JP7074593B2 - Object detector - Google Patents

Description

The present disclosure relates to a technique for detecting an object by a plurality of sensors.

As a technique for detecting an object by a plurality of sensors, for example, in Patent Document 1, the difference in arrival time of radio waves from an object is measured in each of two different combinations of sensors out of three or more sensors, and each of them is measured. A technique for detecting the position of an object based on the difference in the arrival time of a set caused by the difference in the distance between the sensor and the object is described.

When detecting the position of an object based on the difference in arrival time measured by each set of sensors, multiple signals may interfere with each other or noise may be generated in the receiver having the sensor. Multiple different arrival time differences may be measured.

Therefore, in the technique described in Patent Document 1, when a plurality of different arrival time differences are measured by each set of sensors, the radio signals received by other sensors are shifted with respect to the reference sensor by the respective arrival time differences. Calculate the inner product of the shifted radio signals. If the radio signals have the correct arrival time difference, shifting the radio signal by the arrival time difference results in a radio signal that reaches the same time for each set of sensors, so it is larger than the inner product of the radio signals of other arrival time differences. Become a value.

Then, in the technique described in Patent Document 1, the position of an object is to be detected based on the arrival time difference of a combination of radio signals having a large inner product value and a high correlation.

Japanese Unexamined Patent Publication No. 2014-44160

When detecting the position of an object, as in the technique described in Patent Document 1, when detecting the position of an object based on the arrival time difference of radio signals, that is, based on the distance between the sensor and the object, a plurality of sensors If the object exists within the installation range, the position of the intersection of each of the plurality of sensors and the object and the distance can be detected as the position of the object.

On the other hand, when an object exists outside the installation range of multiple sensors, if the distance between the sensors is short with respect to the distance to the object, the distance to the object can be measured with high accuracy, but for the sensor. It is difficult to specify the position of the intersection of the distances from each of the plurality of sensors to the object in the azimuth direction, that is, the angular direction. Therefore, there is a problem that the detection accuracy of the position of the object is lowered.

It is desirable that the present disclosure provide a technique for detecting the position of an object existing outside the installation range of a plurality of sensors with high accuracy.

The object detection device (10, 40, 50) of the present disclosure positions a plurality of objects existing in the detection area (100, 110) outside the installation range (4) in which the plurality of sensors (2) are installed. It is an object detection device that detects based on the distance information between the sensor and the object measured by the sensor at least, and is an information acquisition unit (12), an evaluation unit (20), a peak extraction unit (30), and an object detection unit. (32) and.

The information acquisition unit acquires distance information from a plurality of sensors. Based on the distance information acquired by the information acquisition unit, the evaluation unit ensures that the object exists in each of the plurality of evaluation areas (102, 112, 150, 160, 162, 170, 172) in which the detection area is divided. Set an evaluation value that expresses the uniqueness.

The peak extraction unit extracts an evaluation region having a peak evaluation value with a higher probability that an object exists than the surrounding evaluation region, based on the evaluation value set by the evaluation unit in each of the evaluation regions. The object detection unit determines whether or not an object exists in the evaluation region based on the evaluation value of the evaluation region extracted by the peak extraction unit.

According to the configuration of the present disclosure described above, the detection area outside the installation range in which the plurality of sensors are installed is divided into a plurality of evaluation areas, and the evaluation area is based on the distance information to the object detected by the plurality of sensors. Set an evaluation value that indicates the certainty that an object exists in. Then, an evaluation region having a peak evaluation value with respect to the surrounding evaluation region is extracted.

As a result, even if the object exists in the detection area outside the installation range in which multiple sensors are installed and the difference in distance detected by the multiple sensors is small, the evaluation value of the peak is compared with the surrounding evaluation area. It is possible to determine whether or not an object exists in the evaluation area based on the evaluation value of the evaluation area having. Therefore, it is possible to detect the position of an object existing outside the installation range in which a plurality of sensors are installed with high accuracy.

