JP2015087352A - Traveling speed estimation device, still object classification device and traveling speed estimation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a traveling speed estimation device, a still object classification device and a traveling speed estimation method capable of estimating the traveling speed of a traveling object on which a radar device is mounted with high accuracy.SOLUTION: A traveling speed estimation device includes: a speed position measurement part; a position estimation part; an object classification part; and a traveling speed estimation part. The speed position determination part is configured to, on the basis of the output of a radar device which receives an electromagnetic wave reflected by an object, repeatedly measure a relative speed and a relative position between the object and the radar device. The position estimation part is configured to, on the basis of the measured relative speed and relative position of the object, estimate the relative position between the object and the radar device at a plurality of time. The object classification part is configured to, on the basis of the comparison of the estimated relative position of the object and the measured relative position of the object, classify the object into a still object. The traveling speed estimation part is configured to, on the basis of the relative speed between the object classified into the still object and the radar device, estimate the traveling speed of the traveling object on which the radar device is mounted.

Description

  Embodiments described herein relate generally to a moving speed estimation device, a stationary object classification device, and a moving speed estimation method.

  Patent Document 1 discloses an absolute speed measurement device (movement speed estimation device) that measures the absolute speed of a vehicle using a radar device. Further, Patent Document 2 discloses a vehicle movement state detection apparatus (movement speed estimation apparatus) that detects a relative speed of a vehicle using a radar apparatus.

JP 2006-337025 A JP 2010-43960 A

  However, the moving speed estimation device has a problem that it cannot accurately estimate the moving speed of a moving body equipped with a radar device.

  The problem to be solved by the present invention is to provide a moving speed estimating device, a stationary object classifying device, and a moving speed estimating method capable of estimating with high accuracy the moving speed of a moving body equipped with a radar device. .

  The movement speed estimation device of the embodiment includes a speed position measurement unit, a position estimation unit, an object classification unit, and a movement speed estimation unit. The velocity position measurement unit repeatedly measures the relative velocity and the relative position between the object and the radar device based on the output of the radar device that receives the electromagnetic wave reflected by the object. The position estimation unit estimates the relative position between the object and the radar apparatus at a plurality of times based on the measured relative speed and relative position of the object. The object classifying unit classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object. The moving speed estimation unit estimates the moving speed of the moving body on which the radar device is mounted based on the relative speed between the object classified as a stationary object and the radar device.

  The stationary object classification device according to the embodiment includes a velocity position measurement unit, a position estimation unit, and an object classification unit. The velocity position measurement unit repeatedly measures the relative velocity and the relative position between the object and the radar device based on the output of the radar device that receives the electromagnetic wave reflected by the object. The position estimation unit estimates the relative position between the object and the radar apparatus at a plurality of times based on the measured relative speed and relative position of the object. The object classifying unit classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object.

It is a block diagram which shows the structural example of the moving speed estimation system in one Embodiment. It is an external view which shows the example of the moving body carrying the moving speed estimation apparatus in one Embodiment. It is an overhead view which shows the example of the relative position of an object and a radar apparatus in one Embodiment. It is a figure which shows the example of distribution of relative velocity in one Embodiment. It is a figure which shows the example of distribution of the relative velocity from which noise was removed in one Embodiment. It is a figure which shows the example of the measured relative position of the object and radar apparatus in one Embodiment. It is a figure which shows the 1st example of the process which classifies an object into the candidate of a stationary object in one Embodiment. It is a figure showing the 2nd example of processing which classifies an object into a candidate for a stationary object in one embodiment. It is a figure which shows the example of the object classified into the stationary object in one Embodiment. It is a figure which shows the example of distribution of the relative velocity of a stationary object in one Embodiment. It is a flowchart which shows the example of the operation | movement procedure of the moving speed estimation apparatus in one Embodiment.

  Embodiments will be described in detail with reference to the drawings. FIG. 1 is a block diagram showing a configuration example of a moving speed estimation system. The moving speed estimation system 10 includes a radar apparatus 100, a moving speed estimation apparatus 200, and a speed presentation apparatus 300. The moving speed estimation apparatus 200 can estimate the moving speed of a moving body mounted with the radar apparatus 100 with high accuracy.

