Axis offset estimation device

Abstract

An axial deviation estimation device (4, 46) mounted on a mobile body comprises an acquisition unit (S10), an extraction unit (S20), a device coordinate unit (S30, S210) and an estimation unit (S30, S220, S230, S240). The estimation unit estimates the axial deviation angle and the height of the radar device using a relational expression established between at least two unknown parameters including the axial deviation angle and the mounting height of the above-mentioned radar device and at least two elements included in the device coordinates of a road surface reflection point, wherein the axial deviation angle is the deviation angle of the coordinate axis of the radar device around an object axis, which is one of a horizontal axis and a traveling direction axis as the coordinate axis of the mobile body.

Description

Technical Field

[0001] The present invention relates to a technology for estimating an axial deviation of a radar device that detects the direction and relative speed of an object. Background Art

[0002] In a vehicle-mounted radar device, the setting state changes due to some reason, resulting in so-called axis deviation, in which the central axis of the radar beam is offset. For example, the following patent document 1 discloses a technology for estimating the axis deviation angle of the vehicle-mounted radar device based on the fact that the reception intensity of the reflected wave from the vicinity of the vehicle becomes the maximum when the axis deviation occurs.

[0003] Patent Document 1: Japanese Patent No. 6321448

[0004] However, as a result of detailed studies by the inventors, it was found that the conventional device described in Patent Document 1 has a problem that the axis deviation of the radar device in the height direction cannot be estimated. Summary of the invention

[0005] One embodiment of the present invention provides a technique capable of estimating both the axis offset angle and the axis offset in the height direction of a radar device.

[0006] One aspect of the present invention provides an axial misalignment estimation device mounted on a moving object. The axial misalignment estimation device includes an acquisition unit, an extraction unit, a device-system coordinate unit, and an estimation unit.

[0007] The acquisition unit is configured to acquire reflection point information for each of the plurality of reflection points detected by the radar device. The reflection point information includes at least a horizontal angle and a vertical angle, which are azimuth angles with respect to the reflection point, and a distance between the radar device and the reflection point, and is obtained based on a direction along the central axis of the radar beam, that is, a beam direction. The extraction unit is configured to extract at least one road surface reflection point detected by reflection on the road surface from among the plurality of reflection points based at least on the reflection point information.

[0008] The device system coordinate unit is configured to determine the three-dimensional coordinates based on the coordinate axis of the radar device, that is, the device system coordinates, for each of the road surface reflection points based on the reflection point information. The estimation unit is configured to estimate the axis offset angle and the mounting height using a relationship between at least two unknown parameters including the axis offset angle and the mounting height of the radar device and at least two elements included in the device system coordinates of the road surface reflection point. The axis offset angle is the offset angle of the coordinate axis of the radar device around the target axis, which is one of the horizontal axis and the travel direction axis as the coordinate axis of the moving body.

[0009] As a result, the axis misalignment estimation device can estimate the axis misalignment angle and the mounting height at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a block diagram showing the structure of a vehicle control system.

[0011] Figure 2 This is an explanatory diagram for explaining the irradiation range of radar waves in the horizontal direction.

[0012] Figure 3 This is an explanatory diagram for explaining the irradiation range of radar waves in the vertical direction.

[0013] Figure 4 This is a block diagram for explaining the function of the signal processing unit.

[0014] Figure 5 This is an explanatory diagram for explaining the vertical axis offset angle and the roll angle.

[0015] Figure 6 This is an explanatory diagram for explaining an example of vertical axis deviation.

[0016] Figure 7 This is an explanatory diagram for explaining the positional deviation of the radar device in the height direction.

[0017] Figure 8 This is a flowchart of the axis offset estimation process according to the first embodiment.

[0018] Fig. 9 It is a flowchart of the road surface reflection extraction process.

[0019] Fig.10 This is a flowchart of the calculation process of the first embodiment.

[0020] Fig.11 This is an explanatory diagram for explaining the principle of estimating the vertical axis offset angle in the first embodiment.

[0021] Fig.12 This is a flowchart of the calculation process of Modification Example 1.

[0022] Fig.13 This is an explanatory diagram for explaining the principle of estimating the roll angle in the first modification.

[0023] Fig.14 This is a flowchart of the calculation process of Modification Example 3.

[0024] Fig.15 This is an explanatory diagram showing the principle of estimating the vertical axis offset angle and the roll angle in Modification 3.

[0025] Fig.16 This is a flowchart of the axis offset estimation process according to the second embodiment.

[0026] Fig.17 is a flow chart of the flatness processing.

[0027] Fig.18 is a flow chart of the weighting process. DETAILED DESCRIPTION

[0028] Hereinafter, the exemplary embodiments of the present invention will be described with reference to the accompanying drawings. In addition, the "vertical" mentioned below is not limited to the "vertical" in a strict sense, and may not be strictly "vertical" as long as the same effect is achieved. The same applies to the "horizontal" and "aligned" mentioned below.

[0029] [1. First embodiment]

[0030] [1-1. Structure]

[0031] (1) Overall structure

[0032] Figure 1 The vehicle control system 1 shown is a system mounted on a vehicle VH as a mobile body. The vehicle control system 1 includes a radar device 2, a vehicle-mounted sensor group 3, a signal processing unit 4, and an assist execution unit 5. In addition, the vehicle control system 1 may also include an axle deviation notification device 51 and an adjustment device 52. Hereinafter, the vehicle VH on which the vehicle control system 1 is mounted is also referred to as the host vehicle VH. In addition, the vehicle width direction of the host vehicle VH is also referred to as the horizontal direction, and the vehicle height direction is also referred to as the vertical direction.

[0033] like Figure 2 and Figure 3 As shown in FIG. 1 , the radar device 2 is mounted on the front side of the vehicle VH. The radar device 2 irradiates radar waves within a predetermined angle range Ra in the horizontal direction in front of the vehicle VH and within a predetermined angle range Rb in the vertical direction in front of the vehicle VH. The radar device 2 generates reflection point information related to the reflection point where the radar wave is reflected by receiving the reflected wave of the irradiated radar wave.

[0034] In addition, 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 lasers as radar waves, or a sonar that uses sound waves as radar waves. In short, the antenna unit that transmits and receives radar waves is configured to detect the direction of arrival of reflected waves in any direction of the horizontal direction and the vertical direction. The antenna unit may also include array antennas arranged in the horizontal direction and the vertical direction.

[0035] The radar device 2 is installed so that the beam direction coincides with the front-rear direction, that is, the traveling direction of the vehicle VH, and detects various targets existing in front of the vehicle VH. The beam direction refers to the direction along the central axis CA of the irradiated radar beam.

[0036] The reflection point information generated by the radar device 2 includes at least the azimuth of the reflection point and the distance of the reflection point. The distance of the reflection point refers to the distance between the radar device 2 and the reflection point. In addition, the radar device 2 can also be configured to detect the relative speed of the reflection point relative to the vehicle VH and the reception intensity of the radar beam reflected by the reflection point. The reflection point information can also include the relative speed and reception intensity of the reflection point.

[0037] like Figure 2 , 3 As shown, the azimuth of the reflection point is at least one of the horizontal angle (hereinafter referred to as the horizontal angle) Hor and the vertical angle (hereinafter referred to as the vertical angle) Ver where the reflection point is located, which are obtained based on the direction along the central axis CA of the radar beam, that is, the beam direction. In this embodiment, both the vertical angle Ver and the horizontal angle Hor are included in the reflection point information as information indicating the azimuth of the reflection point.

[0038] In the present embodiment, the radar device 2 adopts the FMCW method to alternately transmit radar waves in the uplink modulation interval and radar waves in the downlink modulation interval with a preset modulation period, and receives the reflected radar waves. FMCW is the abbreviation of Frequency Modulated Continuous Wave. In the present embodiment, the radar device 2 detects the azimuth angle of the reflection point, i.e., the horizontal angle Hor and the vertical angle Ver, the distance to the reflection point, the relative speed to the reflection point, and the received power of the received radar wave as the reflection point information according to each modulation period as described above. Hereinafter, the received power of the received radar wave is referred to as the reflected power.

[0039] The vehicle-mounted sensor group 3 is at least one sensor mounted on the vehicle VH in order to detect the state of the vehicle VH, etc. The vehicle-mounted sensor group 3 may also include a vehicle speed sensor. The vehicle speed sensor is a sensor that detects the vehicle speed based on the rotation of the wheels. In addition, the vehicle-mounted sensor group 3 may also include a camera. The camera captures the same range as the irradiation range of the radar wave of the radar device 2.

[0040] The vehicle-mounted sensor group 3 may include an acceleration sensor. The acceleration sensor detects the acceleration of the vehicle VH. The vehicle-mounted sensor group 3 may include a yaw rate sensor. The yaw rate sensor detects the speed of change of the yaw angle indicating the inclination of the traveling direction of the vehicle VH relative to the front of the vehicle VH.

