A dynamic calibration algorithm, dynamic calibration device and computer-readable storage medium based on radar track points

Abstract

The present invention relates to a dynamic calibration algorithm, a dynamic calibration device and a computer-readable storage medium based on radar track points. The dynamic calibration algorithm includes S1, fence identification; S2, fence clustering, clustering according to the abscissa difference of the intersection points of suspected fences and the X-axis, and selecting the suspected fence covering the largest number of track points in each category as a temporary fence; S3, fence association; S4, calculating the angle of the mature fence, and calculating the calibration angle through the angle of the mature fence. The present invention provides a dynamic calibration algorithm, a dynamic calibration device and a computer-readable storage medium based on radar track points, which can obtain the radar installation deviation angle in real time for automatic compensation.

Description

Technical Field

[0001] The present invention relates to the technical field of millimeter radar wave applications, and in particular, to a dynamic calibration algorithm, a dynamic calibration device, and a computer-readable storage medium based on radar track points. Background Art

[0002] During the installation of in-vehicle millimeter radar on a vehicle, it is inevitable to have an angular deviation. At the same time, during vehicle driving, there is also a possibility that the in-vehicle millimeter radar has an angular deviation due to reasons such as collision or vibration. The angular deviation will cause a deviation in the radar target angle measurement and reduce the performance of the radar.

[0003] To solve this problem, this paper proposes a dynamic calibration angle acquisition algorithm based on multi-fence processing, which can automatically obtain the radar installation offset angle in real time for automatic compensation. Summary of the Invention

[0004] In view of the above problems of the prior art, the present invention proposes a dynamic calibration algorithm based on radar track points, which can obtain the radar installation offset angle in real time for automatic compensation.

[0005] Specifically, the present invention proposes a dynamic calibration algorithm based on radar track points, including the steps of:

[0006] S1, fence identification;

[0007] S11, obtaining N track points after the radar tracking of this frame is completed;

[0008] S12, selecting two track points to form a straight line, obtaining a first set of track points whose perpendicular distance to the straight line is less than a set first threshold and a second set of track points less than a set second threshold, and judging whether the straight line is a suspected fence according to the number of track points in the first set of track points and the second set of track points;

[0009] S13, repeatedly executing steps S11 to S12 to obtain all suspected fences;

[0010] S2, fence clustering, clustering according to the positional relationship between the suspected fences to obtain temporary fences;

[0011] S3, fence association, associating the temporary fences obtained in this frame with the temporary fences obtained in the previous frame to obtain mature fences;

[0012] S4, calculating the angle of the mature fence, and calculating the calibration angle through the angle of the mature fence.

[0013] According to an embodiment of the present invention, step S12 includes the steps of:

[0014] S121, Select two track points n(X n , Y n ), m(X m , Y m );

[0015] S122, Calculate the slope K mn of the track points n and m, and obtain the straight line m_n connecting the track points n and m, expressed as Y = K mn * X + B;

[0016] S123, Calculate the perpendicular distance L o , Y o ) of any track point o(X o ;

[0017]

[0018] S124, Obtain the first set of track points where the perpendicular distance to the straight line m_n is less than the set first threshold. Let the number of track points included in the first set of track points be N x , and let the average speed of the track points included in the first set of track points be V; then

[0019] S125, Obtain the second set of track points where the perpendicular distance to the straight line m_n is less than the set second threshold. The first threshold is less than the second threshold. Let the number of track points included in the second set of track points be N y ;

[0020] S126, If N x is greater than the set third threshold and N x / N y >= Q1, then determine that the straight line m_n is a suspected fence, where Q1 is a preset value;

[0021] S127, Record the attributes of the suspected fence, including the slope K, intercept B, abscissa X of the intersection with the X-axis, average speed V, and number of points N.

[0022] According to an embodiment of the present invention, step S124 further includes equally dividing and counting all N track points according to the distance to the radar; step S126 further includes, if N x is greater than the set fourth threshold and N x / N y >= Q2, and the numerical values of each equal division count are greater than the preset values of each division, then determine that the straight line m_n is a suspected fence, where Q2 is a preset value.

[0023] According to an embodiment of the present invention, in step 121, select two track points n(Xn , Y n ), m(X m , Y m ), and abs(Y n ) > abs(Y m ).