  The radar apparatus 100 forms a covered area by irradiating electromagnetic waves in a predetermined installation direction. Here, the radar apparatus 100 may sweep the frequency of the electromagnetic wave in a predetermined short cycle. The radar apparatus 100 may irradiate electromagnetic waves by an FMCW (Frequency Modulated Continuous Wave) radar system. In addition, the radar apparatus 100 may irradiate electromagnetic waves by other methods (for example, a pulse Doppler method), and the method is not particularly limited.

  The radar apparatus 100 receives an electromagnetic wave reflected by an object located within the formed coverage. The radar apparatus 100 includes one or a plurality of radar units. In FIG. 1, the radar apparatus 100 includes, as an example, a radar unit 100a, a radar unit 100b, a radar unit 100c, and a radar unit 100d.

  The radar unit 100a outputs a signal corresponding to the received electromagnetic wave. The same applies to the radar units 100b to 100d. When the moving speed estimation system 10 includes a plurality of radar units such as the radar unit 100a to the radar unit 100d, the moving unit speed of the moving unit can be estimated robustly by the diversity effect.

  The moving speed estimation apparatus 200 estimates the moving body speed of the moving body with high accuracy based on a signal corresponding to the received electromagnetic wave (output of the radar apparatus 100). The moving speed estimation device 200 includes a stationary object classification device 210 and a moving speed estimation unit 220. The stationary object classification device 210 includes a speed position measurement unit 211, a position estimation unit 212, an object classification unit 213, and a storage unit 214.

  Some or all of these functional units are software functional units that function when, for example, a processor such as a CPU (Central Processing Unit) executes a program stored in the storage unit 214. Some or all of these functional units may be hardware functional units such as LSI (Large Scale Integration) and ASIC (Application Specific Integrated Circuit). The storage unit 214 includes a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an HDD (Hard Disk Drive), a register, and the like.

  A signal corresponding to the received electromagnetic wave is input to the speed position measurement unit 211 as an output of the radar apparatus 100. Further, identification information (for example, coordinate information) for identifying a candidate for a stationary object is input from the object classification unit 213 to the speed position measurement unit 211. The speed position measurement unit 211 repeatedly measures the relative speed and relative position between the object and the radar apparatus 100 at predetermined intervals based on the output of the radar apparatus 100. The measurement result is stored in the storage unit 214 as a history.

  The velocity position measurement unit 211 may measure the relative velocity and the relative position between the object and the radar apparatus 100 by, for example, MRAV (Measurement Range after Measurement Velocity) method. The speed position measuring unit 211 may measure the relative speed and the relative position by other methods, and the method is not limited.

  The speed position measurement unit 211 detects noise from the distribution of the measured relative speed. For example, the speed position measurement unit 211 may detect, as noise, a relative speed that deviates from another relative speed by more than a predetermined speed in the measured relative speed distribution. The speed position measurement unit 211 determines an object that has moved at a relative speed that has not been detected as noise as a candidate for a stationary object. Here, the speed position measurement unit 211 may determine still object candidates so as to further narrow the candidates from the still object candidates already classified by the object classification unit 213.

  The position estimation unit 212 acquires history information indicating the relative speed and relative position of the object measured at a plurality of times by the speed position measurement unit 211 from the storage unit 214. The position estimation unit 212 estimates the relative position between the object and the radar apparatus 100 at a plurality of times for each measured time based on the relative speed and the relative position of the object measured at a plurality of times. Further, the position estimation unit 212 may estimate the relative speed between the object and the radar apparatus 100 at a plurality of times for each measured time based on the measured relative speed and relative position of the object.

  More specifically, the position estimation unit 212 assumes that the relative velocity vector of an object classified as a stationary object candidate continues, and uses an expectation maximization (EM) algorithm to detect the object and the radar apparatus 100. At least one of the relative speed and the relative position may be estimated. The position estimation unit 212 may estimate at least one of the relative speed and the relative position between the object and the radar apparatus 100 by applying a Kalman filter to the expected value of the relative speed.

  The object classification unit 213 classifies the object as a stationary object based on a comparison between the relative position of the object estimated by the position estimation unit 212 and the relative position of the object measured by the velocity position measurement unit 211. Details of the stationary object classification apparatus 210 including the object classification unit 213 will be described later with reference to FIGS.