[0041] In addition, the vehicle-mounted sensor group 3 may also include a navigation device having map information. The navigation device may also detect the position of the vehicle VH based on GPS signals, etc., and correspond the position of the vehicle VH to the map information. The map information may also include a numerical value indicating the flatness of the road surface as various information related to the road. Each sensor included in the vehicle-mounted sensor group 3 is connected to the signal processing unit 4 via a communication line.

[0042] The signal processing unit 4 includes a microcomputer including a CPU 41, and a semiconductor memory such as a ROM 43, a RAM 44, and a flash memory (hereinafter referred to as a memory 42). The various functions of the signal processing unit 4 are realized by executing a program stored in a non-migrating physical recording medium by the CPU 41. In this example, the memory 42 corresponds to a non-migrating physical recording medium storing the program. In addition, by executing the program, a method corresponding to the program is executed. In addition, the signal processing unit 4 may also include one microcomputer or a plurality of microcomputers.

[0043] like Figure 4 As shown, the signal processing unit 4 has the functions of a recognition unit 45 and an estimation unit 46. The recognition unit 45 detects the lane in which the host vehicle VH is traveling, the preceding vehicle traveling in the same lane as the host vehicle VH, other vehicles, obstacles, etc. based on the reflection point information obtained from the radar device 2 and various information obtained from the vehicle-mounted sensor group 3. The detection result in the recognition unit 45 is output to the assistance execution unit 5, etc. The estimation unit 46 estimates the axial offset of the radar device 2 as described later.

[0044] The assistance execution unit 5 controls various vehicle-mounted devices based on the detection results of the recognition unit 45 to perform predetermined driving assistance. The various vehicle-mounted devices that become the control targets may also include a monitor that displays images, an acoustic device that outputs an alarm sound or a guidance sound. In addition, it may also include a control device that controls the internal combustion engine, power transmission mechanism, brake mechanism, etc. of the host vehicle VH.

[0045] The axle misalignment notification device 51 is a sound output device installed in the vehicle cabin, and outputs a warning sound to the occupants of the host vehicle VH. Alternatively, an acoustic device or the like included in the assist execution unit 5 may be used as the axle misalignment notification device 51.

[0046] The adjustment device 52 includes a motor and a gear mounted on the radar device 2. The adjustment device 52 rotates the motor according to the drive signal output from the signal processing unit 4. Thus, the rotational force of the motor can be transmitted to the gear, so that the radar device 2 rotates around the axis along the horizontal direction and the axis along the vertical direction. In addition, the adjustment device 52 can make the radar device 2 move up and down in the vertical direction.

[0047] (2) Axis deviation of radar device 2

[0048] The axis deviation of the radar device 2 detected by the estimation unit 46 is described. The axis deviation refers to the deviation of the coordinate axis of the radar device 2 when the radar device 2 is actually installed on the vehicle VH from the coordinate axis of the radar device 2 when the radar device 2 is accurately installed on the vehicle VH. The axis deviation of the radar device 2 includes the axis deviation around the device coordinate axis and the axis deviation in the height direction.

[0049] (a) Coordinate axis

[0050] The coordinate axes of the radar device 2 and the coordinate axes of the host vehicle VH will be described.

[0051] Here, if Figure 5 As shown, the coordinate axes of the radar device 2 refer to the vertical axis Zs extending along the vertical direction of the radar device 2, the horizontal axis Ys extending along the horizontal direction of the radar device 2, and the front-rear axis Xs extending along the front and rear direction of the radar device 2 when the radar device 2 is installed on the vehicle VH. The vertical axis Zs, the horizontal axis Ys, and the front-rear axis Xs are orthogonal to each other. In the present embodiment in which the radar device 2 is provided in front of the vehicle VH, the front-rear axis Xs is equal to the central axis CA.

[0052] On the other hand, the coordinate axes of the host vehicle VH are the vertical axis Zc extending in the vertical direction, the horizontal axis Yc extending in the horizontal direction, and the traveling direction axis Xc extending in the traveling direction of the host vehicle VH. The vertical axis Zc, the horizontal axis Yc, and the traveling direction axis Xc are orthogonal to each other.

[0053] In addition, as described above, in the present embodiment, when the radar device 2 is accurately mounted on the vehicle VH, the central axis CA is consistent with the traveling direction of the vehicle VH. That is, the coordinate axes of the radar device 2 and the coordinate axes of the vehicle VH are consistent in all directions. For example, in the initial state such as when shipped from the factory, the radar device 2 is accurately mounted on the vehicle VH, that is, it is mounted at a predetermined position. Based on the detection result of the radar device 2 accurately mounted on the vehicle VH, the recognition unit 45 realizes the function of object recognition with high accuracy.

[0054] (b) Axis deviation around the device coordinate axis

[0055] After the initial state, axis deviation around the device coordinate axis will occur in the vehicle VH. Such axis deviation includes vertical axis deviation and roll axis deviation. The axis deviation angle represents the magnitude of such axis deviation in degrees.

[0056] Here, the vertical axis offset refers to a state in which an offset occurs between the up-down axis Zs of the coordinate axis of the radar device 2 and the vertical axis Zc of the coordinate axis of the host vehicle VH. The axis offset angle during such a vertical axis offset is called a vertical axis offset angle θp. The vertical axis offset angle θp is the so-called pitch angle θp, which is the axis offset angle of the coordinate axis (i.e., the left-right axis Ys) of the radar device 2 around the horizontal axis Yc of the host vehicle VH. That is, the vertical axis offset angle θp is the axis offset angle when an axis offset occurs around the left-right axis Ys of the radar device 2. In addition, according to Figure 5 It can be seen that the vertical axis offset angle θp may be an angle indicating the magnitude of the offset between the front-rear axis Xs of the coordinate axis of the radar device 2 and the traveling direction axis Xc of the coordinate axis of the host vehicle VH.

[0057] On the other hand, the roll axis offset refers to a state in which the left-right axis Ys of the coordinate axis of the radar device 2 and the horizontal axis Yc of the coordinate axis of the host vehicle VH are offset. The axis offset angle when such a roll axis offset occurs is called a roll angle θr. That is, the roll angle θr is the axis offset angle of the coordinate axis (i.e., the front-rear axis Xs) of the radar device 2 around the traveling direction axis Xc of the host vehicle VH. That is, the roll angle θr is the axis offset angle when the axis offset of the radar device 2 around the front-rear axis Xs occurs.

[0058] For example Figure 6 1 and 2. The case where a vertical axis offset, that is, an axis offset around the left-right axis Ys of the radar device 2 occurs is shown.

[0059] (c) Axis offset in height direction

[0060] As described above, the radar device 2 is accurately installed at a predetermined position of the vehicle VH in the initial state. The initial height referred to below refers to the height between the radar device 2 and the road surface at this time. The initial height is pre-stored in the memory 42 such as the ROM 43.

[0061] After the initial state, in the vehicle VH, an axial deviation in the height direction (hereinafter referred to as height deviation) occurs in the radar device 2. Figure 7 , an example of height deviation is shown in FIG. The radar device 200 shown by the dotted line indicates the position when it is set at the initial height F. For example, when the user replaces the tire of the host vehicle VH with a tire having a different diameter from that when the initial height is stored, or when the user replaces the suspension of the host vehicle VH with a suspension different from that when the initial height is stored, etc., a height deviation occurs.

[0062] The height deviation refers to a state in which the mounting height H is deviated from a predetermined height, that is, an initial height, in the vertical direction. The mounting height H refers to the height of the radar device 2 mounted on the vehicle VH from the road surface. The height deviation D represents the magnitude of such a height deviation in terms of distance.

[0063] In the present embodiment where the radar device 2 is installed in front of the vehicle VH, the front-rear axis Xs is equal to the central axis CA. That is, the height offset D corresponds to the vertical distance between the traveling direction axis Xc and the front-rear axis Xs of the radar device 2 .

[0064] The estimation unit 46 executes an axis offset estimation process described later to estimate the axis offset of the above-mentioned radar device 2 .

[0065] [1-2. Processing]

[0066] (1-1) Axis offset estimation processing

[0067] Next, use Figure 8 The flowchart of the axis offset estimation process performed by the signal processing unit 4 is described. This process is started when the ignition switch is turned on. In addition, the following describes an example in which the signal processing unit 4 estimates the vertical axis offset angle (i.e., the pitch angle) θp as the axis offset angle and the mounting height H of the radar device 2 through the axis offset estimation process.