In addition, the reference numerals in parentheses described in this column and the scope of claims indicate the correspondence with the specific means described in the embodiment described later as one embodiment, and the technical scope of the present disclosure is defined. It is not limited.

The block diagram which shows the object detection apparatus of 1st Embodiment. The schematic diagram which shows the detection method of the object based on the positioning distance. The schematic diagram which shows the detection method of a plurality of objects based on a positioning distance. The schematic diagram which shows an example which divided the detection area into an evaluation area. The schematic diagram which shows the other example which divided the detection area into an evaluation area. The schematic diagram which shows the detection method of the object based on the distance error and the distance variance. The schematic diagram which shows the plurality of partial detection regions of 2nd Embodiment. The block diagram which shows the object detection apparatus of 3rd Embodiment. The schematic diagram which shows the division of the detected evaluation area of an object. The block diagram which shows the object detection apparatus of 4th Embodiment. The schematic diagram which shows an example of the evaluation area of a different size. Schematic diagram showing other examples of evaluation regions of different sizes.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings.
[1. First Embodiment]
[1-1. Constitution]
The object detection device 10 shown in FIG. 1 is mounted on a moving body such as a vehicle and detects the position of an object existing around the moving body. The object detection device 10 acquires distance information between the millimeter wave radar 2 and the object from a plurality of millimeter wave radars 2 as a positioning sensor for measuring the position of the object. Although three millimeter-wave radars 2 are shown in FIG. 1, the number of millimeter-wave radars 2 may be two as long as it is plural, or may be more than three.

As shown in FIG. 2, the millimeter wave radar 2 detects a distance 6 to an object existing outside the installation range 4 in which the millimeter wave radar 2 is installed.
The object detection device 10 is mainly composed of a microcomputer including a CPU, semiconductor memories such as RAM, ROM, and flash memory, and an input / output interface. Hereinafter, the semiconductor memory is also simply referred to as a memory. The object detection device 10 may be equipped with one microcomputer or may be equipped with a plurality of microcomputers.

Various functions of the object detection device 10 are realized by the CPU executing a program stored in a non-transitional substantive recording medium. In this example, the memory corresponds to a non-transitional substantive recording medium in which the program is stored. When the CPU executes this program, the method corresponding to the program is executed.

The object detection device 10 includes an information acquisition unit 12, an evaluation unit 20, a peak extraction unit 30, and an object detection unit 32 as a configuration of functions realized by the CPU executing a program. The method for realizing these elements constituting the object detection device 10 is not limited to software, and a part or all of the elements may be realized by using one or a plurality of hardware. For example, when the above function is realized by an electronic circuit which is hardware, the electronic circuit may be realized by a digital circuit including a large number of logic circuits, an analog circuit, or a combination thereof.

The information acquisition unit 12 acquires distance information obtained by measuring the distance to an object from the millimeter wave radar 2. When the information acquisition unit 12 tries to detect the position of the intersection of distances based on the distance information from the millimeter wave radar 2 to the object, as shown in FIG. 2, the distance to the intersection can be specified, but the millimeter wave. A range 8 in which the intersections overlap in the directional direction, that is, in the angular direction with respect to the radar 2 is generated.

That is, the error in the position of the object is large in the angular direction with respect to the millimeter wave radar 2. If nothing is done, the position of the object cannot be detected with high accuracy.
As shown in FIG. 3, when a plurality of objects actually exist at the positions indicated by “+”, the intersections of distances overlap with the millimeter wave radar 2 in addition to the positions where the objects actually exist. A range arises. Therefore, it is difficult to detect the position where the object exists.

Therefore, in the present embodiment, for example, as shown in FIG. 4, the detection areas 100 are set in a range of 90 ° to the left and right with respect to the front of the vehicle and 50 m from the vehicle, and the detection areas 100 are set at intervals of 10 ° in the angular direction and in the distance direction. The detection area 100 is divided into a plurality of fan-shaped evaluation areas 102 at intervals of 5 m.