  The moving speed estimation unit 220 estimates the moving speed of the moving body 400 on which the radar apparatus 100 is mounted based on the relative speed between the object classified as a stationary object and the radar apparatus 100. Here, the moving speed estimation unit 220 may estimate the moving speed of the moving body 400 based on the median value of the relative speed distribution between the object classified as the stationary object and the radar apparatus 100.

  Further, the moving speed estimation unit 220 may estimate the moving speed of the moving object 400 based on the relative speed history (time series data) between the object classified as a stationary object and the radar apparatus 100. Further, the movement speed estimation unit 220 may calculate exercise information indicating, for example, the accumulated movement distance and the movement locus based on the estimated movement speed. Details of the moving speed estimation apparatus 200 including the moving speed estimation unit 220 will be described later with reference to FIGS.

  Information indicating the motion of the moving body 400 is input to the speed presentation apparatus 300 from the movement speed estimation apparatus 200. The speed presentation device 300 presents information indicating the movement of the moving body 400. For example, the speed presentation device 300 may be a display device. When the speed presentation device 300 is a display device, the speed presentation device 300 displays information indicating the motion of the moving body 400 on the screen. For example, the speed presentation device 300 may be an audio output device. When the speed presentation device 300 is a voice output device, the speed presentation device 300 outputs information indicating the motion of the moving body 400 as voice generated by predetermined voice processing.

  FIG. 2 shows an example of a moving body on which the moving speed estimation apparatus 200 is mounted by an external view. The radar apparatus 100, the moving speed estimation apparatus 200, and the speed presentation apparatus 300 are mounted on the moving body 400 and move together with the moving body 400. The moving body 400 is, for example, a vehicle, an aircraft, a ship, or a hovercraft, and is not particularly limited as long as it is a movable object.

  The radar unit 100a irradiates an electromagnetic wave in a predetermined first installation direction to form a first covered area 110a, and the electromagnetic wave reflected by an object positioned in the formed first covered area 110a. Receive. The radar unit 100b radiates electromagnetic waves in a predetermined second installation direction to form the second covered area 110b, and the electromagnetic waves reflected by the object located in the formed second covered area 110b. Receive.

  The radar unit 100c irradiates an electromagnetic wave in a predetermined third installation direction to form a third covered area 110c, and the electromagnetic wave reflected by an object located in the formed third covered area 110c. Receive. The radar unit 100d irradiates an electromagnetic wave in a predetermined fourth installation direction to form a fourth covered area 110d, and the electromagnetic wave reflected by an object located in the formed fourth covered area 110d. Receive. Note that at least part of the covered area may overlap. Further, as described above, the radar apparatus 100 may include one radar unit.

  FIG. 3 shows an example of the relative position between the object and the radar apparatus 100 as an overhead view. Hereinafter, the moving body 400 will be described as an example of moving the surface S (for example, the ground surface, the water surface). Hereinafter, the description will be continued based on a two-dimensional coordinate system (XY coordinate system) defined for the surface S for convenience. The moving body 400 moves on the surface S in the positive direction of the Y axis at a predetermined moving speed.

  Further, in the positive direction of the Y axis with respect to the moving body 400, as an example, the first object 500, the second object 510, the third object 520, the fourth object 530, the fifth object 600, Assume that six objects 610 are located. The first object 500, the second object 510, the third object 520, the fourth object 530, the fifth object 600, and the sixth object 610 may be stationary objects or non-stationary objects (moving objects). These objects are classified by the stationary object classification device 210 as a stationary object or a non-stationary object.

  Hereinafter, description will be made based on a two-dimensional coordinate system (xy coordinate system) determined for the convenience of the moving speed estimation apparatus 200. The radar unit 100a forms a first covered area 110a in the positive direction of the y-axis (first installation direction). The radar unit 100b forms a second covered area 110b in the positive direction of the y axis (second installation direction). In FIG. 3, the third covered area 110c and the fourth covered area 110d are not shown.

  Hereinafter, the first object 500, the second object 510, the third object 520, the fourth object 530, the fifth object 600, and the sixth object 610 are located in the first covered area 110a or the second covered area 110b. And Note that the y-axis determined in the moving speed estimation apparatus 200 may be parallel to the Y-axis or may not be parallel to the Y-axis depending on the moving direction of the moving body 400.