[0068] If this process is started, the signal processing unit 4 acquires the reflection point information from the radar device 2 in S10. As described above, the reflection point information refers to information about each of the multiple reflection points detected by the radar device 2 mounted on the vehicle VH. The reflection point information includes at least the horizontal angle and the vertical angle as the azimuth of the reflection point and the distance between the radar device 2 and the reflection point. Hereinafter, the reflection point determined based on the reflection point information is referred to as the acquired reflection point. In addition, the signal processing unit 4 acquires various detection results including the vehicle speed Cm from the vehicle-mounted sensor group 3.

[0069] The signal processing unit 4 performs a road surface reflection extraction process in S20. The road surface reflection extraction process is a process for extracting a reflection point on the road surface, that is, a road surface reflection point, from the acquired reflection points. The road surface reflection point refers to a reflection point detected by reflection on the road surface. The details of the road surface reflection extraction process will be described later.

[0070] The signal processing unit 4 performs calculation processing in S30. The calculation processing is a process of estimating the axis deviation angle of the radar device 2 and the mounting height H of the radar device 2 based on at least the position of the road surface reflection point. In the present embodiment, the signal processing unit 4 estimates the vertical axis deviation angle θp as the axis deviation angle of the radar device 2 and the mounting height H of the radar device 2. The details of the calculation processing will be described later.

[0071] In S40 , the signal processing unit 46 determines the height offset D. In the present embodiment, the height offset D is the difference between the mounting height H estimated in S30 and the initial height. The estimation unit 46 stores the determined height offset D in the memory 42 .

[0072] In S50, the signal processing unit 4 determines whether the axis offset angle estimated in S30 and the height offset amount D estimated in S40 need to be adjusted by the mounted height adjustment device 52. When at least one of the vertical axis offset angle θp is greater than a predetermined angle, that is, a threshold angle, and the height offset amount D is greater than a predetermined distance, that is, a threshold distance, is satisfied, the signal processing unit 4 determines that adjustment is necessary. Here, when the signal processing unit 4 determines that adjustment is not necessary, that is, when the vertical axis offset angle θp is less than the threshold angle and the height offset amount D is less than the threshold distance, the process moves to S90. On the other hand, when the signal processing unit 4 determines that adjustment is necessary, the process moves to S60.

[0073] In S60, the signal processing unit 4 determines whether both the axis offset angle estimated in S30 and the height offset amount D estimated in S40 are within the adjustable range by the adjustment device 52. Here, the signal processing unit 4 moves the process to S70 when both the vertical axis offset angle θp and the height offset amount D are within the adjustable range. On the other hand, when at least one of the vertical axis offset angle θp and the height offset amount D is outside the adjustable range, the signal processing unit 4 moves the process to S80.

[0074] In S70, the signal processing unit 4 adjusts the radar mounting angle to the axis offset angle estimated in S30 by the adjustment device 52. That is, the signal processing unit 4 rotates the radar device 2 by the vertical axis offset angle θp around the left-right axis Ys of the radar device 2 with the left-right axis Ys as the center, and adjusts the mounting angle of the radar device 2. In addition, the signal processing unit 4 adjusts the mounting height H to the height offset amount D estimated in S40 by the adjustment device 52. That is, the signal processing unit 4 moves the radar device 2 up and down in the vehicle height direction with the front-rear axis Xs of the radar device 2 as the center by the height offset amount D, and adjusts the mounting height H. Then, the signal processing unit 4 ends the axis offset estimation process.

[0075] In addition, the signal processing unit 4 may calculate an azimuth obtained by correcting the azimuth of the reflection point acquired in S10 by the axis offset angle estimated in S30 in a process different from the actual axis offset estimation process. Furthermore, the signal processing unit 4 may cause the recognition unit 45 to execute based on the corrected azimuth.

[0076] In S80, the signal processing unit 4 outputs diagnostic information indicating that the radar device 2 has an axial deviation to an external device of the signal processing unit 4. Hereinafter, the diagnostic information indicating that the radar device 2 has an axial deviation is referred to as an axial deviation diagnosis. The external device may also be an axial deviation notification device 51. The signal processing unit 4 may also output the axial deviation diagnosis to the axial deviation notification device 51, for example. The axial deviation notification device 51 may also output a warning sound based on the axial deviation diagnosis.

[0077] The signal processing unit 4 determines whether the ignition switch is off in S90. Here, if the ignition switch is not off, the signal processing unit 4 moves the process to S10. On the other hand, if the ignition switch is off, the signal processing unit 4 ends the own axis offset estimation process.

[0078] (2-2) Road surface reflection extraction and processing

[0079] Next, use Fig. 9 The flowchart of FIG. 1 illustrates the road surface reflection extraction process executed by the signal processing unit 4 in S20 of the axis deviation estimation process.

[0080] In S100, the signal processing unit 4 acquires detection results of the state of the host vehicle VH and the like by various sensors from the vehicle-mounted sensor group 3. The detection results mentioned here may include the vehicle speed, acceleration, yaw angle and the like of the host vehicle VH.

[0081] In S110 , the signal processing unit 4 determines whether to extract a road surface reflection point based on the detection results of the state of the host vehicle VH and the like acquired from the vehicle-mounted sensor group 3 .

[0082] Specifically, the signal processing unit 4 determines whether the body of the vehicle VH is stable relative to the road surface based on the detection results of the state of the vehicle VH, and determines to extract the road surface reflection point when the body of the vehicle VH is stable relative to the road surface.

[0083] The state in which the vehicle body of the host vehicle VH is stable relative to the road surface may be a state in which the vehicle body of the host vehicle VH is not tilted relative to the road surface, or a state in which the vehicle body of the host vehicle VH is not moved up and down relative to the road surface. In other words, the state in which the vehicle body of the host vehicle VH is stable relative to the road surface may be a state in which the vehicle body of the host vehicle VH is not traveling on a curved road with a large curvature, or a state in which the vehicle body is not traveling on a road with a large unevenness.

[0084] Here, when the vehicle is not traveling on a road with large bumps, it can be said that the vehicle is traveling on a flat road. In this case, it is considered that the speed and acceleration are greater than when the vehicle is traveling on a road with large bumps. On the other hand, when the vehicle is not traveling on a curved road with large curvature, it can be said that the vehicle is close to traveling on a straight road. In this case, the speed and acceleration are greater than when the vehicle is traveling on a curved road with large curvature, and the change rate of the yaw angle is often smaller than when the vehicle is traveling on a curved road with large curvature.

[0085] Therefore, when the vehicle speed of the host vehicle VH is greater than a predetermined vehicle speed threshold, the signal processing unit 4 may determine that the vehicle body of the host vehicle VH is in a stable state relative to the road surface, and determine to extract the road surface reflection point. That is, when the vehicle speed of the host vehicle VH is less than the vehicle speed threshold, the signal processing unit 4 may determine that the vehicle body of the host vehicle VH is in an unstable state relative to the road surface, and determine not to extract the road surface reflection point.

[0086] Similarly, when the acceleration of the host vehicle VH is greater than a predetermined acceleration threshold, the signal processing unit 4 determines that the body of the host vehicle VH is in a stable state relative to the road surface, and determines to extract the road surface reflection point. In addition, similarly, when the change rate of the yaw angle of the host vehicle VH is less than a predetermined threshold, the signal processing unit 4 determines that the body of the host vehicle VH is in a stable state relative to the road surface, and determines to extract the road surface reflection point.

[0087] The signal processing unit 4 moves the process to S120 when determining that a road surface reflection point is to be extracted, and moves the process to S180 when determining that a road surface reflection point is not to be extracted.

[0088] The signal processing unit 4 selects one acquisition reflection point from all the acquisition reflection points in S120. The signal processing unit 4 executes the processes of S130 to S195 for the selected acquisition reflection point (hereinafter referred to as the acquisition reflection point).

[0089] In S130, the signal processing unit 4 determines whether the acquired reflection point is located within a prescribed azimuth range, i.e., an extraction range, which includes the central axis CA in the horizontal direction. If the acquired reflection point is located within the azimuth range, the signal processing unit 4 moves the processing to S140, and if the selected acquired reflection point is not located within the azimuth range, the processing moves to S190.

[0090] That is, the signal processing unit 4 extracts the acquisition reflection points located within the extraction range from the plurality of acquisition reflection points. The extraction range may also be determined, for example, as a range of ±several degrees to tens of degrees including the central axis CA in the horizontal direction. In other words, in the present embodiment in which the radar device 2 is arranged in front of the vehicle VH, the extraction range may also be determined as a prescribed range near the traveling direction of the vehicle VH. The extraction range may also be predetermined by experiments or the like. The extraction range is pre-stored in the memory 42.

[0091] In S140, the signal processing unit 4 determines whether the distance between the selected acquisition reflection point and the radar device 2 is less than a predetermined distance threshold. If the distance to the selected acquisition reflection point is less than the distance threshold, the signal processing unit 4 moves the process to S150, and if the distance to the selected acquisition reflection point is greater than the distance threshold, the signal processing unit 4 moves the process to S190.