[0024] According to an embodiment of the present invention, step S2 includes the steps of:

[0025] S21, clustering according to the abscissa difference of the intersection points of the suspected fences with the X-axis; or clustering according to the difference between the abscissa difference of the intersection points of the suspected fences with the X-axis and the slope K of the suspected fences;

[0026] S22, selecting the suspected fence covering the largest number of track points as the temporary fence in each cluster; or taking the mean value of the slopes K and the intersections with the X of all the suspected fences in the cluster as the temporary fence.

[0027] According to an embodiment of the present invention, step S21 includes the steps of:

[0028] S211, setting the nth suspected fence among all suspected fences as Y n = K n * X n + B n ;

[0029] S212, calculating the abscissa of the intersection point of the nth suspected fence with the X-axis:

[0030]

[0031] S213, clustering those suspected fences whose abscissa differences of the intersection points with the X-axis are less than a set fifth threshold into one category; or clustering those suspected fences whose abscissa differences of the intersection points with the X-axis are less than a set sixth threshold and the difference between the slope K of the suspected fences is less than a seventh threshold.

[0032] According to an embodiment of the present invention, step S3 for associating the temporary fence obtained in this frame and the temporary fence obtained in the previous frame to obtain a mature fence includes the following steps:

[0033] S31, associating according to the abscissa difference of the intersection points of the temporary fence obtained in this frame and the temporary fence obtained in the previous frame with the X-axis;

[0034] S32, repeatedly executing step S31 to obtain a mature fence according to the continuous association quantity.

[0035] According to an embodiment of the present invention, step S31 includes the steps of:

[0036] S311, setting the attribute of the temporary fence obtained in this frame as Kl+1 , B l+1 , V l+1 , X l+1 , N l+1 , the attribute of the temporary fence obtained in the previous frame is K l , B l , V l , X l , N l ;

[0037] S312, if abs(X l+1 - X l ) < the eighth threshold value, it is determined that the temporary fence of this frame is successfully associated.

[0038] According to an embodiment of the present invention, step S31 further includes the step of:

[0039] S313, perform weighted filtering on the attributes of the successfully associated temporary fence.

[0040] According to an embodiment of the present invention, the step S32 includes: if the temporary fence fails to be associated successfully for R1 consecutive frames, delete the temporary fence; if the temporary fence is associated successfully for R2 consecutive frames, convert the temporary fence into a mature fence; if the mature fence fails to be associated successfully for R3 consecutive frames, delete the mature fence; where R1, R2, and R3 are set values.

[0041] According to an embodiment of the present invention, step S4 includes:

[0042] S41, adopt a continuous inter - frame sampling method to extract the mature fence, retain the last mature fence, and record the continuous extraction frame number FrameNum;

[0043] S42, calculate the current angle AngTemp of the last mature fence n ;

[0044] S43, repeatedly execute steps S41 to S42, record the effective times AngNum of the current angle AngTemp, and the continuous invalid times invalidn;

[0045] S44, determine whether the continuous extraction frame number, effective times, and invalid times reach the set quantity, and calculate the mean value and deviation of the current angle of the mature fence or end this calculation according to the judgment result;

[0046] Judge whether the mean value and deviation of the current angle meet the set conditions. If so, use the current angle as the calibration angle; if not, end this calculation.

[0047] According to an embodiment of the present invention, in step S42, if the abscissa X of the intersection point of the mature fence and the X-axis l <is less than the ninth threshold and the slope K l the absolute value abs(K l ) is greater than the tenth threshold, then calculate the current angle AngTemp of the mature fence as:

[0048] AngTemp = 90 - atand(K l );

[0049] And / or, in S44, if the continuous invalid times invalidn reach the eleventh threshold, end the calculation and clear the valid times AngNum; if FrameNum reaches the upper limit set value, end the current calculation and clear the valid times AngNum;

[0050] And / or, in S44, if the valid times AngNum reach the twelfth threshold, let the number of times of the valid times AngNum be β, then calculate the mean value μ and the deviation δ of the current angle AngTemp of the mature fence,

[0051]

[0052] If the mean value μ < the thirteenth threshold and the deviation δ < the fourteenth threshold, then use the mean value μ as the calibration angle; otherwise, end the current calculation and clear the valid times AngNum.