Next, details of the moving speed estimation apparatus 200 will be described.
FIG. 4 shows an example of a relative velocity distribution (histogram). The horizontal axis represents the relative speed between the object and the radar apparatus 100. The vertical axis represents the number of detected objects. The speed position measurement unit 211 detects noise from the distribution of the measured relative speed. In FIG. 4, the relative speed of the object moved by the relative speed vector V2 is detected as noise by a predetermined detection process.

  FIG. 5 shows an example of a relative velocity distribution (histogram) from which noise is removed. The horizontal axis represents the relative speed between the object and the radar apparatus 100. The vertical axis represents the number of detected objects. The speed position measurement unit 211 removes noise detected by a predetermined detection process from the distribution of relative speeds. For example, the speed position measurement unit 211 may exclude noise detected by the process of comparing a plurality of peaks in the relative speed distribution from the relative speed distribution. Further, the speed position measuring unit 211 removes the relative speed greatly deviating from the relative speed distribution at the previous measurement time (time t-1) from the relative speed distribution at the current measurement time (time t). Also good.

  The position estimation unit 212 estimates the relative position between the object and the radar apparatus 100 by predetermined statistical processing (integration processing) based on the relative velocity vector V1 of the candidate for the stationary object and the relative position. For example, the relative velocity vector V1 may be a median value of the relative velocity vectors V1a to V1e (described later with reference to FIG. 6). Note that the statistical process executed by the speed position measurement unit 211 is not limited to the process for obtaining the median value, and may be any process.

  FIG. 6 shows an example of the measured relative position between the object and the radar apparatus 100. Time t-1 is the first measurement time. The time t is a second measurement time after the first measurement time. These measurement times may be times corresponding to the frequency sweep cycle of electromagnetic waves.

The first object 500 is at a relative position indicated as “500-2” in FIG. 6 at time t-1. Further, it is assumed that the first object 500 moves with the relative velocity vector V1a and is at the relative position indicated as “500-1” in FIG. 6 at time t.
The second object 510 is in a relative position indicated as “510-2” in FIG. 6 at time t-1. Further, it is assumed that the second object 510 moves with the relative velocity vector V1b and is at the relative position indicated as “510-1” in FIG. 6 at time t.

The third object 520 is in a relative position indicated as “520-2” in FIG. 6 at time t-1. Further, it is assumed that the third object 520 moves at the relative velocity vector V1c and is at the relative position indicated as “520-1” in FIG. 6 at time t.
The fourth object 530 is at a relative position indicated as “530-2” in FIG. 6 at time t-1. Further, it is assumed that the fourth object 530 moves with the relative velocity vector V1d and is at a relative position indicated as “530-1” in FIG. 6 at time t.

The fifth object 600 is in a relative position indicated as “600-2” in FIG. 6 at time t−1. Further, it is assumed that the fifth object 600 moves at the relative velocity vector V2 and is at the relative position indicated as “600-1” in FIG. 6 at time t.
The sixth object 610 is in a relative position indicated as “610-2” in FIG. 6 at time t-1. Further, it is assumed that the sixth object 610 moves with the relative velocity vector V1e and is at the relative position indicated as “610-1” in FIG. 6 at time t.

  FIG. 7 shows a first example of processing for classifying an object as a candidate for a stationary object. In FIG. 7, the speed position measurement unit 211 excludes the fifth object 600 moved by the relative speed vector V2 from the stationary object candidates based on the relative speed distribution shown in FIG. In other words, the speed position measurement unit 211 converts the first object 500, the second object 510, the third object 520, the fourth object 530, and the fifth object 600 that have moved at a relative speed not detected as noise into a stationary object. Set as a candidate.

  In FIG. 7, the position estimation unit 212 estimates the relative position of the first object 500 at time t. Here, the position estimation unit 212 obtains a corresponding point of the first object 500 within the first range 501 based on a nearest neighbor (NN) correlation, whereby the relative position of the first object 500 at time t. May be estimated. For example, the position estimation unit 212 determines the corresponding point by moving the relative position of the first object 500 at time t−1, which is indicated as “500-2” in FIG. 7, by the relative velocity vector V1. The first range 501 centered on the point is estimated as the error range of the relative position of the first object 500 at time t.