[0092] That is, the signal processing unit 4 extracts the acquired reflection points whose distance from the radar device 2 is smaller than the distance threshold. The distance threshold is stored in the memory 42 in advance.

[0093] The signal processing unit 4 determines whether the acquired reflection point is a stationary reflection point in S150. If the acquired reflection point is a stationary reflection point, the signal processing unit 4 moves the processing to S160, and if the acquired reflection point is not a stationary reflection point, the signal processing unit 4 moves the processing to S190. A stationary reflection point refers to a reflection point where radar waves are reflected by a stationary object.

[0094] That is, the signal processing unit 4 extracts the stationary reflection points from the acquired reflection points. Specifically, the signal processing unit 4 may also use the vehicle speed Cm acquired in S10, set the relative speed contained in the reflection point information to q, set the preset lower speed threshold to ε1, and set the upper speed threshold to ε2, and extract the acquired reflection points satisfying ε1≤q / Cm<ε2 as stationary reflection points. That is, the acquired reflection points within the predetermined speed threshold range where the ratio of the vehicle speed Cm to the relative speed q is greater than ε1 and less than ε2 are extracted as stationary reflection points.

[0095] When the direction from the stationary reflection point toward the radar device 2 is consistent with the beam direction, the vehicle speed Cm and the relative speed q of the reflection point are the same, and the direction of the relative speed q is opposite to the vehicle speed Cm, so q / Cm = -1. In this way, the reflection point with q / Cm = -1 is considered to be a stationary reflection point.

[0096] The vehicle speed Cm obtained from the vehicle-mounted sensor group 3 may not be consistent with the actual vehicle speed due to wheel slippage, etc. In addition, the relative speed q detected by the radar device 2 also contains errors. Therefore, even at a stationary reflection point, q / Cm=-1 is not necessarily the case. The lower speed threshold ε1 and the upper speed threshold ε2 may also be appropriately set in consideration of these effects.

[0097] In S160, the signal processing unit 4 determines whether the reflected power at the reflection point is less than a predetermined power threshold. If the reflected power at the reflection point is less than the power threshold, the signal processing unit 4 moves the process to S170, and if the reflected power at the reflection point is greater than the power threshold, the signal processing unit 4 moves the process to S190.

[0098] That is, the signal processing unit 4 extracts the reflection points where the reflection power is less than the power threshold. It is considered that the reflection power from the road surface is smaller than the reflection power from other vehicles, for example. The power threshold can also be appropriately determined based on such reflection power from the road surface. For example, the power threshold can also be predetermined by experiments, etc. The power threshold is pre-stored in the memory 42.

[0099] In S170, the signal processing unit 4 determines whether the acquired reflection point is recognized as a road surface in the captured image of the camera. If the acquired reflection point is estimated as a road surface in the captured image, the signal processing unit 4 moves the processing to S180, and if the acquired reflection point is not estimated as a road surface in the captured image, the signal processing unit 4 moves the processing to S195.

[0100] That is, the signal processing unit 4 extracts the acquired reflection points recognized as the road surface in the captured image. In addition, the signal processing unit 4 may also be configured to acquire the captured image of the camera and estimate the azimuth range recognized as the road surface in the captured image in a process different from the own-axis offset estimation process.

[0101] The signal processing unit 4 determines in S180 that the acquired reflection point is a road surface reflection point, stores the three-dimensional coordinates of the acquired reflection point as a road surface reflection point in the memory 42, and moves the process to S195.

[0102] The signal processing unit 4 determines in S190 that the acquired reflection point is not a road surface reflection point, does not store the acquired reflection point in the memory 42, and moves the process to S195.

[0103] In S195, the signal processing unit 4 determines whether the confirmation of whether all the acquired reflection points are road surface reflection points has been completed. Here, if the confirmation has not been completed, the signal processing unit 4 moves the processing to S110 and repeats the processing of S110-S195. On the other hand, if the confirmation has been completed, the signal processing unit 4 ends the road surface reflection extraction processing.

[0104] That is, in the road surface reflection extraction process of the present embodiment, among the acquired reflection points, those that satisfy all of the following (a) to (e) are extracted as road surface reflection points.

[0105] (a) It is located within the extraction range including the central axis CA in the horizontal direction.

[0106] (b) The distance to the radar device 2 is smaller than the distance threshold.

[0107] (c) is the stationary reflection point.

[0108] (d) The reflected power is less than the power threshold.

[0109] (e) Recognized as a road surface in the image captured by the camera.

[0110] In addition, the road surface reflection extraction process may also be configured to satisfy at least (a) of the above (a)-(e). That is, the road surface reflection extraction process may also be configured to satisfy (a) and further satisfy at least one of (b)-(e). Alternatively, the road surface reflection extraction process may also be configured to satisfy at least (a) and (b). That is, the road surface reflection extraction process may also be configured to satisfy (a) and (b), and the road surface reflection extraction process may further satisfy at least one of (c)-(e).

[0111] [2-3. Calculation Processing]

[0112] Next, use Fig.10 The flowchart of FIG. 4 illustrates the calculation process executed by the signal processing unit 4 in S30 of the axis deviation estimation process. The signal processing unit 4 estimates the vertical axis deviation angle θp and the mounting height H through the calculation process.

[0113] In S210, the signal processing unit 4 calculates the device coordinates of the road surface reflection point based on the reflection point information using the distance and azimuth included in the reflection point information. The device coordinates refer to three-dimensional coordinates based on the coordinate axes of the radar device 2. The device coordinates are coordinates that have the horizontal distance (hereinafter, ys), the vertical distance (hereinafter, zs), and the distance in the beam direction (hereinafter, xs) on the plane orthogonal to the beam direction as elements. The signal processing unit 4 calculates the device coordinates (xs, ys, zs) for all road surface reflection points and stores them in the memory 42.

[0114] In S220, the signal processing unit 4 estimates the vertical axis offset angle θp and the mounting height H of the radar device 2. Specifically, the signal processing unit 4 estimates using a relational expression (i.e., equation (1)) established between the vertical axis offset angle θp as an unknown parameter, the mounting height H as an unknown parameter, and two elements (i.e., xs and zs) included in the device system coordinates.

[0115] [Mathematical formula 1]

[0116]

[0117] [Mathematical formula 2]

[0118] in,

[0119]

[0120] in addition,

[0121]

[0122] A and B in equation (1) are as shown in equation (2). In addition, when multiple (i.e., n) road surface reflection points are detected, the device system coordinate image (xs n , ys n , zs n ), where n is an integer greater than 2. xs, ys, and zs at each road surface reflection point are expressed as in equation (3). That is, A is an n×2 matrix, and B is an n×1 matrix.

[0123] The signal processing unit 4 calculates the vertical axis offset angle θp and the mounting height H based on the equation (1), stores the calculated vertical axis offset angle θp and the mounting height H in the memory 42, and ends the calculation process.

[0124] [2-4. Derivation of relational expressions]

[0125] The derivation of the relational expression (that is, the expression (1) in the present embodiment) will be described.

[0126] Furthermore, first, the correspondence between the axis offset angle in the relational expression and the two elements included in the device system coordinates will be described.

[0127] If one of the horizontal axis Yc and the traveling direction axis Xc, which are the coordinate axes of the host vehicle VH, is set as the target axis, the axis offset angle can be said to be the offset angle of the coordinate axis of the radar device 2 around the target axis. For example, the vertical axis offset angle θp is the axis offset angle of the coordinate axis of the radar device 2 around the horizontal axis Yc, which is the target axis, and the roll angle θr is the axis offset angle of the coordinate axis of the radar device 2 around the traveling direction axis Xc, which is the target axis.

[0128] If the coordinate axes of the radar device 2 corresponding to the target axis are defined as corresponding axes, the corresponding axis corresponding to the horizontal axis Yc is the left-right axis Ys, and the corresponding axis corresponding to the traveling direction axis Xc is the front-back axis Xs.

[0129] The two elements included in the above-mentioned device-system coordinates are elements related to the two coordinate axes of the radar device 2 included in the plane perpendicular to the corresponding axis among the three coordinate axes of the radar device 2. In other words, the two elements included in the above-mentioned device-system coordinates are equivalent to the coordinates of the projection point of the road surface reflection point on the plane perpendicular to the corresponding axis among the three coordinate axes of the radar device 2, that is, the projection plane.