[0053] The present invention also provides a dynamic calibration device based on radar track points, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the foregoing dynamic calibration algorithm are implemented.

[0054] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the foregoing dynamic calibration algorithm are implemented.

[0055] A dynamic calibration algorithm based on radar track points provided by the present invention can calculate the fence deflection angle through fence identification, fence clustering, and fence filtering, and can obtain the radar installation deflection angle in real time for automatic compensation..

[0056] It should be understood that the foregoing general description and the following detailed description of the present invention are both exemplary and explanatory, and are intended to provide further explanation of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are included to provide a further explanation of the present invention, and they are incorporated and constitute a part of this application. The accompanying drawings illustrate embodiments of the present invention and, together with this specification, serve to explain the principles of the present invention.

[0058] In the accompanying drawings:

[0059] Figure 1 The flowchart of the dynamic calibration algorithm based on radar track points according to an embodiment of the present invention is shown.

[0060] Figure 2 The schematic diagram showing that the track points in an embodiment of the present invention are concentrated around a straight line Figure 1 .

[0061] Figure 3 The schematic diagram showing that the track points in an embodiment of the present invention are concentrated around a straight line Figure 2 .

[0062] Figure 4 The schematic diagram of the fence clustering according to an embodiment of the present invention is shown.

[0063] Figure 5 The normal distribution diagram of the statistical characteristics of the calibration angle according to an embodiment of the present invention is shown. Detailed Embodiments

[0064] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments may be combined with each other.

[0065] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way restricts this application and its application or use. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application.

[0066] It should be noted that the terms used here are only for describing the specific embodiments and are not intended to limit the exemplary embodiments according to this application. As used here, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or their combinations.

[0067] Unless otherwise specifically stated, the relative arrangements, numerical expressions, and numerical values of the components and steps set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the said technologies, methods, and devices should be regarded as part of the specification. In all the examples shown and discussed herein, any specific values should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0068] In the description of the present application, it should be understood that the orientation or positional relationships indicated by orientation words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal", and "top, bottom" are generally based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Without contrary instructions, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and thus should not be construed as limiting the protection scope of the present application; the orientation words "inside, outside" refer to the inside and outside relative to the contour of each component itself.

[0069] In addition, it should be noted that the use of words such as "first", "second", etc. to limit components is only for the convenience of distinguishing the corresponding components. Without additional statements, the above words have no special meanings, and thus should not be construed as limiting the protection scope of the present application. In addition, although the terms used in the present application are selected from well-known and commonly used terms, some of the terms mentioned in the specification of the present application may be selected by the applicant according to his or her judgment, and their detailed meanings are described in the relevant parts of the description herein. In addition, it is required to understand the present application not only through the actual terms used, but also through the meaning implied by each term.

[0070] Figure 1 The flowchart of the dynamic calibration algorithm based on radar track points according to an embodiment of the present invention is shown. As shown in the figure, a dynamic calibration algorithm based on radar track points includes the steps:

[0071] S1, fence identification;

[0072] S11, obtaining N track points after the radar tracking of the current frame is completed;

[0073] S12. Select two waypoints to form a straight line, obtain all the first set of waypoints whose perpendicular distance to the straight line is less than a set first threshold and the second set of waypoints whose perpendicular distance is less than a set second threshold, and determine whether the straight line is a suspected fence according to the number of waypoints in the first set of waypoints and the second set of waypoints;

[0074] S13. Repeat steps S11 to S12 to obtain all suspected fences. Each suspected fence is a straight line formed by two waypoints.

[0075] S2. Fence clustering. Cluster according to the positional relationship between the suspected fences to obtain temporary fences;

[0076] S3. Fence association. Associate the temporary fences obtained in this frame with the temporary fences obtained in the previous frame to obtain mature fences;

[0077] S4. Calculate the angle of the mature fence, and calculate the calibration angle through the angle of the mature fence.