In addition to the setting of the detection area 100 and the evaluation area 102 shown in FIG. 4, as shown in FIG. 5, a rectangular detection area 110 of 50 m is set in the forward direction and the left-right direction with respect to the millimeter wave radar 2. The evaluation area 112 divided into a grid pattern at intervals of 5 m may be set.

The size of the evaluation area when the detection areas 100 and 110 are divided into a plurality of evaluation areas is appropriately determined by the detection accuracy of the required position of the object. The smaller the evaluation area, the higher the accuracy of detecting the position of the object. Actually, the size of the evaluation area set by dividing the detection areas 100 and 110 is smaller than the size shown in FIGS. 4 and 5.

The evaluation unit 20 sets an evaluation value indicating the certainty that an object exists in the evaluation area 102 or the evaluation area 112. The evaluation unit 20 includes an error evaluation unit 22 and a dispersion evaluation unit 24 in order to set an evaluation value.

The error evaluation unit 22 calculates the distance error to the object detected by the millimeter wave radar 2 for each of the evaluation areas 102 and 112. Hereinafter, the distance error calculated by the error evaluation unit 22 in the evaluation area 102 shown in FIG. 4 will be described.

First, the number of millimeter-wave radars 2 is Ns, the number of objects is No, the number of divisions of the detection area 100 in the distance direction is Nr, the length of the evaluation area 102 in the distance direction is Δr, and the index of the evaluation area 102 in the distance direction is set. nr = 1, ..., Nr, the number of divisions of the detection area 100 in the angular direction is Np, the angle in the angular direction of the evaluation area 102 is Δp, and the index of the evaluation area 102 in the angular direction is np = 1, ... Np, the index of the millimeter wave radar 2 is n = 1, ..., Ns, the positioning distance for the No. object by the nth millimeter wave radar 2 is Rn = (rn1, ..., rnNo), the nth. Let the coordinates of the millimeter wave radar 2 be LRadar_n = (xn, yn).

The coordinates Lmesh (nr, np) of the evaluation area 102 of the index (nr, np) are expressed by the following equation (1).

そして、各ミリ波レーダ２と各評価領域１０２との距離ｒｍｅｓｈ（ｎｒ、ｎｐ、ｎ）は次式（２）で表される。

The distance rmeth (nr, np, n) between each millimeter-wave radar 2 and each evaluation region 102 is expressed by the following equation (2).

尚、式（２）は、各ミリ波レーダ２のｘｙ座標と各評価領域１０２のｘｙ座標とのそれぞれの差の２乗の和の平方根を求めていることを表している。

The equation (2) represents that the square root of the sum of the squares of the differences between the xy coordinates of each millimeter-wave radar 2 and the xy coordinates of each evaluation area 102 is obtained.

Next, in the evaluation area 102 of the index (nr, np), the distances Rn = (rn1, ..., rnNo) to the plurality of objects detected by the nth millimeter wave radar 2 and the evaluation area 102. The minimum distance error δ (nr, np, n) that minimizes the difference from the distance rmesh (nr, np, n) with the nth millimeter-wave radar 2 is calculated from the following equation (3).

そして、各評価領域１０２において式（３）で算出した最小距離誤差を、すべてのミリ波レーダ２について加算した合計である各評価領域１０２の距離誤差ε（ｎｒ、ｎｐ）は、次式（４）から算出される。

Then, the distance error ε (nr, np) of each evaluation area 102, which is the sum of the minimum distance error calculated by the equation (3) in each evaluation area 102 added for all the millimeter wave radars 2, is the following equation (4). ) Is calculated.

式（４）が示す距離誤差ε（ｎｒ、ｎｐ）の値が小さいほど、該当する評価領域に物体が存在する確からしさが高いことを表している。

The smaller the value of the distance error ε (nr, np) shown in the equation (4), the higher the probability that the object exists in the corresponding evaluation region.