[0130] In the present embodiment of estimating the vertical axis offset angle θp, the target axis is the horizontal axis Yc, and the corresponding axis is the left-right axis Ys. Thus, the elements (i.e., zs and xs) related to the up-down axis Zs and the front-back axis Xs of the radar device 2 included in the plane perpendicular to the corresponding axis, i.e., the left-right axis Ys, are equivalent to the two elements included in the above-mentioned device coordinates. In other words, the two elements zs and xs included in the device coordinates are equivalent to the coordinates of the projection point of the road surface reflection point projected onto the projection plane perpendicular to the left-right axis Ys.

[0131] In addition, in the example of estimating the roll angle θr (i.e., Modification 1 described later), the target axis is the traveling direction axis Xc, and the corresponding axis is the front-rear axis Xs. Thus, the elements (i.e., ys and zs) related to the left-right axis Ys and the up-down axis Zs of the radar device 2 included in the plane perpendicular to the corresponding axis, i.e., the front-rear axis Xs, are equivalent to the two elements included in the above-mentioned device system coordinates. In other words, the two elements ys and zs included in the device system coordinates are equivalent to the coordinates of the projection point of the road surface reflection point projected onto the projection plane perpendicular to the front-rear axis Xs.

[0132] In this way, the two elements in the relation are determined.

[0133] Next, the derivation of the relational expression will be described. Hereinafter, the derivation of the relational expression for estimating the vertical axis offset angle θp (ie, Expression (1)) will be described.

[0134] like Fig.11 As shown, the road surface reflection points are located on the road surface. That is, the road surface reflection points are located on the same plane as the road surface. Therefore, it is considered that a plurality of road surface reflection points are arranged in a straight line on the above-mentioned projection plane.

[0135] Here, assuming that the radar device 2 has no height offset, the coordinate axes of the radar device 2, namely the front-rear axis Xs and the up-down axis Zs, are rotated by a vertical axis offset angle θp on the projection plane, thereby being consistent with the coordinate axes of the vehicle VH, namely the traveling direction axis Xc and the vertical axis Zc.

[0136] That is, on the projection plane, the coordinate axis of the radar device 2 is offset by the vertical axis offset angle θp around the traveling direction axis Xc, so that the two elements (xs, zs) of the device coordinate system coincide with the two elements (xc, zc) of the vehicle coordinate system. Here, the vehicle coordinate system refers to the three-dimensional coordinates (xc, yc, zc) based on the coordinate axis of the host vehicle VH.

[0137] In other words, on the projection plane, the radar device 2 is rotated about the front-rear axis Xs by the vertical axis offset angle θp, so that the two elements (xs, zs) of the device coordinates coincide with the two elements (xc, zc) of the vehicle coordinates. That is, the following equation (4) holds.

[0138] [Mathematical formula 3]

[0139]

[0140] On the other hand, according to Fig. 9 It can be seen that the magnitude of the vehicle coordinate (zc) is equal to the mounting height H, and the sign is negative. Therefore, equation (5) is obtained.

[0141] [Formula 4]

[0142] [z c ]=[-H] (5)

[0143] Furthermore, according to equations (4) and (5), the relationship of equation (6) is obtained.

[0144] [Mathematical formula 5]

[0145] [z c ]=[sinθ p × s +cosθ p × s ]=[-H] (6)

[0146] Furthermore, the relationship of equation (7) is obtained from equation (6), and equation (8) and equation (9) are obtained from equation (7).

[0147] [Mathematical formula 6]

[0148] [sinθ p × s +H]=[-cosθ p × s ] (7)

[0149]

[0150]

[0151] In formula (9), by expressing A and B as in formula (2), formula (1) can be obtained.

[0152] [1-3. Effect]

[0153] According to the first embodiment described in detail above, the following effects are achieved.

[0154] (1a) In S10, the signal processing unit 4 repeatedly obtains reflection point information for each of the multiple reflection points detected by the radar device 2. The horizontal angle and the vertical angle are obtained based on the beam direction. In S20, the signal processing unit 4 extracts multiple road surface reflection points from the multiple reflection points based on at least the reflection point information.

[0155] In S210, the signal processing unit 4 determines the device system coordinates for each of the road surface reflection points based on the reflection point information. In S220, the signal processing unit 4 estimates the vertical axis offset angle θp and the mounting height H using the relationship (i.e., equations (1)-(3)). Equation (1) is a relationship established between two unknown parameters (i.e., the vertical axis offset angle θp and the mounting height H) and two elements (i.e., xs and zs) of the device system coordinates included in the road surface reflection point.

[0156] The device coordinates of each reflection point are detected with high accuracy by the radar device 2. The signal processing unit 4 arithmetically estimates the vertical axis offset angle θp and the mounting height H as the axis offset angle based on the device coordinates of the road surface reflection point.

[0157] Conventionally, there is no technology that can simultaneously estimate the axis offset angle and the mounting height.

[0158] The signal processing unit 4 can simultaneously estimate the vertical axis offset angle θp and the mounting height H as the axis offset angle. As a result, the signal processing unit 4 can estimate the axis offset angle and the height offset amount D based on the mounting height H. In addition, the signal processing unit 4 can correct both the vertical axis offset angle θp and the mounting height H.

[0159] However, the existing device (hereinafter referred to as the comparison device) that estimates the axis offset angle based on the situation where the reception intensity of the reflected wave from the vicinity of the vehicle becomes the maximum when the axis offset occurs is based on the premise that no offset occurs at the mounting height H. That is, the comparison device estimates the axis offset angle by assuming that no height offset occurs when it is not known whether the axis offset or the height offset around the device coordinate axis has occurred. Therefore, in the comparison device, even if it is assumed that only the height offset occurs and no axis offset around the device coordinate axis has occurred, it is possible to estimate the axis offset angle around the device coordinate axis. That is, in the comparison device, an estimation error of the axis offset angle may occur.

[0160] Since the signal processing unit 4 estimates both the axis offset angle and the mounting height, it is possible to estimate the mounting height and suppress an estimation error of the axis offset angle.

[0161] (1b) The two elements (i.e., xs and zs) included in the above-mentioned device-based coordinates are elements related to the two coordinate axes (i.e., the front-rear axis Xs and the up-down axis Zs) of the radar device 2 included in the plane perpendicular to the corresponding axis among the three coordinate axes of the radar device 2. The corresponding axis mentioned here is the left-right axis Ys. The corresponding axis refers to the coordinate axis of the radar device 2 corresponding to the object axis (i.e., Yc). Thus, the axis offset angle is estimated based on the two-dimensional coordinates, so that the processing load of the signal processing unit 4 can be reduced compared with the case of using the device-based coordinates as three-dimensional coordinates.

[0162] (1c) The signal processing unit 4 may also be configured to obtain the detection result of the state of the vehicle VH from the vehicle-mounted sensor group 3 that detects the state of the vehicle VH in S110, and judge whether the body of the vehicle VH is stable relative to the road surface based on the detection result. Moreover, the signal processing unit 4 may also be configured to extract at least one road surface reflection point from multiple reflection points in S20 when it is judged that the body of the vehicle VH is stable relative to the road surface. As a result, it is difficult to extract reflection points on non-planar road surfaces such as inclined surfaces and concave-convex surfaces as road surface reflection points. That is, since it is easy to extract reflection points on a flat road surface as road surface reflection points, the axis offset angle can be estimated with high accuracy based on the situation where the road surface reflection points are located on the same plane.

[0163] (1d) The signal processing unit 4 may be configured to extract, based on the reflection point information, at least one reflection point located within a predetermined azimuth range including the central axis CA of the radar beam in the horizontal direction from among the plurality of reflection points as a road surface reflection point in S130.

[0164] As a result, it is considered that the road surface is at least located in the vicinity of the front direction of the vehicle VH (i.e., the direction of the central axis CA of the radar beam), so by appropriately determining the specified azimuth range, the accuracy of extracting the reflection points on the road surface can be improved.

[0165] (1e) The signal processing unit 4 may also be configured to extract, based on the reflection point information, at least one reflection point whose distance from the radar device 2 is less than a distance threshold from the plurality of reflection points as a road surface reflection point in S140. As a result, it is considered that the road surface is at least located closest to the vehicle VH, and thus the accuracy of extracting the reflection points on the road surface can be further improved by appropriately determining the distance threshold.

[0166] (1f) The reflection point information may also include the relative speed of the reflection point with respect to the vehicle VH. The signal processing unit 4 may also be configured to extract at least one reflection point that is a stationary reflection point from the plurality of reflection points as a road surface reflection point in S150 based on the reflection point information. As a result, since the road surface is stationary with respect to the vehicle VH, the accuracy of extracting the reflection points on the road surface can be further improved.

[0167] (1g) The reflection point information may also include the reception intensity of the reflection point. The signal processing unit 4 may also be configured to extract at least one reflection point whose reflection power is less than a power threshold as a road surface reflection point in S160 based on the reflection point information. As a result, since the reflection power from the road surface is considered to be smaller than the reflection power from other vehicles, for example, the power threshold is appropriately determined based on the reflection power from the road surface, and thus the accuracy of extracting the reflection point on the road surface can be further improved.