[0078] Figure 2 Shows the schematic of waypoints in a track point set of an embodiment of the present invention concentrated around a straight line Figure 1 . Figure 3 Shows the schematic of waypoints in a track point set of an embodiment of the present invention concentrated around a straight line Figure 2 . Preferably, step S12 includes the steps:

[0079] S121. Select two waypoints n(X n ,Y n ) and m(X m ,Y m ) from N waypoints;

[0080] S122. Calculate the slope of the straight line m_n formed by waypoints n and m as K mn , and the slope Obtain the straight line m_n connecting waypoints n and m expressed as Y = K mn *X + B, where B is the intercept;

[0081] S123. Calculate the perpendicular distance L o between any waypoint o(X o ) in N waypoints and the straight line m_n; o ;

[0082]

[0083] S124. As Figure 2 and Figure 3 shown, obtain all the perpendicular distances L o to the straight line m_n 201The first set of track points less than the set first threshold Val1. Let the number of track points 202 included in the first set of track points be N x . The number of track points 202 included in the first set of track points refers to all track points 202 included within a distance of the first threshold Val1 around the straight line m_n 201, which is represented in the figure by the track points 202 included between the left and right dotted lines closest to the straight line m_n 201. Figure 2 The number of track points 202 included in the first set of track points in x = 8, Figure 3 The number of track points 202 included in the first set of track points in x = 8. Let the average speed V of the track points included in the first set of track points 202; then

[0084] S125, obtain all the perpendicular distances L from the straight line m_n 201 o The second set of track points with a perpendicular distance L less than the set second threshold Val2 from the straight line m_n 201. The first threshold Val1 is less than the second threshold Val2. Let the number of track points 202 included in the second set of track points be N y . The number of track points 202 included in the second set of track points refers to all track points 202 included within a distance of the second threshold Val2 around the straight line m_n 201, which is represented in the figure by the track points 202 included between the left and right dotted lines far from the straight line m_n201. Figure 2 The number of track points 202 included in the second set of track points in y = 11, Figure 3 The number of track points 202 included in the first set of track points in y = 17.

[0085] S126, if N x is greater than the set third threshold Val3 and N x / N y >= Q1, then determine that the straight line m_n is a suspected fence, where Q1 is a preset value and can be determined according to experience. Assume that the third threshold Val3 is 6 and Q1 is 0.7. According to Figure 2 , N x = 8 and N y = 11, meeting the above conditions, then determine that the straight line m_n 201 is a suspected fence. According to Figure 3 , N x = 8 and N y = 17, N x / N yIf it is less than 0.7 and does not meet the above conditions, it is determined that the straight line m_n 201 is not a suspected fence. By the above method, by comparing the ratio of the number of track points 202 within the first threshold Val1 and the second threshold Val2, it is possible to prevent Figure 3 the misjudgment of the situation with many non-fence miscellaneous points shown in Figure 3 as a suspected fence. The type of suspected fence obtained through steps S121 to S126 is a continuous fence.

[0086] S127, record the attributes of the suspected fence, including the slope K, the intercept B, the abscissa X of the intersection with the X-axis, the average speed V, and the number of points N.

[0087] Optionally, step S124 further includes equally dividing and counting all N track points according to the distance to the radar; step S126 further includes that if N x is greater than the set fourth threshold Val4 and N x / N y ≥Q2, and the numerical value of each segmented count is greater than the preset value of each segment, then it is determined that the straight line m_n is a suspected fence, where Q2 is a preset value and can be set according to experience. Specifically, record all N track points for segmented counting. The distance from the track point to the radar is R, where:

[0088] 0≤R<50m, the count value is N1;

[0089] 50m≤R<100m, the count value is N2;

[0090] 100m≤R<150m, the count value is N3;

[0091] 150m≤R<200m, the count value is N4;

[0092] 200m≤R<250m, the count value is N5.

[0093] If N x is greater than the set fourth threshold Val4, which is used to ensure that there are sufficient track points. And N x / N y ≥Q2, which is used to ensure that the track points are concentrated enough. And the numerical values N1 to N5 of each segmented count are greater than the preset values of each segment, which is used to ensure that the track points in each segment are evenly distributed. If the foregoing conditions are met, it is determined that the straight line m_n is a suspected fence, and the type of this suspected fence is a dot-shaped fence.

[0094] It is easy to understand that the suspected fence includes at least a continuous fence and a dot-shaped fence, which are obtained by the foregoing two methods respectively. In actual use, any one of the methods can be used to obtain the suspected fence, or both methods can be used simultaneously, as long as the suspected fence obtained by any one of the methods is satisfied.