In FIG. 6, which will be described next, the points with high density of the points indicated by “+” represent the points with high probability that the object exists. The upper part of FIG. 6 shows the certainty that an object exists based on the distance error.

In FIG. 6, the probability that the object exists is shown by the density of the points indicated by "+", but the probability that the object exists is displayed as image data by the shade of color or different colors. May be good.

As can be seen from the upper part of FIG. 6, the distance error represented by the equation (4) is highly accurate in the distance direction with respect to the millimeter wave radar 2, but is accurate in the directional direction, that is, in the angular direction with respect to the millimeter wave radar 2. low.
Therefore, the variance evaluation unit 24 uses the following equation (5) to represent the variance of the minimum distance error δ (nr, np, n) calculated by the equation (3) in each evaluation region 102. ) Is calculated. In the equation (5), E (δ (nr, np)) represents the average of the minimum distance errors corresponding to the plurality of radars 2 in each evaluation region 102.

式（５）が示す距離分散σ（ｎｒ、ｎｐ）の値が小さいほど、該当する評価領域１０２に物体が存在する確からしさが高いことを表している。

The smaller the value of the distance variance σ (nr, np) shown in the equation (5), the higher the probability that the object exists in the corresponding evaluation region 102.

As can be seen from the middle stage of FIG. 6, the distance variance represented by the equation (5) indicates that the accuracy in the angular direction is higher than that of the millimeter wave radar 2, but the accuracy in the distance direction is lower than that of the millimeter wave radar 2. ing.
Next, the distance error shown in the upper part of FIG. 6 and the distance variance shown in the middle part of FIG. 6 are added. When adding the distance error and the distance dispersion, in order to suppress erroneous detection of the object, the distance error divides the length Δr of the evaluation area 102 in the distance direction by the number of millimeter wave radars 2. If the value is greater than Δr / Ns, the distance error in the evaluation region 102 is set to infinity.

Further, in each evaluation region 102, when the distance variance is larger than the value Δr / σth obtained by dividing the length Δr in the distance direction of the evaluation region by a predetermined divisor σth, the distance variance in the evaluation region is set to infinity. To. The divisor σth is empirically set according to the degree of suppression of false detection. The larger the divisor σth, the more the false detection of the object can be suppressed, but there are cases where the existing object cannot be detected.

The lower part of FIG. 6 shows the result of using the value obtained by adding the distance error and the distance variance as the evaluation value of the evaluation area 102. In the peak extraction unit 30, among the remaining evaluation regions 102, the evaluation value of the peak whose height of certainty that the object exists is higher than that of the surrounding evaluation regions 102 existing in the front-back distance direction and the left-right angular direction, for example. The evaluation region 102 having the above is extracted from the detection region 100.

In the present embodiment, the peak extraction unit 30 extracts an evaluation region having a peak evaluation value having a lower evaluation value than the surrounding evaluation region 102 from the detection region 100.
It should be noted that weighting may be performed according to the accuracy with which the distance error and the distance variance are emphasized, and then the distance error and the distance variance may be added. For example, if the directional accuracy is more important than the distance accuracy, the distance variance representing the directional accuracy may be made larger than the value calculated from the equation (5), and then the distance error and the distance variance may be added.

Further, since there is a high possibility that an object is erroneously detected in the angular direction rather than the distance direction with respect to the millimeter wave radar 2, the peak extraction unit 30 has the evaluation area 102 having the evaluation value of the peak and the surrounding area for comparing the evaluation value. For the evaluation area 102, it is desirable that the number of evaluation areas 102 in the angular direction is larger than the number of evaluation areas 102 in the distance direction. For example, if the number of evaluation areas 102 in the distance direction is one in the front-rear direction, the number of evaluation areas 102 in the angular direction is two in the left-right direction.