[0168] (1h) The signal processing unit 4 may also be configured to acquire a captured image of a camera and estimate the azimuth range of the road surface identified in the captured image. The signal processing unit 4 may also be configured to extract at least one reflection point located within the azimuth range estimated as the road surface in the captured image from among the plurality of reflection points in S170 as a road surface reflection point. In this way, the accuracy of extracting the road surface reflection point can be further improved.

[0169] In addition, in the above-mentioned embodiment, the coordinate axes of the host vehicle VH are equivalent to the coordinate axes of the mobile body. In addition, the vertical axis offset angle θp is equivalent to the axis offset angle. The vertical axis offset angle θp and the mounting height H are equivalent to two unknown parameters and at least two unknown parameters including the axis offset angle, and xs and zs are equivalent to two elements and at least two elements included in the device system coordinates. The horizontal axis Yc is equivalent to the object axis, the left and right axes Ys are equivalent to the corresponding axes, and the two coordinate axes of the radar device 2 included in the plane perpendicular to the corresponding axes are equivalent to the front-rear axis Xs and the up-down axis Zs.

[0170] [1-4. Modifications]

[0171] (Variant 1) In variant 1, the signal processing unit 4 may estimate the roll angle θr as the axis offset angle instead of the vertical axis offset angle θp. Specifically, the signal processing unit 4 may also perform Fig.12 The calculation process shown is replaced by Fig.10 The calculation process shown. Fig.12 In the calculation process shown, Fig.10 The S220 in the example is replaced by S230.

[0172] The signal processing unit 4 performs the following steps in S210: Fig.10Similarly, in S210 shown, based on the reflection point information, the device system coordinates are determined for each road surface reflection point.

[0173] In S230, the signal processing unit 4 estimates the roll angle θr and the mounting height H as the axis offset angle. Specifically, the signal processing unit 4 estimates using a relational expression (i.e., equation (10)). The relational expression (i.e., equation (10)) is a relational expression established between the roll angle θr as an unknown parameter, the mounting height H of the radar device 2 as an unknown parameter, and two elements (i.e., ys and zs) included in the device system coordinates.

[0174] [Mathematical formula 7]

[0175]

[0176] [Mathematical formula 8]

[0177]

[0178] A and B in formula (10) are as shown in formula (11). In addition, ys and zs in formula (11) are as shown in formula (3).

[0179] The signal processing unit 4 calculates the roll angle θr and the mounting height H based on the equation (10), stores the calculated roll angle θr and the mounting height H in the memory 42, and ends the calculation process.

[0180] In addition, if Fig.13 As shown, the road surface reflection points are located on the same plane as the road surface. Therefore, it is considered that multiple road surface reflection points are arranged in a straight line on the projection plane perpendicular to the front-rear axis Xs (i.e., the Ys-Zs plane). The relationship (i.e., equation (10)) is the same as the above equations (4)-(9), and can be obtained by replacing the vertical axis offset angle θp in the above equations (4)-(9) with the roll angle θr and replacing xs with ys.

[0181] Thus, the axis deviation estimation device in the modification 1, i.e., the signal processing unit 4, takes the traveling direction axis Xc as the target axis, and takes the axis deviation angle about the traveling direction axis Xc, i.e., the roll angle θr and the mounting height H as unknown parameters. In addition, the signal processing unit 4 takes xs and ys in the device system coordinates of the road surface reflection point as two elements. In the signal processing unit 4, the estimation unit 46 is configured to determine the roll angle θr and the mounting height H by calculation based on the above-mentioned equations (10)-(11) and (3).

[0182] As a result, the signal processing unit 4 can estimate the roll angle θr, which is the axis offset angle, and the mounting height H at the same time.

[0183] In addition, in the modification 1, the roll angle θr is equivalent to the axis offset angle, and the roll angle θr and the mounting height H are equivalent to two unknown parameters including the axis offset angle and at least two unknown parameters. Ys and zs are equivalent to two elements and at least two elements included in the device system coordinates. The front-back axis Xs is equivalent to the corresponding axis, and the two coordinate axes of the radar device 2 included in the plane perpendicular to the corresponding axis are equivalent to the left-right axis Ys and the up-down axis Zs.

[0184] (Variation 2) The signal processing unit 4 may use the vertical axis offset angle θp and the roll angle θr as the axis offset angles to estimate the vertical axis offset angle θp, the roll angle θr and the mounting height H. Specifically, the signal processing unit 4 may also execute Fig.10 The calculation process shown in S220 is added after Fig.12 The calculation process shown in S230 is performed. In addition, as the mounting height H, an average value of the values ​​calculated based on S220 and S230 may be used.

[0185] (Variant 3) The signal processing unit 4 may use a calculation method different from that of (Variant 2) to estimate the vertical axis offset angle θp and the roll angle θr as the axis offset angles, and the vertical axis offset angle θp and the roll angle θr, as well as the loading height H. Specifically, the signal processing unit 4 may also perform Fig.14 The calculation process shown is replaced by Fig.10 The calculation process shown. Fig.14 In the calculation process shown, Fig.10 The S220 in the example is replaced by S240.

[0186] In S240, the signal processing unit 4 estimates the vertical axis offset angle θp and the roll angle θr as the axis offset angles, and the mounting height H. Specifically, the signal processing unit 4 uses a relational expression (i.e., equation (12)) for estimation. The relational expression (i.e., equation (12)) is a relational expression established between the vertical axis offset angle θp as an unknown parameter, the roll angle θr as an unknown parameter, the mounting height H of the radar device 2 as an unknown parameter, and the three elements (i.e., xs, ys, and zs) included in the device system coordinates.

[0187] [Mathematical formula 9]

[0188]

[0189] The signal processing unit 4 calculates the vertical axis offset angle θp, the roll angle θr, and the mounting height H based on equation (12), stores the calculated vertical axis offset angle θp, the roll angle θr, and the mounting height H in the memory 42, and ends the calculation process.

[0190] In addition, if Fig.15 As shown, equation (12) is obtained based on the fact that the coordinate axis of the radar device 2 is rotated around the left-right axis Ys by the vertical axis offset angle θp and around the front-back axis Xs by the roll angle θr so as to coincide with the coordinate axis of the vehicle VH. That is, equations (13) to (14) are obtained.

[0191] [Formula 10]

[0192]

[0193] Here, from the relationship expressed by the above-mentioned equation (5) and equation (14), equation (15) is obtained. In addition, by dividing equation (15) by cosθrcosθp, equation (16) is obtained. And, equation (12) is derived from equation (16).

[0194] [Mathematical formula 11]

[0195] [Z c ]=[cosθ r sinθ p X s -sinθ r Y s +cosθ r cosθ p Z s ]=[-H] (15)

[0196]

[0197] As a result, the signal processing unit 4 can estimate the vertical axis offset angle θp and the roll angle θr, which are axis offset angles, and the mounting height H at the same time.

[0198] [2. Second Embodiment]

[0199] [2-1. Structure]

[0200] The basic structure of the second embodiment is the same as that of the first embodiment, so the differences will be described below. In addition, the same reference numerals as those of the first embodiment represent the same structure, and the previous description is referred to.

[0201] In the first embodiment, the axle offset angle and the mounting height H are estimated based on the position of the road surface reflection point. In contrast, in the second embodiment, the road surface flatness Wc is calculated, and the axle offset angle and the mounting height H are estimated by weighting based on the road surface flatness Wc based on the position of the road surface reflection point, which is different from the first embodiment. The road surface flatness Wc is a numerical value indicating the degree of flatness of the road surface. Here, the flatter the road surface, the larger the numerical value of the road surface flatness Wc is.

[0202] [2-2. Processing]

[0203] [2-2-1. Axis offset estimation processing]

[0204] Next, use Fig.16 The flowchart of the second embodiment replaces the signal processing unit 4 Figure 8 The axis offset estimation process performed by the axis offset estimation process of the first embodiment shown in FIG. Fig.16 Processing other than S25-S27 in Figure 8 The processing of S10-S20 and S30-S90 is the same, so the description will be partially simplified.

[0205] In S25 subsequent to S20 , the signal processing unit 4 performs a flatness process described later to calculate the road surface flatness Wc.

[0206] The signal processing unit 4 determines whether the road surface is flat based on the road surface flatness Wc in the flatness determination unit S26 . Specifically, the signal processing unit 4 determines that the road surface is flat when the road surface flatness Wc is equal to or greater than a predetermined flatness threshold WT. The flatness threshold WT is stored in advance in the memory 42 .