[0095] Preferably, in step 121, two waypoints n(X n , Y n ) and m(X m , Y m ) are selected, and abs(Y n ) > abs(Y m ). To avoid repeated operations, it can save half of the computational workload.

[0096] Preferably, step S2 includes the steps of:

[0097] S21, clustering according to the abscissa difference of the intersection points of the suspected fences with the X-axis; or clustering according to the difference between the abscissa difference of the intersection points of the suspected fences with the X-axis and the slope K of the suspected fences;

[0098] S22, selecting the suspected fence covering the largest number of waypoints in each cluster as the temporary fence; or taking the mean value of the slopes K and the intersection points with the X of all suspected fences in the cluster as the temporary fence.

[0099] Preferably, step S21 includes the steps of:

[0100] S211, setting the nth suspected fence among all suspected fences as Y n = K n * X n + B n ;

[0101] S212, calculating the abscissa of the intersection point of the nth suspected fence with the X-axis:

[0102]

[0103] S213, clustering those suspected fences whose abscissa differences of the intersection points with the X-axis are less than the set fifth threshold into one category; or clustering those suspected fences whose abscissa differences of the intersection points with the X-axis are less than the set sixth threshold and the difference between the slope K of the suspected fences is less than the seventh threshold.

[0104] Figure 4The figure shows a schematic diagram of fence clustering according to an embodiment of the present invention. As shown in the figure, it is assumed that after completing step S1, 6 suspected fences are obtained, namely straight lines a, b, c, d, e, and f. The intersections of each straight line with the X-axis are Xa, Xb, Xc, Xd, Xe, and Xf, and the corresponding abscissas of the intersections are Xa', Xb', Xc', Xd', Xe', and Xf'. If Xa - Xb < the fifth threshold Val5, then a and b are clustered into one category. By analogy, straight lines a, b, and c are clustered into one category; the intersections of straight lines d, e, and f with the X-axis are far from the intersections of straight lines a, b, and c with the X-axis, greater than the fifth threshold Val5, so straight lines d, e, and f cannot be clustered with straight lines a, b, and c. If Xd - Xe < for straight lines d, e, and f, and Xe - Xf < for straight lines d, e, and f, then straight lines d, e, and f are clustered into another category. In each category, select the suspected fence with the largest number of associated points as the output of the fence clustering result. For example, if among the three suspected fences a, b, and c, the number of associated points of straight line b is the largest, then use straight line b as the temporary fence after clustering the three fences a, b, and c; if among straight lines d, e, and f, the number of associated points of straight line e is the largest, then use straight line e as the temporary fence after clustering the three suspected fences d, e, and f. Through the fence clustering step, these 6 suspected fences are finally clustered into two temporary fences b and e.

[0105] By way of example and not limitation, clustering can also be performed based on the difference in the abscissa of the intersection of straight lines a, b, c, d, e, and f with the X-axis and the difference in their respective slopes K. Take the mean of the slopes K and the intersections with the X of all suspected fences in each cluster as the temporary fence, and the specific implementation method will not be elaborated.

[0106] Preferably, step S3 for associating the temporary fence obtained in this frame with the temporary fence obtained in the previous frame to obtain a mature fence includes the following steps:

[0107] S31, perform association based on the difference in the abscissa of the intersection of the temporary fence obtained in this frame and the temporary fence obtained in the previous frame with the X-axis;

[0108] S32, repeatedly execute step S31 to obtain a mature fence according to the continuous association quantity.

[0109] Preferably, step S31 includes the steps:

[0110] S311, set the attributes of the temporary fence obtained in this frame as slope K l+1 , intercept B l+1 , average speed V l+1 , abscissa X of the intersection with the X-axis l+1 , number of points N l+1 , and set the attributes of the temporary fence obtained in the previous frame as slope K l , intercept B l , average speed Vl , the abscissa X of the intersection point with the X-axis l , the number of points N l ;

[0111] S312, if abs(X l+1 -X l ) < the eighth threshold value Val6, it is determined that the temporary fence association of this frame is successful.

