Axis deviation estimating device

Abstract

To enhance estimation accuracy of an axis deviation angle by suppressing estimation under a condition that estimation variation of the axis deviation angle becomes large in an axis deviation estimation device.SOLUTION: The off-axis estimation device estimates an off-axis angle of a radar device mounted on a moving body, and includes a speed acquiring unit S120 that acquires a speed of the moving body, a stationary object extracting unit S130 that extracts a stationary object from among objects detected by the radar device, an off-axis angle estimating unit S160 that estimates the off-axis angle by using an azimuth angle dependency of a relative speed with respect to the extracted stationary object, and an estimation execution determining unit S150 that determines whether or not to execute estimation of the off-axis angle by the off-axis angle estimating unit.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to an axis shift estimation device that estimates an axis shift of a radar device. [Background technology]

[0002] In a radar device mounted on a vehicle, the central axis of the radar beam may shift due to changes in the installation state for some reason. When this axis shift occurs, the detection accuracy of the object being detected by the radar device decreases.

[0003] Therefore, as described in Patent Document 1, it has been proposed that in a radar device, the horizontal and vertical axis deviation angles of the radar device are estimated by utilizing the azimuth angle dependency of the relative velocity based on the relative velocity and azimuth angle observed for multiple reflection points of a stationary object. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2018-54315 Summary of the Invention [Problem to be solved by the invention]

[0005] However, when the axis deviation estimation technology described in Patent Document 1 is applied to a radar device that detects objects present to the side of a vehicle, the path of the radar wave between the vehicle and a stationary object may be blocked by a moving object moving around the vehicle. In this case, the number of stationary objects used to estimate the axis deviation angle may be uneven above, below, left, and right of the central axis of the radar beam, resulting in a problem of large variation in the estimated axis deviation angle.

[0006] An object of one aspect of the present disclosure is to improve the accuracy of estimating an axis deviation angle in an axis deviation estimation device by suppressing estimation under conditions that result in large variations in the estimation of the axis deviation angle. [Means for solving the problem]

[0007] An axis deviation estimation device according to one aspect of the present disclosure estimates an axis deviation angle of a radar device (2) mounted on a moving object (20) and configured to detect object information, including the relative speed and azimuth angle, of objects present in a detection area around the moving object based on transmitted and received radar waves. The axis deviation estimation device according to the present disclosure includes a speed acquisition unit (S120) that acquires the speed of the moving object, a stationary object extraction unit (S130), an axis deviation angle estimation unit (S160), and an estimation execution determination unit (S150, S152, S154, S156).

[0008] The stationary object extraction unit extracts stationary objects from among the objects present in the detection area based on the relative speed and azimuth angle of the object detected by the radar device and the speed of the moving body acquired by the speed acquisition unit.

[0009] The axis deviation angle estimator estimates the axis deviation angle of the radar device by utilizing the azimuth angle dependency of the relative velocity with respect to the stationary object extracted by the stationary object extractor. The estimation execution determination unit determines whether or not to execute estimation of the axis deviation angle by the axis deviation angle estimation unit, depending on the distribution or number of stationary objects for each azimuth angle extracted by the stationary object extraction unit.

[0010] In other words, the reason why the estimated variation in axis deviation angle increases due to the influence of moving objects around the moving body is because the distribution of the azimuths of stationary objects detected within the detection area is biased. This bias can be estimated from the distribution or number of stationary objects for each azimuth angle.

[0011] Therefore, in the axis misalignment estimation device of the present disclosure, whether or not to perform axis misalignment angle estimation by the axis misalignment angle estimator is determined according to the distribution or number of stationary objects for each azimuth angle. Thus, according to the axis misalignment estimation device of the present disclosure, when the estimation variation becomes large due to a bias in the stationary objects used in the axis misalignment angle estimation, the axis misalignment angle estimation is not performed, thereby suppressing the variation in the axis misalignment angle estimation and improving the accuracy of the axis misalignment angle estimation.

