also include a communications subsystem  1230 , which can include support of wireline communication technologies and/or wireless communication technologies (in some embodiments) managed and controlled by a wireless communication interface  1233 . The communications subsystem  1230  may include a modem, a network card (wireless or wired), an infrared communication device, a wireless communication device, and/or a chipset, and/or the like. The communications subsystem  1230  may include one or more input and/or output communication interfaces, such as the wireless communication interface  1233 , to permit data and signaling to be exchanged with a network, mobile devices, other computer systems, and/or any other electronic devices described herein. As previously noted, a radar system  105  (as illustrated in  FIG.  1   ) may be incorporated into a wireless communications interface  1233  such that antenna elements in a Tx antenna array  135  and Rx antenna array  140 , and the circuitry connected with the antenna elements (e.g., the other components of the radar system  105 ), may be used for both RF imaging and data communication. For example, in some embodiments, the wireless communication interface  1233  may comprise an 802.11ad- and/or 802.11ay-compatible modem capable of both radar-based proximity sensing and data communication. 
     As noted, some embodiments may have a radar system  105  that is not used for wireless communication. In such instances, the radar system  105  may be incorporated elsewhere within the electronic device  1200 . In some embodiments, for example, the radar system  105  may be incorporated into the electronic device  1200  as an input device  1215 . 
     In many embodiments, the electronic device  1200  will further comprise a working memory  1235 , which can include a RAM and/or or ROM device. Software elements, shown as being located within the working memory  1235 , can include an operating system  1240 , device drivers, executable libraries, and/or other code, such as application(s)  1245 , which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein. Merely by way of example, one or more procedures described with respect to the method(s) discussed above, such as the methods described in relation to  FIGS.  7  and  10   , may be implemented as code and/or instructions that are stored (e.g. temporarily) in working memory  1235  and are executable by a computer (and/or a processing unit within a computer such as processing unit(s)  1210 ); in an aspect, then, such code and/or instructions can be used to configure and/or adapt a general purpose computer (or other device) to perform one or more operations in accordance with the described methods. 
     A set of these instructions and/or code might be stored on a non-transitory computer-readable storage medium, such as the storage device(s)  1225  described above. In some cases, the storage medium might be incorporated within a computer system, such as electronic device  1200 . In other embodiments, the storage medium might be separate from a computer system (e.g., a removable medium, such as an optical disc), and/or provided in an installation package, such that the storage medium can be used to program, configure, and/or adapt a general purpose computer with the instructions/code stored thereon. These instructions might take the form of executable code, which is executable by the electronic device  1200  and/or might take the form of source and/or installable code, which, upon compilation and/or installation on the electronic device  1200  (e.g., using any of a variety of generally available compilers, installation programs, compression/decompression utilities, etc.), then takes the form of executable code. 
     It will be apparent to those skilled in the art that substantial variations may be made in accordance with specific requirements. For example, customized hardware might also be used, and/or particular elements might be implemented in hardware, software (including portable software, such as applets, etc.), or both. Further, connection to other computing devices such as network input/output devices may be employed. 
     With reference to the appended figures, components that can include memory can include non-transitory machine-readable media. The term “machine-readable medium” and “computer-readable medium” as used herein, refer to any storage medium that participates in providing data that causes a machine to operate in a specific fashion. In embodiments provided hereinabove, various machine-readable media might be involved in providing instructions/code to processing units and/or other device(s) for execution. Additionally or alternatively, the machine-readable media might be used to store and/or carry such instructions/code. In many implementations, a computer-readable medium is a physical and/or tangible storage medium. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Common forms of computer-readable media include, for example, magnetic and/or optical media, any other physical medium with patterns of holes, a RAM, a PROM, EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read instructions and/or code. 
     The methods, systems, and devices discussed herein are examples. Various embodiments may omit, substitute, or add various procedures or components as appropriate. For instance, features described with respect to certain embodiments may be combined in various other embodiments. Different aspects and elements of the embodiments may be combined in a similar manner. The various components of the figures provided herein can be embodied in hardware and/or software. Also, technology evolves and, thus, many of the elements are examples that do not limit the scope of the disclosure to those specific examples. 
     It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, information, values, elements, symbols, characters, variables, terms, numbers, numerals, or the like. It should be understood, however, that all of these or similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as is apparent from the discussion above, it is appreciated that throughout this Specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” “ascertaining,” “identifying,” “associating,” “measuring,” “performing,” or the like refer to actions or processes of a specific apparatus, such as a special purpose computer or a similar special purpose electronic computing device. In the context of this Specification, therefore, a special purpose computer or a similar special purpose electronic computing device is capable of manipulating or transforming signals, typically represented as physical electronic, electrical, or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the special purpose computer or similar special purpose electronic computing device. 
     Terms, “and” and “or” as used herein, may include a variety of meanings that also is expected to depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B, or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B, or C, here used in the exclusive sense. In addition, the term “one or more” as used herein may be used to describe any feature, structure, or characteristic in the singular or may be used to describe some combination of features, structures, or characteristics. However, it should be noted that this is merely an illustrative example and claimed subject matter is not limited to this example. Furthermore, the term “at least one of” if used to associate a list, such as A, B, or C, can be interpreted to mean any combination of A, B, and/or C, such as A, AB, AA, AAB, AABBCCC, etc. 
     Having described several embodiments, various modifications, alternative constructions, and equivalents may be used without departing from the spirit of the disclosure. For example, the above elements may merely be a component of a larger system, wherein other rules may take precedence over or otherwise modify the application of the various embodiments. Also, a number of steps may be undertaken before, during, or after the above elements are considered. Accordingly, the above description does not limit the scope of the disclosure.