[0112] Preferably, step S31 further includes the step:

[0113] S313, perform weighted filtering on the attributes of the successfully associated temporary fence. In this embodiment, the weighted filtering formula is as follows:

[0114] Intermediate parameter

[0115] The abscissa of the intersection point with the X-axis

[0116] Slope

[0117] Intercept B l =-X l *K l ;

[0118] Average speed

[0119] Since the road conditions encountered by the vehicle during driving are relatively complex, there may be other track points misjudged as temporary fences in the track point data obtained by each radar detection. Therefore, step S3 performs filtering and association operations to filter out the temporary fences that do not meet the requirements and obtain mature fences for subsequent fence angle extraction.

[0120] Preferably, step S32 includes:

[0121] If the temporary fence fails to be associated successfully for R1 consecutive frames, delete the temporary fence; if the temporary fence is associated successfully for R2 consecutive frames, convert the temporary fence into a mature fence; if the mature fence fails to be associated successfully for R3 consecutive frames, delete the mature fence;

[0122] Where R1, R2, and R3 are set values, set according to experience. It can be set that R1 = 2, R2 = 3, R3 = 5. If the temporary fence fails to be associated successfully for 2 consecutive frames, delete the temporary fence; if the temporary fence is associated successfully for 3 consecutive frames, convert the temporary fence into a mature fence; if the mature fence fails to be associated successfully for 5 consecutive frames, delete the mature fence. By way of example and not limitation, R1, R2, and R3 can also be set to other values.

[0123] Preferably, step S4 includes:

[0124] S41. Take continuous inter-frame sampling to extract mature fences, retain the last mature fence, and record the number of consecutive frames extracted, FrameNum;

[0125] S42. Calculate the current angle, AngTemp, of the last mature fence;

[0126] S43. Repeat steps S41 to S42, record the number of valid times, AngNum, of the current angle AngTemp, and the consecutive number of invalid times, invalidn;

[0127] S44. Determine whether the number of consecutive frames extracted, the number of valid times, and the number of invalid times reach the set quantities, and calculate the mean and deviation of the current angle of the mature fence or end this calculation according to the judgment result;

[0128] Determine whether the mean and deviation of the current angle meet the set conditions. If they meet, use the current angle as the calibration angle; if not, end this calculation.

[0129] Preferably, in step S42, if the abscissa X of the intersection point of the mature fence and the X-axis l <the ninth threshold, Val7, and the slope K l the absolute value of abs(K l ) > the tenth threshold, Val8, then calculate the current angle AngTemp of the mature fence as:

[0130] AngTemp = 90 - atand(K l );

[0131] The function atand is used to calculate the angle of the slope K l ;

[0132] And / or, in step S44, if the consecutive number of invalid times, invalidn, reaches the eleventh threshold, Val9, it means that the continuous interruption time of the mature fence is too long, end the calculation, clear the number of valid times, AngNum, and recalculate the angle of the mature fence based on the mature fence obtained from the next radar detection; if the number of valid times, FrameNum, reaches the upper limit set value, such as 6666 times, it means that the duration of this angle extraction process is too long, end this calculation, clear the number of valid times, AngNum, and recalculate the angle of the mature fence based on the mature fence obtained from the next radar detection;

[0133] And / or, in step S44, if the number of valid times, AngNum, reaches the twelfth threshold, Val10, calculate the mean, μ, and deviation, δ, of the current angle AngTemp of the mature fence;

[0134]

[0135] If the mean value μ < the thirteenth threshold value Val11 and the deviation δ < the fourteenth threshold value Val12, then use the mean value μ as the calibrated angle; otherwise, end this calculation and clear the effective count AngNum to zero.

[0136] Let the ninth threshold value Val7 be 5.5, the tenth threshold value Val8 be 8, the eleventh threshold value Val9 be 80, the twelfth threshold value Val10 be 150, the thirteenth threshold value Val11 be 6, and the fourteenth threshold value Val12 be 1.