[0012] The symbols in parentheses above indicate a correspondence with specific means described in the embodiments described below as one aspect, and do not limit the technical scope of the present disclosure. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a block diagram showing a configuration of a vehicle control system according to a first embodiment. [Figure 2] 4 is a flowchart illustrating an axis deviation estimation process according to the first embodiment. [Figure 3] 1 is an explanatory diagram showing the relationship between the beam direction of a radar device, the moving direction of a vehicle, and the direction in which a reflection point detected by the radar device exists; [Figure 4] This is an explanatory diagram showing the possible values ​​of a reflection point vector, the observed value of a stationary reflection point, and the relationship between the W-axis coordinate of a three-dimensional coordinate system and the relative speed of the reflection point. [Figure 5] FIG. 10 is an explanatory diagram illustrating the reason why an estimation error occurs in a radar device on the side of a vehicle. [Figure 6] FIG. 10 is an explanatory diagram showing the results of estimating axis misalignment while actually running a vehicle, in comparison with a conventional device. [Figure 7] 10 is an explanatory diagram showing the estimation results obtained when the axis deviation angle in the vertical direction is set to a predetermined value, in comparison with those of a conventional device. FIG. [Figure 8] 10 is a flowchart illustrating a first modified example of the axis shift estimation process of the first embodiment. [Figure 9] 10 is a flowchart illustrating a second modified example of the axis shift estimation process of the first embodiment. [Figure 10] 10 is a flowchart illustrating an axis shift estimation process according to a second embodiment. [Figure 11] 10 is a flowchart illustrating an axis shift estimation process according to a third embodiment. [Figure 12] 10 is a flowchart illustrating an axis deviation estimation process according to a fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. [First embodiment] 1 is a system mounted on a vehicle, which is a moving body, and includes a radar device 2, an on-board sensor group 4, a mounting angle adjustment device 6, and a control device 10. Hereinafter, the vehicle on which the vehicle control system 1 is mounted is also referred to as the host vehicle. Furthermore, the direction parallel to the road surface on which the vehicle is traveling is also referred to as the horizontal direction, and the height direction of the vehicle is also referred to as the vertical direction.

[0015] The radar device 2 is a well-known device that emits radar waves within a predetermined angular range, receives the reflected waves, and generates reflection point information regarding the reflection points that reflect the radar waves. Note that the radar device 2 may be a so-called millimeter-wave radar that uses electromagnetic waves in the millimeter wave band as radar waves, a laser radar that uses laser light as radar waves, or a sonar that uses sound waves as radar waves. In any case, the antenna unit that transmits and receives the radar waves is configured to be able to detect the arrival direction of the reflected waves in both the horizontal and vertical directions.

[0016] 5, the radar device 2 is installed on the front left side of the vehicle 20 so that the beam direction, which is the central axis direction of the irradiated radar beam (the direction of 0 degrees shown in FIG. 5), is aligned in a predetermined direction to the side of the vehicle 20. The radar device 2 is also arranged so that the detection area of ​​the reflection point includes the forward direction along the straight-ahead direction of the vehicle 20 and the lateral direction perpendicular to the straight-ahead direction.

[0017] The radar device 2 may be installed on the front right side of the vehicle 20, on the rear left side of the vehicle 20, on the rear right side of the vehicle 20, in front of the vehicle 20, or behind the vehicle 20.

[0018] The reflection point information generated by the radar device 2 includes at least the horizontal and vertical angles at which the reflection points S1, S2, S3, ... are located, determined based on the beam direction, and the relative speed with respect to the reflection points S1, S2, S3, ....

[0019] The on-board sensor group 4 is a group of various sensors mounted on the vehicle to detect the state of the vehicle. Here, the sensors constituting the on-board sensor group 4 include at least a vehicle speed sensor that detects the vehicle speed based on the rotation of the wheels.

[0020] The control device 10 is mainly configured with a well-known microcomputer including a CPU 12 and memories such as a ROM 14 and a RAM 16. The functions of the control device 10 are realized by the CPU 12 executing a program stored in a non-transitory tangible recording medium. Memories such as the ROM 14 correspond to the non-transitory tangible recording medium storing the program.