The position estimation unit 212 similarly estimates the relative positions of other stationary object candidates at time t. That is, the position estimation unit 212 includes the second range 511 of the relative position of the second object 510 at the time t, the third range 521 of the relative position of the third object 520, the fourth range 531 of the relative position of the fourth object 530, And the 5th range 611 of the relative position of the 6th object 610 is estimated similarly.
The radius of the first range 501, the radius of the second range 511, the radius of the third range 521, the radius of the fourth range 531, and the radius of the fifth range 611 are predetermined distances. Moreover, each shape of the 1st range 501-the 5th range 611 may not be circular shape, and is not specifically limited.

  The object classification unit 213 includes the relative position of the first object 500 at time t, which is indicated as “500-1” in FIG. 7, included in the estimated relative position error range, that is, the first range 501. It is determined whether or not. In FIG. 7, since the relative position indicated as “500-1” is included in the first range 501, the object classification unit 213 classifies the first object 500 as a stationary object candidate. That is, the object classifying unit 213 classifies an object for which a corresponding point is found in the first range 501 as a stationary object candidate. By performing the classification process similarly, in FIG. 7, the object classification unit 213 classifies the second object 510 to the fourth object 530 into stationary object candidates.

  The object classification unit 213 includes the relative position of the sixth object 610 at time t, which is indicated as “610-1” in FIG. 7, included in the estimated relative position error range, that is, the fifth range 611. It is determined whether or not. In FIG. 7, since the relative position indicated as “610-1” is not included in the fifth range 611, the object classification unit 213 excludes the fifth range 611 from the stationary object candidates.

  FIG. 8 shows a second example of processing for classifying an object as a stationary object candidate. The object classification unit 213 may exclude, from among the stationary object candidates, objects located within a predetermined distance from the relative position other than the stationary object candidate (moving object) from the stationary object candidates. Thereby, the object classification unit 213 can classify the object as a stationary object with higher accuracy.

  The object classification unit 213 displays the stationary object in the sixth range 602 centered on the relative position of the fifth object 600 (other than the stationary object candidate) at time t−1, which is indicated as “600-2” in FIG. It is determined whether or not candidates are included. In addition, the object classification unit 213 displays a sixth range 612 centered on the relative position of the sixth object 610 (other than a stationary object candidate) at time t−1, which is indicated as “610-2” in FIG. It is determined whether a stationary object candidate is included.

  Since the partial range of the relative position of the fourth object 530 (still object candidate) at time t, which is indicated as “530-1” in FIG. 8, is included in the seventh range 612, the object classification unit 213 Excludes the fourth object 530 from the stationary object candidates. The radius of the sixth range 602 and the radius of the seventh range 612 are predetermined distances. Further, the shapes of the sixth range 602 and the seventh range 612 need not be circular and are not particularly limited.

  FIG. 9 shows an example of an object classified as a stationary object. The first object 500, the second object 510, and the third object 520 are classified as stationary objects by the classification process described with reference to FIGS. The first object 500 (stationary object) moves with the relative velocity vector V1a, and is at the relative position indicated as “500-1” in FIG. 9 at time t. The second object 510 (stationary object) moves with the relative velocity vector V1b, and is at the relative position indicated as “510-1” in FIG. 9 at time t. The third object 520 (stationary object) moves with the relative velocity vector V1c, and is at the relative position indicated as “520-1” in FIG. 9 at time t.

  FIG. 10 shows an example of a relative velocity distribution (histogram) of a stationary object. The horizontal axis represents the relative speed between the object and the radar apparatus 100. The vertical axis represents the number of detected objects. The moving speed estimation unit 220 estimates the moving speed of the moving body 400 based on the distribution of relative speeds of the classified stationary objects. In FIG. 10, the moving speed estimation unit 220 estimates the relative speed vector V1A of the stationary object as the moving speed of the radar apparatus 100, that is, the moving speed of the classified moving body 400. The moving speed estimation unit 220 determines a relative speed vector V1A of the stationary object by a predetermined statistical process for the stationary object group. For example, the relative velocity vector V1A may be a median value of the relative velocity vectors V1a to V1c shown in FIG. In addition, the statistical process which the movement speed estimation part 220 performs is not specifically limited.