[0137] Figure 5 A normal distribution graph showing the statistical characteristics of the calibrated angle of an embodiment of the present invention is shown. The first parameter of the normal distribution is the mean value μ. The mean value μ is the central tendency of the normal distribution, which determines the position of the peak of the curve 501 in the graph. The change of the mean value μ causes the curve 501 to move horizontally along the x-axis. The second parameter of the normal distribution is the deviation δ. The deviation δ or the standard deviation δ is a measure of the variability of the normal distribution, which determines the width of the curve. The change of the deviation δ causes the curve to become narrower or wider and has an inverse proportional effect on the height of the curve. For example, the curve 501 can change from the actual position in the graph to the dotted line position, that is, the curve 501 becomes wider and the peak decreases. Generally, the more stable and continuous the fence sampling is, the smaller the value of the deviation δ will be, and the closer the obtained standard angle will be to the true radar installation angle. When the deviation δ is greater than a certain threshold value, it means that the angle of the mature fence obtained by this sampling is unstable.

[0138] The present invention also provides a dynamic calibration device for radar traces, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any one of the foregoing dynamic calibration algorithms.

[0139] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of any one of the foregoing dynamic calibration algorithms.

[0140] Among them, for the specific implementation manners and technical effects of the dynamic calibration device for radar traces and the computer-readable storage medium, reference can be made to the embodiments of the dynamic calibration algorithm provided by the present invention above, and details are not described herein again.

[0141] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

[0142] The various illustrative logical modules and circuits described in connection with the embodiments disclosed herein can be implemented using a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors cooperating with a DSP core, or any other such configuration.

[0143] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0144] In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or code. The computer-readable medium includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. The storage media may be any available media that can be accessed by a computer. By way of example and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of the medium. As used herein, the terms "disk" and "disc" include compact discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

Claims

1. A dynamic calibration algorithm based on radar track points, comprising the steps: S1, fence identification; S11, obtaining N track points after the radar tracking of the current frame is completed; S12, selecting two track points to form a straight line, obtaining a first set of track points whose perpendicular distance to the straight line is less than a set first threshold and a second set of track points whose perpendicular distance to the straight line is less than a set second threshold, and judging whether the straight line is a suspected fence according to the number of track points in the first set of track points and the second set of track points; S13, repeating steps S11 to S12 to obtain all suspected fences; S2, fence clustering, clustering according to the positional relationship between the suspected fences to obtain temporary fences; S3, fence association, associating the temporary fences obtained in the current frame with the temporary fences obtained in the previous frame to obtain mature fences; S4, calculating the angle of the mature fence, and calculating the calibration angle through the angle of the mature fence.

2. The dynamic calibration algorithm according to claim 1, characterized in that Step S12 includes the steps: S121, Select two track points n(X n , Y n ), m(X m , Y m ); S122, calculate the slope K of the track points n and m mn , and obtain the straight line m_n connecting the track points n and m, expressed as Y = K mn *X + B; S123, calculate the perpendicular distance L between any track point o(X o , Y o ) and the straight line m_n o ; S124, obtain a first set of trajectory points all of which have a perpendicular distance to the straight line m_n less than a set first threshold value. Let the number of trajectory points included in the first set of trajectory points be N x , and let the average speed of the trajectory points included in the first set of trajectory points be V; then S125, obtain a second set of trajectory points whose perpendicular distance to the straight line m_n is less than a set second threshold, where the first threshold is less than the second threshold, and assume the number of trajectory points included in the second set of trajectory points is N y ; S126, if N x is greater than a set third threshold value and N x / N y ≥ Q1, then determine that the straight line m_n is a suspected fence, where Q1 is a preset value; S127, recording the attributes of the suspected fence, including slope K, intercept B, abscissa X of the intersection with the X-axis, average speed V, and number of points N.

3. The dynamic calibration algorithm according to claim 2, wherein Step S124 further includes equally segmenting and counting all N track points according to the distance to the radar; step S126 further includes that if N x is greater than a set fourth threshold value and N x / N y ≥ Q2, and the numerical value of each segmented count is greater than the preset value of each segment, then it is determined that the straight line m_n is a suspected fence, where Q2 is a preset value.

4. The dynamic calibration algorithm according to claim 2, wherein In step 121, select two track points n(X n , Y n ), m(X m , Y m ), and abs(Y n ) > abs(Y m ).

5. The dynamic calibration algorithm according to claim 1, wherein Step S2 includes the steps: S21, clustering according to the difference in the abscissa of the intersection of the suspected fence with the X-axis; or clustering according to the difference in the abscissa of the intersection of the suspected fence with the X-axis and the difference between the slope K of the suspected fence; S22, selecting the suspected fence with the largest number of covered track points in each cluster as the temporary fence; or taking the mean value of the slope K and the intersection with the X of all suspected fences in the cluster as the temporary fence.