[0021] The mounting angle adjustment device 6 includes an actuator configured by combining a motor, gears, etc., and the actuator can adjust the mounting angle of the radar device 2 on the vehicle 20, and therefore the emission direction of the radar beam.

[0022] The processes executed by the control device 10 include at least a target recognition process and an axis deviation estimation process. Of these, the target recognition process is a well-known process that detects the lane in which the vehicle is traveling, a preceding vehicle traveling in the same lane as the vehicle, other vehicles, obstacles, etc., based on reflection point information obtained from the radar device 2 and various information obtained from the on-board sensors 4.

[0023] The processing results of this target recognition processing are used for driving assistance of the host vehicle 20. The on-vehicle equipment used for driving assistance includes a monitor that displays various images and an audio device that outputs warning sounds and guidance voices. This on-vehicle equipment may also include a control device that controls the internal combustion engine and motor that serve as the power source of the host vehicle, a powertrain mechanism, a brake mechanism, etc.

[0024] On the other hand, the axis shift estimation process is a process for detecting the axis shift angle of the radar device 2. Therefore, the control device 10 functions as an axis shift estimation device by executing the axis shift estimation process. The axis deviation estimation process executed by the control device 10 will be described below with reference to the flowchart in FIG. 2. This process is started for each measurement cycle in which radar waves are transmitted and received. The principle of estimating the axis deviation angle by the axis deviation estimation process of this embodiment is the same as that described in Patent Document 1. Therefore, except for the processes of S140 and S150 in FIG. 2, the process is executed in the same procedure as that described in Patent Document 1.

[0025] 2, when the axis shift estimation process is started, the control device 10 first acquires reflection point information from the detection results by the radar device 2 as object information around the host vehicle in S110, and then proceeds to S120. In the following description, the reflection points identified from the reflection point information are referred to as acquired reflection points.

[0026] Next, in S120, the radar device 2 executes processing as a speed acquisition unit, acquiring vehicle information, at least the host vehicle speed Cm, from the on-board sensor group 4. Then, in S130, the radar device 2 executes processing as a stationary object extraction unit, extracting stationary objects from among the reflection points detected by the radar device 2, based on the relative speeds and azimuth angles of the reflection points included in the reflection point information acquired in S110 and the host vehicle speed Cm acquired in S120.

[0027] That is, in S130, first, coordinate conversion is performed for each of the acquired reflection points based on the reflection point information acquired in S110. Specifically, as shown in Fig. 3, the horizontal angle included in the reflection point information is defined as Hor, and the vertical angle is defined as Ver, and the three-dimensional coordinates (u, v, w) are calculated using equations (1) to (3).

[0028]

number

[0029] In equation (1), θmount represents the design value of the mounting angle of the radar device 2 with respect to the vehicle 20. In other words, in this embodiment, the radar device 2 is a side radar that emits radio waves to the side of the vehicle 20, and since the beam direction does not coincide with the vehicle traveling direction, the reference axis of the angle u needs to be set to the vehicle traveling direction from the front of the radar device 2. For this reason, in equation (1), the angle (design value) of the front of the radar device 2 with respect to the vehicle traveling direction is set as the mounting angle θmount, and the horizontal angle Hor included in the reflection point information is corrected to find the coordinate u. Then, using the vehicle speed Cm acquired in S120, the relative speed included in the reflection point information as q, and a preset threshold as ε, the acquired reflection points that satisfy the formula (4) are extracted as stationary reflection points.

[0030]

number

[0031] In other words, a reflection point where the left side of equation (4) is 0 is considered to be a stationary reflection point. However, the vehicle speed Cm acquired from the on-board sensor group 4 does not necessarily match the actual vehicle speed due to wheel slippage, etc., and when the beam direction and the traveling direction of the vehicle are misaligned, the relative speed q detected by the radar device 2 also changes in accordance with the misalignment. For this reason, even if the reflection point is a stationary reflection point, the left side of equation (4) may not necessarily be 0. Therefore, in S130, a threshold value ε is used to extract stationary reflection points.