[0207] Here, if the signal processing unit 4 determines that the road surface is flat, the processing moves to S30, and after S30, the same Figure 8 On the other hand, when the signal processing unit 4 determines that the road surface is uneven, the processing proceeds to S27.

[0208] In S27, the signal processing unit 4 performs weighting processing described later, and further performs weighting based on the road surface flatness Wc based on the above-mentioned relationship to estimate the vertical axis deviation angle θ p And the loading height H. And, the process is moved to S40, and S40 and thereafter are executed with Figure 8 The same processing as shown.

[0209] [2-2-2. Flatness processing]

[0210] based on Fig.17 The flowchart shown in FIG. 4 is used for the signal processing unit 4. Fig.16 The flatness processing executed in S25 of the axis offset estimation processing shown in FIG.

[0211] In S310, the signal processing unit 4 obtains the output value of the acceleration sensor and calculates the first coefficient W1 based on the output value. The first coefficient W1 is a numerical value indicating the flatness of the road surface, and the larger the output value of the acceleration sensor is, the smaller the first coefficient W1 is calculated to be. For example, the output value of the acceleration sensor and the corresponding first coefficient W1 may be stored in the memory 42 as information in the form of a table, and the signal processing unit 4 may refer to the information in the form of the table to calculate the first coefficient W1 corresponding to the output value of the acceleration sensor.

[0212] In S320, the signal processing unit 4 obtains the value of the reflected power of each of the plurality of road surface reflection points, and calculates the second coefficient W2 based on the deviation of the reflected power. The second coefficient W2 is a numerical value representing the flatness of the road surface, and the larger the index representing the deviation of the reflected power, the smaller the second coefficient W2 is calculated to be. The signal processing unit 4 may, for example, use the standard deviation or variance of the reflected power as an index representing the deviation. For example, information in the form of a table representing the correspondence between the second coefficient W2 and the index representing the deviation may be stored in the memory 42, and the signal processing unit 4 may refer to the table to calculate the second coefficient W2 corresponding to the index representing the deviation.

[0213] In S330, the signal processing unit 4 obtains the current position of the vehicle VH from the navigation device, and calculates the third coefficient W3 based on the current position of the vehicle VH and the map information. The third coefficient W3 is a numerical value indicating the flatness of the road surface, and is included in the map information. The flatter the road surface, the larger the third coefficient W3 is. The signal processing unit 4 may also obtain the flatness of the road surface at the current position of the vehicle VH based on the map information, and use the obtained flatness as the third coefficient W3.

[0214] In S340, the signal processing unit 4 obtains the captured image of the camera and calculates the fourth coefficient W4 based on the captured image. The fourth coefficient W4 is a numerical value representing the flatness of the road surface and is based on the captured image. The flatter the road surface, the larger the value of the fourth coefficient W4. The captured image mentioned here includes the road surface in front of the vehicle VH. The signal processing unit 4 may also use a recognizer to estimate the flatness of the road surface included in the captured image, and use the estimated flatness as the fourth coefficient W4. The recognizer is previously trained to estimate the flatness of the road surface included in the image based on a plurality of images including the road surface.

[0215] In S350, the signal processing unit 4 calculates the road surface flatness Wc using the first coefficient W1-fourth coefficient W4. The signal processing unit 4 stores the average value of the first coefficient W1-fourth coefficient W4 as the road surface flatness in the Wc memory 42. The signal processing unit 4 ends the flatness processing at this point. However, the present invention is not limited to this. The signal processing unit 4 may also use the maximum value or the median value of the first coefficient W1-fourth coefficient W4 as the road surface flatness Wc and store it in the memory 42.

[0216] [2-2-3. Weighting Processing]

[0217] based on Fig.18 The flowchart shown in FIG. 4 is used for the signal processing unit 4. Fig.16 The weighting process performed in S27 of the axis misalignment estimation process shown in FIG. 1 is described below. The weighting process is repeatedly performed each time the process moves to S27 in the axis misalignment estimation process. In addition, a series of processes from the beginning to the end of the weighting process is also referred to as a "cycle".

[0218] In S410, the signal processing unit 4 calculates the device system coordinates of the road surface reflection point in the current cycle, similarly to S210. In addition, xs, ys, and zs of each of the plurality of (ie, n) road surface reflection points are expressed as in the above-mentioned equation (3).

[0219] The signal processing unit 4 performs weighted calculations based on the road surface flatness Wc on the right side of the above-mentioned equation (1) in S420-S470, thereby estimating the left side of the equation (1), that is, the vertical axis deviation angle θp and the mounting height H after weighting based on the road surface flatness Wc.

[0220] First, in S420, the signal processing unit 4 calculates the parameters Ma and Mb used to calculate the right side of equation (1) based on the device system coordinates of the road surface reflection point in the current cycle, as in equations (17) and (18).

[0221] [Mathematical formula 12]

[0222] Ma=A T A (17)

[0223] Mb=A T B (18)

[0224] Here, the parameters A and B are as shown in the above equation (2). The parameter Ma is a 2×2 matrix, and the parameter Mb is a 2×1 matrix.

[0225] In S430 , the signal processing unit 4 obtains the road surface flatness Wc of the current cycle.

[0226] In S440, the signal processing unit 4 calculates the weighted parameters Mwa and Mwb of the current cycle as in equations (19) and (20). The weighted parameter Mwa of the current cycle is obtained by multiplying the parameter Ma of the current cycle by the road surface flatness Wc of the current cycle. The weighted parameter Mwb of the current cycle is obtained by multiplying the parameter Mb of the current cycle by the road surface flatness Wc of the current cycle.

[0227] [Mathematical formula 13]

[0228] Mwa=wc×Ma (19)

[0229] Mwb=wc×Mb (20)

[0230] In S450, the signal processing unit 4 stores the total weighted parameter Mcwa of the current cycle in the memory 42. As in formula (21), the weighted parameter Mwa of the current cycle is added to the total weighted parameter Mdcwa of the past stored in the memory 42 to obtain the total weighted parameter Mcwa of the current cycle. Similarly, the signal processing unit 4 stores the total weighted parameter Mcwb of the current cycle in the memory 42. As in formula (22), the weighted parameter Mwb of the current cycle is added to the total weighted parameter Mdcwb of the past stored in the memory 42 to obtain the total weighted parameter Mcwb of the current cycle. The past here means used in the previous cycle.

[0231] [Formula 14]

[0232] Mcwa=Mwa+Mdcwa (21)

[0233] Mcwb=Mwb+Mdcwb (22)

[0234] In S460, the signal processing unit 4 uses the total weighted parameters Mcwa and Mcwb of the current cycle to estimate the weighted vertical axis offset angle θp and the mounting height H based on the road surface flatness Wc according to equation (23). The signal processing unit 4 stores the estimated vertical axis offset angle θp and the mounting height H in the memory 42.

[0235] [Mathematical formula 15]

[0236]

[0237] In S470, the signal processing unit 4 stores the total weight parameter Mcwa of the current cycle as the past total weight parameter Mdcwa in the memory 42. In addition, the signal processing unit 4 stores the total weight parameter Mcwb of the current cycle as the past total weight parameter Mdcwb in the memory 42. The signal processing unit 4 then ends the weighting process.

[0238] [2-3. Effect]

[0239] According to the second embodiment described in detail above, the following effects are achieved.

[0240] (2a) The signal processing unit 4 calculates the road surface flatness Wc in S25. The signal processing unit 4 determines whether the road surface is flat based on the road surface flatness Wc in S26. When the signal processing unit 4 determines that the road surface is uneven, the signal processing unit 4 estimates the axle offset angle θp and the mounting height H by weighting the road surface flatness Wc based on the relationship (i.e., equations (1) to (3)).

[0241] As the road surface flatness Wc increases, that is, as the road surface becomes flatter, the number of road surface reflection points at that time increases, and the axle offset angle θp and the mounting height H are estimated. In other words, weighting is equivalent to using a larger number of road surface reflection points at that time as the road surface becomes flatter, to estimate the axle offset angle θp and the mounting height H. As a result, the axle offset angle θp and the mounting height H weighted by the road surface flatness Wc can be estimated.

[0242] [2-4. Modifications]

[0243] (Variant 4) In the second embodiment, the axial offset angle θp and the mounting height H weighted by the road surface flatness Wc are estimated, but the present invention is not limited to this. The signal processing unit 4 may replace the equations (1) to (3) and estimate the roll angle θr and the mounting height H weighted by the road surface flatness Wc based on equations (10) to (11) and (3) in the same manner as in the second embodiment.