6. The dynamic calibration algorithm according to claim 5, wherein Step S21 includes the steps: S211. Let the nth suspected fence among all suspected fences be Y n = K n * X n + B n ; S212, calculating the abscissa of the intersection of the nth suspected fence with the X-axis: S213, clustering those suspected fences whose difference in the abscissa of the intersection with the X-axis is less than a set fifth threshold; or clustering those suspected fences whose difference in the abscissa of the intersection with the X-axis is less than a set sixth threshold and whose difference between the slope K of the suspected fence is less than a seventh threshold.

7. The dynamic calibration algorithm according to claim 1, wherein Step S3 for associating the temporary fences obtained in the current frame with the temporary fences obtained in the previous frame to obtain mature fences includes the following steps: S31, associating according to the difference in the abscissa of the intersection of the temporary fence obtained in the current frame and the temporary fence obtained in the previous frame with the X-axis; S32, repeating step S31, and obtaining mature fences according to the continuous association quantity.

8. The dynamic calibration algorithm according to claim 7, wherein Step S31 includes the steps: S311, set the attributes of the temporary fence obtained in this frame as slope K l+1 , intercept B l+1 , average speed V l+1 , abscissa X of the intersection point with the X-axis l+1 , number of points N l+1 , and the attributes of the temporary fence obtained in the previous frame are slope K l , intercept B l , average speed V l , abscissa X of the intersection point with the X-axis l , number of points N l ; S312, if abs(X l+1 -X l ) is less than the eighth threshold, it is determined that the temporary fence association of this frame is successful.

9. The dynamic calibration algorithm according to claim 8, wherein Step S31 also includes the steps: S313, performing weighted filtering on the attributes of the associated temporary fences.

10. The dynamic calibration algorithm according to claim 7, wherein The said step S32 includes: if the temporary fence fails to be associated successfully for R1 consecutive frames, then deleting the temporary fence; if the temporary fence is associated successfully for R2 consecutive frames, then converting the temporary fence into a mature fence; if the mature fence fails to be associated successfully for R3 consecutive frames, then deleting the mature fence; where R1, R2, and R3 are set values.

11. The dynamic calibration algorithm according to claim 1, wherein Step S4 includes: S41, extracting the mature fence by adopting an inter-frame sampling method for consecutive frames, retaining the last mature fence, and recording the number of consecutive extraction frames FrameNum; S42, calculate the current angle AngTemp of the last mature fence n ; S43. Repeat steps S41 to S42, record the valid count AngNum of the current angle AngTemp, and the consecutive invalid count invalidn; S44. Determine whether the consecutive extraction frame count, valid count, and invalid count reach the set quantities, and calculate the mean and deviation of the current angle of the mature fence or end the current calculation according to the determination result; Determine whether the mean and deviation of the current angle meet the set conditions. If they meet, use the current angle as the calibration angle; if not, end the current calculation.

12. The dynamic calibration algorithm according to claim 11, wherein In step S42, if the abscissa X of the intersection point of the mature fence and the X-axis l is less than the ninth threshold and the absolute value of the slope K l abs(K l ) is greater than the tenth threshold, then calculate the current angle AngTemp of the mature fence as follows: AngTemp = 90 - atan(K l ) and / or, in S44, if the consecutive invalid count invalidn reaches the eleventh threshold, end the calculation and clear the valid count AngNum; if FrameNum reaches the upper limit set value, end the current calculation and clear the valid count AngNum; and / or, in S44, if the valid count AngNum reaches the twelfth threshold, let the count of the valid count AngNum be β, then calculate the mean μ and deviation δ of the current angle AngTemp of the mature fence, if the mean μ < the thirteenth threshold and the deviation δ < the fourteenth threshold, use the mean μ as the calibration angle; if not, end the current calculation and clear the valid count AngNum.

13. A dynamic calibration device based on radar track points, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the steps of the dynamic calibration algorithm according to any one of claims 1-12 when executing the computer program.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program implements the steps of the dynamic calibration algorithm according to any one of claims 1-12 when executed by the processor.

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