[0032] Once the stationary reflection point is extracted in this manner, in S160, the axis deviation angle of the radar device 2 is estimated using the azimuth angle dependency of the relative velocity with respect to the stationary reflection point. That is, in S160, a unit vector ep (hereinafter referred to as traveling direction vector) representing the actual traveling direction of the host vehicle 20 and the actual host vehicle speed Cp are estimated using equation (5). Note that Cp is a scalar. Q is a column vector in which the relative velocities q of K stationary reflection points are arranged in order, and is expressed by equation (6). E is a matrix in which the reflection point vectors of K stationary reflection points, represented by row vectors, are arranged in order in the column direction, and is expressed by equation (7). ep is a column vector in which the horizontal component up, vertical component vp, and beam direction component wp are arranged, and is expressed by equation (8). However, |ep|=1.

[0033]

number

[0034] In other words, equation (5) represents K simultaneous equations with the components of Cp and ep as unknown parameters, and Cp and ep can be found by solving this simultaneous equation. Note that ep is composed of three components, but any two of them can be derived from the others. Therefore, the number of unknown parameters that actually need to be found is three in total, including Cp. Therefore, three or more stationary reflection points are required to solve equation (5). Furthermore, specific methods for solving simultaneous equations are well known, so explanations will be omitted here. As an example, the least squares method or the like can be used, but the method is not limited to this.

[0035] FIG. 4 is a graph showing the range in which reflection point vectors (u, v, w) exist (i.e., on the hemisphere in the figure). However, the w-axis has been scaled to represent the relative speed q. Specifically, the host vehicle speed Cm is set to w=1. When the u, v, and q of stationary reflection points are plotted on the coordinate system shown in FIG. 4, if there is no axial misalignment in the radar device 2 and the beam direction and traveling direction are aligned, the stationary reflection points will be plotted on the hemisphere. Solving the above simultaneous equations is equivalent to finding the traveling direction vector and host vehicle speed such that all stationary reflection points are plotted on the hemisphere.

[0036] Then, in S160, the horizontal axis deviation angle ΔH and the vertical axis deviation angle ΔV of the beam direction of the radar device 2 are calculated using equations (9) and (10) based on the horizontal component up and the vertical component vp of the traveling direction vector ep estimated as described above.

[0037]

number

[0038] In this way, when the horizontal and vertical axis deviation angles ΔH and ΔV of the beam direction of the radar device 2 are calculated in S160, the process proceeds to S170, where it is determined whether or not at least one of the calculated axis deviation angles ΔH and ΔV is greater than a threshold value for determining the axis deviation.

[0039] If it is determined in S170 that at least one of the axis deviation angles ΔH, ΔV is greater than the threshold, the mounting angle of the radar device 2 needs to be corrected, and the process proceeds to S180. In S180, diagnostic information indicating that an axis deviation has occurred in the radar device 2 is output to the outside, and the axis deviation estimation process ends. If it is determined in S170 that the axis deviation angles ΔH, ΔV are equal to or less than the threshold, the process proceeds to S110, and the above series of processes are executed again.

[0040] As described above, in the control device 10 of this embodiment, the axis deviation of the radar device 2 installed on the front left side of the vehicle 20 is estimated by utilizing the azimuth angle dependency of the relative speed with respect to the stationary reflection points S1, S2, S3, ... present around the vehicle 20.

[0041] Therefore, as shown in FIG. 5, when the radar wave from the radar device 2 is blocked by another vehicle 30 traveling in a different lane from the vehicle 20, the axis deviation angle cannot be estimated using the stationary reflection points (shown by circles in FIG. 5) located outside the other vehicle 30.

[0042] In this case, the radar waves received by the radar device 2 from the stationary reflection points S1, S2, S3, ... are not dispersed across the central axis of the radar beam, but are biased. When such a bias occurs, the estimated values ​​of the axis deviation angle periodically estimated by the control device 10 vary greatly, as shown in the left column of Fig. 6, and the estimation accuracy of the axis deviation angle decreases.