Next, an example of an operation procedure of the moving speed estimation device will be described.
FIG. 11 is a flowchart illustrating an example of an operation procedure of the moving speed estimation device. The radar apparatus 100 irradiates the first covered area 110a and the second covered area 110b with electromagnetic waves. The radar apparatus 100 receives an electromagnetic wave reflected by an object (for example, the first object 500 or the like) located in the first covered area 110a or the second covered area 110b.

(Step S <b> 1) The speed position measurement unit 211 measures the relative speed and the relative position between the object and the radar apparatus 100 based on the electromagnetic wave reflected by the object and received by the radar apparatus 100.
(Step S2) The speed position measuring unit 211 detects noise from the distribution of the measured relative speed.

  (Step S3) The speed position measuring unit 211 determines an object that has moved at a relative speed that is not detected as noise as a candidate for a stationary object. Here, when the object classification unit 213 has already classified the stationary object candidates, the speed position measurement unit 211 determines a stationary object candidate from among the stationary object candidates already classified by the object classification unit 213. Also good.

(Step S4) The position estimation unit 212 estimates the relative position between the stationary object candidate and the radar apparatus 100 based on the relative velocity of the stationary object candidate and the history of the relative position of the stationary object candidate.
(Step S5) The object classification unit 213 selects an object located within a predetermined distance from the relative position of the estimated stationary object candidate among the stationary object candidates whose relative position is estimated as a stationary object candidate. leave.

  (Step S6) The object classifying unit 213 excludes, from among the remaining stationary object candidates, objects located within a predetermined distance from the relative position other than the stationary object candidate (moving object) from the stationary object candidates. To classify it as a stationary object. Here, the relative position other than the stationary object candidate (moving object) may be the relative position measured at the previous measurement time.

  (Step S <b> 7) The moving speed estimation unit 220 estimates the moving speed of the moving body 400 on which the radar apparatus 100 is mounted, based on the relative speed distribution of the stationary object left without being excluded. The movement speed estimation unit 220 outputs information indicating the movement speed of the moving body 400 to the speed presentation device 300. The speed presentation device 300 presents information indicating the movement of the moving body 400. For example, the speed presentation device 300 may present information indicating the moving speed of the moving body 400 as information indicating the movement of the moving body 400.

  (Step S8) The moving speed estimation unit 220 determines whether or not to end the process of estimating the moving speed. When ending the process of estimating the moving speed (step S8: YES), the moving speed estimating unit 220 ends the process of estimating the moving speed. On the other hand, when the process for estimating the moving speed is not terminated (step S8: NO), the moving speed estimating unit 220 returns the process to step S1.

  As described above, the moving speed estimation apparatus 200 according to the embodiment includes the speed position measuring unit 211, the position estimating unit 212, the object classifying unit 213, and the moving speed estimating unit 220. The speed position measurement unit 211 repeatedly measures the relative speed and the relative position between the object and the radar apparatus 100 based on the output of the radar apparatus 100 that receives the electromagnetic wave reflected by the object (for example, the first object 500). . The position estimation unit 212 estimates the relative position between the object and the radar apparatus 100 at a plurality of times based on the measured relative speed and relative position of the object. The object classifying unit 213 classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object. The moving speed estimation unit 220 estimates the moving speed of the moving body 400 on which the radar apparatus 100 is mounted based on the relative speed between the object classified as a stationary object and the radar apparatus 100.

  The moving speed estimation method in the moving speed estimation apparatus 200 includes a step executed by the speed position measurement unit 211, a step executed by the position estimation unit 212, and a step executed by the object classification unit 213. And a step executed by the moving speed estimation unit 220. The speed position measurement unit 211 determines the relative speed and relative position between the object and the radar apparatus 100 at a plurality of times based on the output of the radar apparatus 100 that receives the electromagnetic wave reflected by the object (for example, the first object 500). taking measurement. The position estimation unit 212 estimates the relative position between the object and the radar apparatus 100 at a plurality of times based on the measured relative speed and relative position of the object. The object classifying unit 213 classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object. The moving speed estimation unit 220 estimates the moving speed of the moving body on which the radar apparatus 100 is mounted based on the relative speed between the object classified as a stationary object and the radar apparatus 100.