[0244] (Variant 5) The signal processing unit 4 may estimate the pitch angle θp, the roll angle θr, and the mounting height H weighted based on the road surface flatness Wc. For example, the signal processing unit 4 may calculate the axis offset angle θp and the mounting height H weighted based on the road surface flatness Wc as described above based on equations (1) to (3). Furthermore, the signal processing unit 4 may estimate the roll angle θr and the mounting height H weighted based on the road surface flatness Wc based on equations (10) to (11) and (3). In addition, as the mounting height H, the average value of the values ​​calculated by weighting based on equations (1) to (3) and equations (10) to (11) and (3) may be used.

[0245] [3. Other embodiments]

[0246] As mentioned above, although embodiment of this invention was described, this invention is not limited to the said embodiment, It can implement with various deformation|transformation.

[0247] (3a) In the above embodiment, the radar device 2 transmits radar waves toward the front of the vehicle VH, but the transmission direction of the radar waves is not limited to the front of the vehicle VH. For example, the radar device 2 may be configured to transmit radar waves toward at least one of the front, right front, left front, rear, right rear, left rear, right side, and left side of the vehicle VH.

[0248] (3b) In the above embodiment, the radar device 2 adopts the FMCW method, but the radar method of the radar device 2 is not limited to FMCW, and may be configured to adopt dual-frequency CW, FCM, or pulse. FCM is the abbreviation of Fast-Chirp Modulation.

[0249] (3c) In the above embodiment, an example is shown in which the signal processing unit 4 executes the axis shift estimation process. However, the radar device 2 may execute the axis shift estimation process.

[0250] (3d) The signal processing unit 4 and the method thereof described in the present invention may also be implemented by a special-purpose computer, which is provided by constituting a processor and a memory programmed to execute one or more functions embodied by a computer program. Alternatively, the signal processing unit 4 and the method thereof described in the present invention may also be implemented by a special-purpose computer, which is provided by constituting a processor composed of one or more special-purpose hardware logic circuits. Alternatively, the signal processing unit 4 and the method thereof described in the present invention may also be implemented by one or more special-purpose computers, which are constituted by a combination of a processor and a memory programmed to execute one or more functions and a processor composed of one or more hardware logic circuits. In addition, a computer program may also be stored as an instruction executed by a computer in a non-migratable tangible recording medium that can be read by a computer. The method for realizing the functions of each unit included in the signal processing unit 4 does not necessarily need to include software, and all of its functions may also be implemented using one or more hardware.

[0251] (3e) It is also possible to implement multiple functions of one component in the above-mentioned embodiments by multiple components, or to implement one function of one component by multiple components. In addition, it is also possible to implement multiple functions of multiple components by one component, or to implement one function implemented by multiple components by one component. In addition, a part of the structure of the above-mentioned embodiments may be omitted. In addition, it is also possible to add or replace at least a part of the structure of the above-mentioned embodiments with respect to the structure of other above-mentioned embodiments.

[0252] (3f) In addition to the above-mentioned signal processing unit 4, radar device 2, and vehicle control system 1, the present invention can also be implemented in various ways such as a program for enabling the signal processing unit 4 to function, a non-migrating physical recording medium such as a semiconductor memory recording the program, and an axis offset estimation method.

[0253] In the above embodiment, the vehicle VH corresponds to the mobile body, and the signal processing unit 4 and the estimation unit 46 correspond to the axis deviation estimation device. In addition, S10 corresponds to the processing as the acquisition unit, S20 corresponds to the processing as the extraction unit, S30 and S210 correspond to the processing as the device system coordinate unit, and S30, S220, S230, and S240 correspond to the processing as the estimation unit 46. In addition, S25 corresponds to the processing as the flatness calculation unit, S26 corresponds to the processing as the flatness determination unit, and S27 corresponds to the processing as the weighting processing unit.

Claims

1. An axial deviation estimation device, mounted on a moving object, wherein: The shaft offset estimation device comprises: an acquisition unit configured to acquire, for each of a plurality of reflection points detected by the radar device, reflection point information, the reflection point information including at least a horizontal angle and a vertical angle, and a distance between the radar device and the reflection point, the horizontal angle and the vertical angle being azimuth angles with respect to the reflection point and being obtained based on a direction along a central axis of the radar beam, that is, a beam direction; an extracting unit configured to extract a plurality of road surface reflection points detected by reflection on a road surface from among the plurality of reflection points based at least on the reflection point information; a flatness calculation unit configured to calculate a road surface flatness, the road surface flatness being a numerical value indicating a degree of flatness of the road surface; a flatness determination unit configured to determine whether the road surface is flat based on the road surface flatness; an apparatus coordinate unit configured to determine apparatus coordinates for each of the road surface reflection points based on the reflection point information, the apparatus coordinates being three-dimensional coordinates based on coordinate axes of the radar apparatus; as well as an estimating unit configured to estimate the axis offset angle and the mounting height of the radar device using a relational expression established between at least two unknown parameters including an axis offset angle and a mounting height of the radar device and at least two elements included in the device system coordinates of the road surface reflection point, wherein the axis offset angle is an offset angle of the coordinate axis of the radar device around an object axis, the object axis being one of a horizontal axis and a traveling direction axis as the coordinate axis of the mobile body, The estimation unit comprises: The weighting processing unit is configured to, when it is determined that the road surface is uneven, perform weighting based on the flatness of the road surface using the relational expression to estimate the axis offset angle and the mounting height of the radar device.

2. The axial offset estimation device according to claim 1, wherein: The reflection point information includes a relative speed associated with each of a plurality of reflection points detected by the radar device. The extraction unit acquires the speed of the moving object, sets the acquired speed of the moving object to Cm, sets the relative speed of the multiple reflection points detected by the radar device to q, sets a preset lower limit speed threshold to ε1, sets a preset upper limit speed threshold to ε2, determines the reflection point satisfying ε1≤q / Cm<ε2 among the multiple reflection points detected by the radar device as a stationary reflection point, and extracts at least the reflection point determined as the stationary reflection point among the multiple reflection points detected by the radar device as the road surface reflection point.

3. The axial offset estimation device according to claim 1 or 2, wherein: The horizontal axis and the traveling direction axis are respectively set as object axes, the axis offset angle around the horizontal axis, i.e., the vertical axis offset angle θp, the axis offset angle around the traveling direction axis, i.e., the roll angle θr, and the mounting height H are set as the unknown parameters, and xs, ys, and zs among the elements of the device system coordinates (xs, ys, zs) of the road surface reflection point are set as the three elements included in the device system coordinates, The estimation unit is configured to determine the vertical axis deviation angle θp, the roll angle θr, and the mounting height H by performing calculations based on the relational expression represented by the following equation (12):

4. The axial offset estimation device according to claim 1 or 2, wherein: The estimation unit is configured to estimate the axis offset angle and the mounting height of the radar device using a relationship between two unknown parameters including the axis offset angle and the mounting height of the radar device and two elements included in the device system coordinates of the road surface reflection point.

5. The axial offset estimation device according to claim 4, wherein: The horizontal axis is set as the object axis, the axis offset angle around the horizontal axis, that is, the vertical axis offset angle θp and the mounting height H are set as the unknown parameters, and xs and zs of the elements of the device system coordinates (xs, ys, zs) of the road surface reflection point are set as the two elements included in the device system coordinates, The estimation unit is configured to determine the vertical axis deviation angle θp and the mounting height H by performing calculations based on the relationship represented by the following equations (1) to (3). in, in addition, 6. The axial offset estimation device according to claim 4, wherein: The traveling direction axis is set as the object axis, the axis offset angle around the traveling direction axis, i.e., the roll angle θr and the mounting height H are set as the unknown parameters, and ys and zs of the elements of the device system coordinates (xs, ys, zs) of the road surface reflection point are set as the two elements included in the device system coordinates, The estimation unit is configured to determine the roll angle θr and the mounting height H by performing calculations based on the relationship represented by the following equations (10), (11), and (3). in, in addition, 7. The axial offset estimation device according to claim 1 or 2, wherein: The extraction unit extracts the road surface reflection point when the moving object is in a stable state relative to the road surface.

8. The axial offset estimation device according to claim 1 or 2, wherein: The extraction unit extracts at least one reflection point whose distance from the radar device is less than a distance threshold from the plurality of reflection points as the road surface reflection point based on the plurality of reflection point information detected by the radar device.

9. The axial offset estimation device according to claim 1 or 2, wherein: The extraction unit extracts at least one reflection point whose reflected power of the received intensity contained in the reflection point information is less than a power threshold from the multiple reflection points detected by the radar device as the road surface reflection point based on the multiple reflection point information detected by the radar device.

10. The axial offset estimation device according to claim 1 or 2, wherein: A camera is mounted on the mobile body. The extraction unit obtains the captured image of the camera and estimates the azimuth range of the road surface identified in the captured image, thereby extracting at least one reflection point located within the azimuth range estimated to be the road surface in the captured image from multiple reflection points detected by the radar device as the road surface reflection point.

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