[0043] Therefore, in this embodiment, as shown in Fig. 2, once stationary reflection points S1, S2, S3, ... are extracted in S130 in the axis shift estimation process, the process proceeds to S140. Then, in S140, it is identified to which azimuth zones divided at predetermined angles (every 20 degrees in Fig. 5) from the central axis of the radar beam the directions of the stationary reflection points S1, S2, S3, ... extracted in S130 belong, and the number of stationary reflection points S1, S2, S3, ... is calculated for each azimuth zone.

[0044] Next, in S150, it is determined whether the number of azimuth regions where the number of stationary objects calculated in S140 is equal to or less than a predetermined value (for example, 0) is less than a preset threshold value. If the number of azimuth regions where the number of stationary objects is equal to or less than the predetermined value is less than the threshold value, it is determined that the stationary reflection points S1, S2, S3, ... are distributed in each azimuth region and that the estimation error of the axis deviation angle can be suppressed, and the process proceeds to S160.

[0045] On the other hand, if the number of azimuth regions where the number of stationary objects is equal to or less than the predetermined value is equal to or greater than the threshold value, it is determined in S150 that the stationary reflection points S1, S2, S3, ... are concentrated in a specific azimuth region and the estimation error of the axis deviation angle will be large, and the process proceeds to S110 without executing the estimation process of S160. Note that the processes of S140 and S150 correspond to the estimation execution determination unit of the present disclosure.

[0046] In this way, according to the axis deviation estimation process of this embodiment, when a moving object is present within a short distance of the radar device 2 and the distribution of the azimuths of the stationary reflection points S1, S2, S3, ... is biased due to the influence of the moving object, it is possible to avoid estimating the axis deviation angle.

[0047] Therefore, according to the axis deviation estimation process of this embodiment, as shown in the right column of FIG. 6, it is possible to suppress the increase in the estimated variation in the axis deviation angle due to the influence of moving objects around the host vehicle 20, and to improve the estimation accuracy of the axis deviation angle.

[0048] 7 shows the results of an experiment in which the axis deviation angle was estimated using a radar device 2 with the axis deviation angle in the vertical direction set to 0 degrees, -6 degrees, and +6 degrees. As is clear from FIG. 7, the experiment results confirm that, regardless of the axis deviation angle of the radar device 2, the present embodiment can reduce the variation in the estimated axis deviation angle compared to conventional devices.

[0049] [First Modification] 2, the axis deviation estimation process identifies to which of the azimuth regions divided into predetermined angles the directions of the still reflection points S1, S2, S3, ... extracted in S130 belong, and calculates the number of still reflection points S1, S2, S3, ... for each azimuth region. If the number of azimuth regions in which the calculated number of still reflection points S1, S2, S3, ... is equal to or less than a predetermined value is less than a threshold, it is determined that the still reflection points S1, S2, S3, ... are distributed in each azimuth region, and an estimation of the axis deviation angle is carried out.

[0050] However, this method of determining the distribution of the orientations of stationary reflection points S1, S2, S3, ... is just one example, and in the axis deviation estimation process of the first modified example, the distribution of the orientations of the stationary objects extracted in S130 is calculated in S142, as shown in Fig. 8. Then, in S152, it is determined from the calculation result of the orientation distribution whether or not there is any bias in the distribution of the orientations of the stationary objects, and if there is no bias in the distribution of the orientations of the stationary objects, the process proceeds to S160. Even in this way, the same effect as in the above embodiment can be obtained.

[0051] Furthermore, in the first modified example, once the axis deviation angle of the radar device 2 is estimated in S160, the process proceeds to S165, where the estimation reliability of the estimated axis deviation angle is calculated. This estimation reliability is set, for example, by finding the variance of the axis deviation angle repeatedly calculated in S160, and the smaller the variance, the higher the reliability. The process of S165 corresponds to the reliability calculation unit of the present disclosure.