  With this configuration, the moving speed estimation unit 220 estimates the moving speed of the moving body 400 on which the radar apparatus 100 is mounted based on the relative speed between the object classified as a stationary object and the radar apparatus 100. For example, the moving speed estimation apparatus 200 according to the embodiment measures the relative position of an object around the moving body 400 for a long time based on the relative speed measured in a short time for frequency sweeping of the electromagnetic wave, and detects the object measured for a long time. Among them, the moving speed of the moving body 400 may be estimated based on the history of the relative speed and the relative position classified as a stationary object.

  Thereby, the moving speed estimation apparatus 200 and the moving speed estimation method of the embodiment estimate the moving speed of the radar apparatus 100, that is, the moving speed (motion) of the moving body 400 equipped with the radar apparatus 100 with high accuracy. Can do. Moreover, the moving speed estimation apparatus 200 of the embodiment can estimate the moving speed of the moving body 400 with high resolution. Moreover, the moving speed estimation apparatus 200 of the embodiment can estimate the moving speed of the moving body 400 with high responsiveness. Moreover, the moving speed estimation apparatus 200 according to the embodiment can robustly estimate the moving speed of the moving body 400.

  In addition, the moving speed estimation apparatus 200 according to the embodiment estimates the moving speed of the moving object 400 based on the relative speed and the relative position of not only a nearby stationary object candidate but also a far stationary object candidate irradiated with an electromagnetic wave. Therefore, the moving speed of the moving object 400 can be estimated with higher accuracy than in the case where the object is estimated based on the imaged image (passively estimated). Moreover, the moving speed estimation apparatus 200 of the embodiment can estimate the moving speed of the moving body 400 without being influenced by environmental changes such as weather.

  Further, the moving speed estimation device 200 of the embodiment can accurately move the moving speed of the moving body 400 without being affected by wear of the wheel diameter or idling of the moving body 400 even when the moving body 400 has wheels. Can be estimated. Moreover, the moving speed estimation apparatus 200 of the embodiment can estimate the moving speed of the moving body 400 with high accuracy even when the moving body 400 does not have wheels. Moreover, the moving speed estimation apparatus 200 of the embodiment can estimate the moving speed of the moving object 400 with high accuracy even in a place where positioning radio waves from satellites cannot be received.

  The position estimation unit 212 may estimate the relative position between the object and the radar apparatus 100 based on the Kalman filter. The position estimation unit 212 may estimate the relative velocity between the object and the radar apparatus 100 based on the Kalman filter.

  The moving speed estimation unit 220 estimates the moving speed of the moving body 400 on which the radar apparatus 100 is mounted based on the median of the relative speed distribution between the object classified as the stationary object and the radar apparatus 100. Good.

  The moving speed estimation unit 220 may estimate the moving speed of the moving object 400 on which the radar apparatus 100 is mounted based on the history of relative speed between the object classified as a stationary object and the radar apparatus 100.

  The position estimation unit 212 may estimate the relative position between the object and the radar apparatus 100 using an expected value maximization algorithm (EM algorithm). The position estimation unit 212 may estimate the relative speed between the object and the radar apparatus 100 using an expected value maximization algorithm.

  The stationary object classification apparatus 210 according to the embodiment includes a velocity position measurement unit 211, a position estimation unit 212, and an object classification unit 213. The speed position measurement unit 211 repeatedly measures the relative speed and the relative position between the object and the radar apparatus 100 based on the output of the radar apparatus 100 that receives the electromagnetic wave reflected by the object. The position estimation unit 212 estimates the relative position between the object and the radar apparatus 100 at a plurality of times based on the measured relative speed and relative position of the object. The object classifying unit 213 classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object.

  With this configuration, the object classification unit 213 classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object. Thereby, the stationary object classification apparatus 210 according to the embodiment can classify an object into a stationary object with high accuracy. In addition, the stationary object classification apparatus 210 according to the embodiment can classify an object into a stationary object and robustly.

  According to the moving speed estimation apparatus 200 of at least one embodiment described above, the moving speed estimation unit 220 that estimates the moving speed based on the relative speed between the object classified as a stationary object and the radar apparatus 100 is provided. The moving speed of the moving body 400 can be estimated with high accuracy.