As shown in the lower part of FIG. 6, the object detection unit 32 determines that the object exists in the evaluation region 102 at the position indicated by the dotted circle 120 having the evaluation value of the peak extracted by the peak extraction unit 30.

[1-3. effect]
In the first embodiment described above, the following effects can be obtained.
(1a) As a possibility that an object exists, the accuracy in the distance direction in which the object exists is high but the accuracy in the angular direction is low, and the distance error in the angular direction in which the object exists is high but the accuracy in the distance direction is low. By adding the variance, it is possible to extract a highly accurate evaluation region in which the object exists in both the distance direction and the angular direction.

As a result, the positions of objects existing in the detection areas 100 and 110 outside the installation range 4 in which the plurality of millimeter wave radars 2 are installed are detected with high accuracy based on the detection results of the millimeter wave radar 2 that measures the distance. can.

(1b) In each evaluation region, when the distance error is larger than the value Δr / Ns obtained by dividing the length Δr in the distance direction of the evaluation region by the number of millimeter wave radars 2, infinity is set for the distance error in the evaluation region. When the distance dispersion is larger than the value Δr / σth obtained by dividing the length Δr in the distance direction of the evaluation region by a predetermined divisor σth, the distance dispersion in the evaluation region is set to infinity. As a result, it can be determined that the object does not exist in the evaluation area in which infinity is set, so that erroneous detection of the object can be suppressed.

[2. Second Embodiment]
[2-1. Differences from the first embodiment]
Since the basic configuration of the second embodiment is the same as that of the first embodiment, the differences will be described below. It should be noted that the same reference numerals as those in the first embodiment indicate the same configuration, and the preceding description will be referred to.

As shown in FIG. 7, the detection area 100 is divided into three partial detection areas 130, 132, and 134. The object detection device 10 does not detect an object from the detection area 100 in one object detection process, but sequentially executes the object detection process for each of the partial detection areas 130, 132, and 134.

The shape of the evaluation region generated by dividing each of the partial detection regions 130, 132, and 134 may be either a fan shape shown in FIG. 4 or a grid shape shown in FIG.
The adjacent partial detection area 130 and the partial detection area 132 have an overlapping area 140 in which the areas overlap, and the adjacent partial detection area 132 and the partial detection area 134 have an overlapping area 142 in which the areas overlap.

As shown by the arrow in FIG. 7, the information acquisition unit 12 sequentially acquires the distance information of the object from the millimeter wave radar 2 for each of the partial detection areas 130, 132, and 134, as in the first embodiment.

The peak extraction unit 30 has an evaluation value having a peak evaluation value in which the certainty that the object exists is higher than the surrounding evaluation area, based on the evaluation value obtained by adding the distance error calculated from the acquired distance information and the distance variance. The area is extracted and the extracted result is stored in the memory.

Then, in the next partial detection region, the peak extraction unit 30 extracts an evaluation region having a peak evaluation value in which the certainty that the object exists is higher than that of the surrounding evaluation region, and stores the extracted result in the memory.

When the same evaluation area is extracted as an evaluation area having a peak evaluation value in each of the overlapping areas 140 and 142, the object detection unit 32 evaluates the partial detection areas 130 and 132, respectively, if the overlapping area 140. The value obtained by adding the distance error and the distance variance of the regions is averaged, and if the overlapping region 142, the average value of the values obtained by adding the distance error and the distance variance of the respective evaluation regions of the partial detection regions 132 and 134 is calculated. , The evaluation value of the corresponding evaluation area.

Alternatively, if the overlapping area 140, the object detection unit 32 selects, for example, a small value as one of the values obtained by adding the distance error and the distance variance of the evaluation areas of the partial detection areas 130 and 132, and the overlapping area. If it is 142, the smaller value is selected from the value obtained by adding the distance error and the distance variance of the respective evaluation areas of the partial detection areas 132 and 134, and is used as the evaluation value of the corresponding evaluation area.