[0052] Then, in the following S175, it is determined whether the axis deviation angle estimated in S160 is greater than a threshold value and whether the estimation reliability of the axis deviation angle calculated in S165 is greater than a threshold value. If both the axis deviation angle and the estimation reliability are greater than a threshold value, the process proceeds to S180.

[0053] As a result, even if the axis deviation angle estimated in S160 is larger than the threshold, if the estimation reliability is low, the process proceeds to S110 and the processes from S110 onwards can be executed. Therefore, if the estimation reliability of the axis deviation angle is low and the axis deviation angle estimation result is unreliable, it is possible to prevent axis deviation diagnostic information from being output from the radar device 2 and to prevent the object detection function of the radar device 2 from being stopped. Furthermore, if the estimation reliability of the axis deviation angle is high, it is possible to output axis deviation diagnostic information and adjust the emission direction of the radar beam of the radar device 2, thereby preventing the object detection function of the radar device 2 from being impaired.

[0054] [Second Modification] In the axis deviation estimation processing of the first embodiment and the first modified example described above, the processing of S140 and S150 or S142 and S152 is executed regardless of whether or not a moving object such as another vehicle 30 is present around the host vehicle 20. However, the function of the estimation execution determination unit realized by these processing steps is effective when a moving object that may cause an estimation error in the axis deviation angle is present around the host vehicle 20, and does not have to function when no moving object is present.

[0055] 9, in the axis shift estimation process of the second modified example, when stationary reflection points that are stationary objects are extracted from the reflection points detected by the radar device 2 in S130, the process proceeds to S132. In S132, the reflection points of moving objects are extracted from the reflection points detected by the radar device 2, excluding the stationary reflection points, thereby extracting moving objects that are not stationary objects.

[0056] Next, in S134, it is determined whether or not there is a moving object whose distance from the host vehicle 20 (more specifically, the radar device 2) is within a predetermined distance range among the moving objects extracted in S132, that is, whether or not there is a moving object within a short distance around the host vehicle 20. If it is determined in S134 that there is a moving object within a short distance, the process proceeds to S142, and if it is determined in S134 that there is no moving object within a short distance, the process proceeds to S160.

[0057] As a result, the processes of S142 and S152 functioning as an estimation execution determination unit are executed only when a moving object is present within the close range, and when no moving object is present within the close range, the axis deviation angle can be estimated in S160 without executing the processes of S142 and S152. As a result, by executing the processes of an estimation execution determination unit when no moving object is present within the close range, it is possible to prevent a long time from elapsed until the axis deviation angle estimation process in S160 is executed. As a result, it is possible to prevent an increase in the time required for the axis deviation angle estimation to converge and an increase in the processing load.

[0058] The axis misalignment estimation process shown in FIG. 9 is obtained by adding the processes of S132 and S134 to the axis misalignment estimation process of the first modified example. However, the same effect as above can be obtained by adding the processes of S132 and S134 to the axis misalignment estimation process of the first embodiment shown in FIG. 2 as well.

[0059] [Second embodiment] In the axis deviation estimation process of the first embodiment, the distribution of the azimuths of the stationary reflection points S1, S2, S3, ... is calculated from the number of each azimuth region, and it is determined whether there is any bias in the distribution of the stationary reflection points, thereby determining whether to estimate the axis deviation angle.

[0060] In contrast to this, in the second embodiment, as shown in Fig. 10, after the processing of S130 in the axis shift estimation process, the dispersion of the orientations of the stationary reflection points S1, S2, S3, ... is calculated in S144. Then, in S154, it is determined whether or not the orientation dispersion calculated in S144 is larger than a preset threshold value, in other words, whether or not the orientation dispersion is sufficiently large. If the orientation dispersion is sufficiently large, the process proceeds to S160, and if the orientation dispersion is not sufficiently large, the process proceeds to S110.

[0061] The axis misalignment estimation process shown in Fig. 10 is obtained by executing the processes of S144 and S154 instead of the processes of S142 and S152 in the axis misalignment estimation process shown in Fig. 8. Therefore, the processes of S144 and S154 shown in Fig. 10 function as an estimation execution determination unit of the present disclosure.