  As mentioned above, although some embodiment of this invention was described, these embodiment is shown as an example and is not intending limiting the range of invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

  In addition, a program for realizing the moving speed estimation device 200 and the stationary object classification device 210 described above is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read by a computer system. Execution processing may be performed by execution. Here, the “computer system” may include an OS and hardware such as peripheral devices.

  Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used. The “computer-readable recording medium” means a flexible disk, a magneto-optical disk, a ROM, a writable nonvolatile memory such as a flash memory, a portable medium such as a CD-ROM, a hard disk built in a computer system, etc. This is a storage device.

Further, the “computer-readable recording medium” refers to a volatile memory (for example, DRAM (Dynamic) in a computer system serving as a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. Random Access Memory)) that holds a program for a certain period of time is also included.
The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line.
The program may be for realizing a part of the functions described above.
Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

DESCRIPTION OF SYMBOLS 10 ... Movement speed estimation system, 100 ... Radar apparatus, 100a ... 1st radar part, 100b ... 2nd radar part, 100c ... 3rd radar part, 100d ... 4th radar part, 110a ... 1st coverage, 110b ... 1st 2 coverage area, 110c ... third coverage area, 110d ... 4th coverage area, 200 ... moving speed estimation device, 210 ... stationary object classification device, 211 ... speed position measurement unit, 212 ... position estimation unit, 213 ... object classification unit , 214 ... storage unit, 220 ... movement speed estimation unit, 300 ... speed presentation device, 400 ... moving body, 500 ... first object, 501 ... first range, 510 ... second object, 511 ... second range, 520 ... 3rd object, 521 ... 3rd range, 530 ... 4th object, 531 ... 4th range, 600 ... 5th object, 602 ... 6th range, 610 ... 6th object, 611 ... 5th range, 612 ... 7th Range, S ... surface

Claims (7)

A velocity position measurement unit that repeatedly measures the relative velocity and the relative position between the object and the radar device based on the output of the radar device that receives the electromagnetic wave reflected by the object;
A position estimation unit that estimates a relative position between the object and the radar apparatus at a plurality of times based on the measured relative velocity and relative position of the object;
An object classifying unit that classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object;
A moving speed estimator that estimates a moving speed of a moving body on which the radar apparatus is mounted, based on a relative speed between the object classified as a stationary object and the radar apparatus;
A moving speed estimation device comprising:   The movement speed estimation apparatus according to claim 1, wherein the position estimation unit estimates a relative position between the object and the radar apparatus based on a Kalman filter.   The moving speed estimation unit estimates a moving speed of a moving body on which the radar device is mounted based on a median of a relative velocity distribution between the object classified as a stationary object and the radar device. The moving speed estimation apparatus according to claim 1 or 2, wherein the moving speed estimation apparatus is characterized.   The moving speed estimation unit estimates a moving speed of a moving body on which the radar device is mounted based on a history of relative speed between the object classified as a stationary object and the radar device. The moving speed estimation apparatus according to any one of claims 1 to 3.   5. The moving speed estimation apparatus according to claim 1, wherein the position estimation unit estimates a relative position between the object and the radar apparatus by an expected value maximization algorithm. . A velocity position measurement unit that repeatedly measures the relative velocity and the relative position between the object and the radar device based on the output of the radar device that receives the electromagnetic wave reflected by the object;
A position estimation unit that estimates a relative position between the object and the radar apparatus at a plurality of times based on the measured relative velocity and relative position of the object;
An object classifying unit that classifies the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object;
A stationary object classification apparatus comprising: A moving speed estimation method in a moving speed estimation device, comprising:
A step of measuring a relative speed and a relative position between the object and the radar apparatus at a plurality of times based on an output of a radar apparatus that receives an electromagnetic wave reflected by the object;
A position estimating unit estimating a relative position between the object and the radar device at a plurality of times based on the measured relative velocity and relative position of the object;
An object classifying unit classifying the object as a stationary object based on a comparison between the estimated relative position of the object and the measured relative position of the object;
A moving speed estimating unit estimating a moving speed of a moving body on which the radar device is mounted based on a relative speed between the object classified as a stationary object and the radar device;
A moving speed estimation method comprising:

Images