Then, the object detection unit 32 determines whether or not an object exists in the corresponding evaluation area based on the evaluation value of the corresponding evaluation area in the detection area 100.
[2-2. effect]
In the second embodiment described above, in addition to the effects (1a) and (1b) of the first embodiment, the following effects (2a) can be obtained.

(2a) Instead of detecting an object existing in the detection area 100 by one object detection process, the detection area 100 is divided into a plurality of partial detection areas 130, 132, and 134, and the detection area 100 is divided into a plurality of partial detection areas 130, 132, and 134. Since the object detection process is sequentially executed, the amount of memory used for detecting the object can be reduced.

Therefore, even if the size of the evaluation area generated by dividing each of the partial detection areas 130, 132, and 134 is smaller than the evaluation areas 102 and 112 of the first embodiment, it is used for detecting the object. The amount of memory can be reduced.

In the second embodiment, the overlapping regions 140 and 142 correspond to the evaluation region of the boundary between the partial detection regions 130, 132 and 134.
[3. Third Embodiment]
[3-1. Differences from the first embodiment]
Since the basic configuration of the third embodiment is the same as that of the first embodiment, the differences will be described below. It should be noted that the same reference numerals as those in the first embodiment indicate the same configuration, and the preceding description will be referred to.

The object detection device 40 of the third embodiment shown in FIG. 8 includes a division portion 42 in addition to the configuration of the object detection device 10 of the first embodiment.
Then, as shown in the upper part of FIG. 9, the detection area 110 of the third embodiment is divided into an evaluation area 150 larger than the evaluation area 112 of the first embodiment.

The division unit 42 divides the evaluation area 150 determined by the object detection unit 32 that an object exists into a plurality of small areas 152 smaller than the evaluation area 150.
The peak extraction unit 30 determines the certainty that the object exists based on the evaluation value obtained by adding the distance error and the distance variance calculated for each of the plurality of small areas 152 of the evaluation area 150 in which the object is detected. A small region 152 having an evaluation value of a peak higher than that of the surrounding evaluation region is extracted.

The object detection unit 32 determines whether or not an object exists in the small area 152 based on the evaluation value of the small area 152 having the evaluation value of the peak extracted by the peak extraction unit 30.
[3-2. effect]
In the third embodiment described above, in addition to the effects (1a) and (1b) of the first embodiment, the following effects (3a) can be obtained.

(3a) For the evaluation region 150 in which the presence of the object is detected in the detection region 100, the object is detected in the small region 152 further divided into the evaluation region 150. As a result, the amount of memory used and the calculation time can be reduced as compared with the case where the detection area 100 is divided into small small areas 152 from the beginning to detect an object.

[4. Fourth Embodiment]
[4-1. Differences from the first embodiment]
Since the basic configuration of the fourth embodiment is the same as that of the first embodiment, the differences will be described below. It should be noted that the same reference numerals as those in the first embodiment indicate the same configuration, and the preceding description will be referred to.

The object detection device 50 of the fourth embodiment shown in FIG. 10 includes a division portion 52 in addition to the configuration of the object detection device 10 of the first embodiment.
As shown in FIGS. 11 and 12, the division unit 52 is based on the distance information measured by the millimeter wave radar 2 acquired by the information acquisition unit 12 before the processing in which the evaluation unit 20 sets the evaluation value of the evaluation area. In addition, in the detection area 110, the areas where the possibility of the presence of an object is low are divided into large evaluation areas 160 and 170, and the areas where the object is likely to exist are the evaluation areas 162 and 172 smaller than the evaluation areas 160 and 170. Divide into.

The object detection unit 32 determines whether or not an object exists in the evaluation regions 160, 162, 170, and 172 based on the evaluation values of the evaluation regions 160, 162, 170, and 172 having the evaluation values of the peaks.

[4-2. effect]
In the fourth embodiment described above, in addition to the effects (1a) and (1b) of the first embodiment, the following effects (4a) can be obtained.