[0062] As described above, in the second embodiment, the estimation execution determination unit calculates the azimuth dispersion of the still reflection points S1, S2, S3, ..., and when the azimuth dispersion is equal to or less than a threshold value, estimation of the axis deviation angle is not performed. Even in this way, the same effect as in the first embodiment can be obtained. Furthermore, in this embodiment, instead of counting the number of extracted still reflection points S1, S2, S3, ... for each azimuth, as in the first embodiment, the azimuth dispersion is calculated using a predetermined formula, and therefore the processing load on the estimation execution determination unit can be reduced.

[0063] [Third embodiment] In the axis deviation estimation process of the first and second embodiments, a determination is made as to whether or not to estimate the axis deviation angle by finding the distribution or variance of the orientations of the stationary reflection points S1, S2, S3, .... However, in the axis deviation estimation process, if the number of stationary reflection points S1, S2, S3, ... extracted in S130 is sufficiently large, the variation in the axis deviation angle estimated in S160 is suppressed.

[0064] 11, in the axis shift estimation process, after the process of S130, the total number of stationary reflection points S1, S2, S3, ... extracted in S130 is calculated in S146. Then, in S156, it is determined whether or not the total number calculated in S146 is larger than a preset threshold value, in other words, whether or not the total number is sufficiently large. If the total number is sufficiently large, the process proceeds to S160, and if the total number is small, the process proceeds to S110.

[0065] The axis misalignment estimation process shown in Fig. 11 is obtained by executing the processes of S146 and S156 instead of the processes of S142 and S152 in the axis misalignment estimation process shown in Fig. 8. Therefore, the processes of S146 and S156 shown in Fig. 11 function as an estimation execution determination unit of the present disclosure.

[0066] As described above, in the third embodiment, the estimation execution determination unit calculates the total number of still reflection points extracted in S130, and if the total number is small, estimation of the axis deviation angle is not performed, but even in this case, the same effects as in the first and second embodiments can be obtained. Also, in this embodiment, it is only necessary to find the total number of still reflection points extracted in S130, so the processing load on the estimation execution determination unit can be reduced compared to the first and second embodiments.

[0067] [Fourth embodiment] In the first to third embodiments, the threshold value serving as the determination condition used to determine whether or not to estimate the axis deviation angle in the determination process (S150, S152, S154, S156) of the estimation execution determination unit has been described as a preset fixed value.

[0068] In contrast to this, in the fourth embodiment, this determination condition is set according to the estimation reliability calculated in S165 as a reliability calculation section in the axis deviation angle estimation process shown in FIGS.

[0069] Specifically, as shown in FIG. 12, in the axis shift estimation process shown in FIG. 8, after the distribution of stationary reflection points is obtained in S142, in S148, the judgment condition used to judge the bias of the distribution in S152 is set according to the estimation reliability calculated previously in S165.

[0070] That is, in S148, when the estimation reliability is low and the variance in the axis deviation angle estimation results is large, the determination conditions are updated so that it becomes more difficult to estimate the axis deviation angle in S160. By doing so, the variation in the axis deviation angle estimated in S160 falls within a predetermined range, and the accuracy of estimating the axis deviation angle can be improved.

[0071] The axis misalignment estimation process shown in FIG. 12 corresponds to the axis misalignment estimation process shown in FIG. 8. However, the axis misalignment estimation process shown in FIGS. 9 to 11, which includes the process of the reliability calculation unit (S165), can also achieve the same effect as above by adding the same process as S148.

[0072] [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 implemented in various modified forms.

[0073] For example, the axis offset estimation apparatus and method of the present disclosure may be realized by a special-purpose computer configured by configuring a processor and memory programmed to execute one or more functions embodied in a computer program. Alternatively, the axis offset estimation apparatus and method described in the present disclosure may be realized by a special-purpose computer configured by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the axis offset estimation apparatus and method of the present disclosure may be realized by one or more special-purpose computers configured by combining a processor and memory programmed to execute one or more functions with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored in a computer-readable non-transitory tangible recording medium as instructions to be executed by a computer. The method for realizing the functions of each unit included in the axis offset estimation apparatus of the present disclosure does not necessarily need to include software, and all of the functions may be realized using one or more hardware components.

[0074] In each of the above embodiments, multiple functions of one component may be realized by multiple components, or one function of one component may be realized by multiple components. Furthermore, multiple functions of multiple components may be realized by one component, or one function realized by multiple components may be realized by one component. Furthermore, part of the configuration of the above embodiments may be omitted. Furthermore, at least part of the configuration of the above embodiments may be added to or substituted for the configuration of another of the above embodiments.

[0075] In addition to the axis misalignment estimation device described above, the present disclosure can also be realized in various other forms, such as a system including the axis misalignment estimation device as a component thereof, a program for causing a computer to function as the axis misalignment estimation device, a non-transient tangible recording medium such as a semiconductor memory on which the program is recorded, and an axis misalignment estimation method. [Explanation of symbols]

[0076] 2... radar device, 4... on-vehicle sensor group, 10... control device, 12... CPU, 14... ROM, 16... RAM, 20... host vehicle.

Claims

1. An axis shift estimation device for estimating an axis shift angle of a radar device (2) mounted on a moving body (20) and detecting object information including a relative speed and an azimuth angle of an object present in a detection area around the moving body based on transmitted and received radar waves, comprising: a speed acquisition unit (S120) configured to acquire the speed of the moving object; a stationary object extraction unit (S130) configured to extract stationary objects from among the objects present in the detection area based on the relative speed and the azimuth angle of the object detected by the radar device and the speed of the moving object acquired by the speed acquisition unit; an axis deviation angle estimation unit (S160) configured to estimate the axis deviation angle of the radar device by utilizing the azimuth angle dependency of the relative velocity with respect to the stationary object extracted by the stationary object extraction unit; an estimation execution determination unit (S150, S152, S154, S156) configured to determine whether or not to execute estimation of the axis deviation angle by the axis deviation angle estimation unit, depending on the distribution or number of the stationary objects for each azimuth angle extracted by the stationary object extraction unit; An axis deviation estimation device comprising:

2. 2. The axis deviation estimation device according to claim 1, the radar device is configured to detect a distance to the object in addition to the relative velocity and the azimuth angle as the object information, the estimation implementation determination unit is configured to determine whether or not the non-stationary moving object is present within a predetermined distance range based on the object information detection result by the radar device, and, if the moving object is present within the predetermined distance range, to determine whether or not to implement estimation of the axis deviation angle by the axis deviation angle estimation unit, and, if the moving object is not present within the predetermined distance range, to implement estimation of the axis deviation angle by the axis deviation angle estimation unit.

3. 3. The axis deviation estimation device according to claim 1, the estimation implementation determination unit is configured to acquire the number of stationary objects extracted by the stationary object extraction unit for each of the predetermined azimuth angles, and determine not to estimate the axis deviation angle when the number of regions of the azimuth angles where the number of extracted stationary objects is equal to or less than a predetermined value is equal to or greater than a threshold.

4. 3. The axis deviation estimation device according to claim 1, the estimation implementation determination unit is configured to calculate azimuth dispersion of the stationary objects extracted by the stationary object extraction unit, and determine not to estimate the axis deviation angle when the azimuth dispersion is equal to or less than a threshold.

5. 3. The axis deviation estimation device according to claim 1, the estimation implementation determination unit is configured to calculate a total number of the stationary objects extracted by the stationary object extraction unit, and, when the total number is equal to or less than a threshold, determine not to estimate the axis deviation angle.

6. 3. The axis deviation estimation device according to claim 1, a reliability calculation unit (S165) that calculates a variation in the estimation result of the axis deviation angle by the axis deviation angle estimation unit as a reliability; the estimation implementation determination unit is configured to set a determination condition used for determining whether to estimate the axis deviation angle, in accordance with the reliability calculated by the reliability calculation unit, so that variation in the estimation result falls within a predetermined range.

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