(4a) In the detection region 100, the portion where the possibility of the presence of the object is low is divided into the large evaluation regions 160 and 170, and the portion where the possibility of the presence of the object is high is divided into the small evaluation regions 162 and 172. As a result, the amount of memory used and the calculation time can be reduced as compared with the case where the detection area 100 is divided into small evaluation areas 162 and 172 from the beginning to detect an object.

[5. Other embodiments]
Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments, and can be variously modified and implemented.

(1) In the above embodiment, the millimeter wave radar 2 is used as a positioning sensor for positioning the distance to an object. In addition to the millimeter wave radar 2, LiDAR, sonar, or the like may be used as long as it is a positioning sensor that irradiates an exploration wave to determine the distance to an object.

(2) In the above embodiment, the object detection device may be mounted on a moving body such as a bicycle, a wheelchair, or a robot in addition to the vehicle as the moving body on which the object detection device is mounted.
(3) The object detection device is not limited to a moving object, and may be installed at a fixed position such as a stationary object.

(4) In the above embodiment, the peak extraction unit 30 sets the value obtained by adding the distance error and the distance variance as the evaluation value of the evaluation area, and evaluates the peak with a higher probability that the object exists than the surrounding evaluation area 102. Evaluation areas with values were extracted. On the other hand, as the evaluation value, an evaluation region having a peak in which both the distance error and the distance variance have a higher probability that the object exists than the surrounding evaluation region 102 may be extracted.

(5) In the second embodiment, the evaluation area of the overlapping area where the partial detection areas 130, 132, and 134 obtained by dividing the detection area 100 are overlapped with each other is set as the evaluation area of the boundary between the partial detection areas. On the other hand, the evaluation areas adjacent to each other in which the detection areas are divided and which are adjacent to each other and do not have overlapping areas may be used as the evaluation area of the boundary between the partial detection areas.

(6) In the second embodiment, the evaluation area of the overlapping area where the partial detection areas 130, 132, and 134 obtained by dividing the detection area 100 are overlapped with each other is set as the evaluation area of the boundary between the partial detection areas. On the other hand, based on the positioning distance to the object measured by the millimeter wave radar 2, the front and rear regions including the positioning distance may be used as the partial detection region. For example, if the positioning distances are 10 m, 40 m, and 100 m, a range of 5 m before and after the positioning distance may be used as a partial detection area.

However, it is desirable to set a partial detection area having a width in the front-rear direction that is greater than or equal to the maximum interval among the installation intervals of the plurality of millimeter-wave radars 2. For example, if the maximum interval among the installation intervals of the plurality of millimeter wave radars 2 is 2 m, a partial detection area of ± 2 m or more is set.
(7) In the fourth embodiment, the division unit 52 determines a position to generate a large and small evaluation region based on the distance information measured by the millimeter wave radar 2.

On the other hand, the dividing unit 52, for example, in order to detect the position of an object existing on the road on which the own vehicle travels, before the information acquisition unit 12 acquires the distance information from the millimeter wave radar 2, the own vehicle Based on the position and the map data of the navigation device, the evaluation area of the range of the road on which the own vehicle travels may be made smaller, and the evaluation area of the range other than the road may be made larger than the evaluation area of the range of the road.

(8) A plurality of functions possessed by one component in the above embodiment may be realized by a plurality of components, or one function possessed by one component may be realized by a plurality of components. Further, a plurality of functions possessed by the plurality of components may be realized by one component, or one function realized by the plurality of components may be realized by one component. Further, a part of the configuration of the above embodiment may be omitted. Further, at least a part of the configuration of the above embodiment may be added or replaced with the configuration of the other above embodiment. It should be noted that all aspects included in the technical idea specified only by the wording described in the claims are embodiments of the present disclosure.

(9) In addition to the above-mentioned object detection devices 10, 40, 50, a system having the object detection devices 10, 40, 50 as components, and object detection for operating a computer as the object detection devices 10, 40, 50. The present disclosure can also be realized in various forms such as a program, a recording medium on which this object detection program is recorded, and an object detection method.

2: Millimeter wave radar (sensor), 4: Installation range, 10, 40, 50: Object detection device, 12: Information acquisition unit, 20: Evaluation unit, 22: Error evaluation unit, 24: Dispersion evaluation unit, 30: Peak Extraction unit, 32: Object detection unit, 42, 52: Division unit, 100, 110: Detection area, 102, 112, 150, 160, 162, 170, 172: Evaluation area, 130 to 134: Partial detection area, 140, 142: Overlapping area (evaluation area of boundary), 152: Small area

Claims (4)

Distance information between the sensor and the object that the plurality of sensors at least measure the position of the object existing in the detection area (100, 110) outside the installation range (4) in which the plurality of sensors (2) are installed. An object detection device (10, 40, 50) that detects based on
An information acquisition unit (12) configured to acquire the distance information from the plurality of sensors, and
Certainly, the object exists in each of the plurality of evaluation regions (102, 112, 150, 160, 162, 170, 172) in which the detection region is divided based on the distance information acquired by the information acquisition unit. An evaluation unit (20) configured to set an evaluation value that expresses the uniqueness, and
Based on the evaluation value set by the evaluation unit in each of the evaluation regions, a peak configured to extract the evaluation region having the evaluation value of the peak having a higher probability than the surrounding evaluation region. Extraction unit (30) and
An object detection unit (32) configured to determine whether or not the object is present in the evaluation region based on the evaluation value of the evaluation region extracted by the peak extraction unit.
Equipped with
The evaluation unit
In each of the evaluation regions, the minimum distance error that minimizes the difference between the distance between each sensor of the plurality of sensors and the object and the distance between the evaluation region and each sensor is calculated, and the minimum distance error is calculated for each sensor. An error evaluation unit (22) configured to calculate the total of the corresponding minimum distance errors and use it as an error evaluation value in the evaluation area.
In each of the evaluation regions, the variance evaluation unit (24) configured to calculate the variance of the minimum distance error corresponding to the plurality of sensors calculated by the error evaluation unit and use it as the variance evaluation value of the evaluation region. )When,
Equipped with
The peak extraction unit has the evaluation value of the peak based on the error evaluation value calculated by the error evaluation unit and the dispersion evaluation value calculated by the dispersion evaluation unit as the evaluation value. Is configured to extract,
Object detector. The object detection device according to claim 1 .
The detection area is divided into a plurality of partial detection areas divided into the plurality of evaluation areas.
The evaluation unit is configured to sequentially set the evaluation value of the evaluation area in each of the plurality of partial detection areas.
The peak extraction unit is configured to sequentially extract the evaluation region having the evaluation value of the peak based on the evaluation value set by the evaluation unit in each of the partial detection regions.
Object detector. The object detection device according to claim 2 .
When the object detection unit has the evaluation value of the peak in each of the evaluation regions at the boundary between the partial detection regions that are adjacent to each other or partially overlap each other, the object detection unit is one of the evaluation regions of the boundary. The evaluation value is selected, or the average value of the evaluation values in the evaluation area at the boundary is set as the evaluation value.
Object detector. The object detection device according to any one of claims 1 to 3 .
The evaluation region (150) having the peak extracted by the peak extraction unit is further provided with a division unit (42, 52) configured to divide the evaluation region (150) into a plurality of smaller small regions (152).
In the evaluation region having a peak
The information acquisition unit is configured to acquire the distance information from the plurality of sensors, and the evaluation unit sets the evaluation value in each of the plurality of small regions based on the distance information. It is composed and
The peak extraction unit is configured to extract the small region having the evaluation value of the peak having a higher probability than the surrounding small region based on the evaluation value in each of the small regions. Ori,
The object detection unit is configured to determine whether or not the object is present in the small region based on the evaluation value of the small region extracted by the peak extraction unit.
Object detector.

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