Automobile electric tail gate control method and system

Abstract

The invention provides an automobile electric tail gate control method and system. N frames of echo data of an automobile tail gate are periodically collected based on a UWB radar; for each frame of echo data, processing the echo data to obtain a distance-Doppler graph of the echo data; cutting the distance-Doppler map of each frame of echo data by using a preset kicking speed-distance threshold range; selecting each amplitude greater than a preset amplitude threshold value from a plurality of amplitudes of the distance-Doppler map of each frame of cut echo data as each target amplitude of each frame of echo data; according to each target amplitude of each frame of echo data, determining a kick feature of each frame of echo data; performing identification according to the kicking features of each frame of echo data through a pre-trained kicking action identification model to obtain a corresponding identification result; if the identification result is the kicking action, the automobile tail door is controlled to be opened or closed.

Description

Technical Field

[0001] The present invention relates to the field of automobile technology, and more particularly to a method and system for controlling an automobile electric tailgate. Background Art

[0002] At present, cars have become an indispensable means of transportation for people to travel. In order to bring greater convenience to people, many manufacturers have added electric tailgates to their cars.

[0003] At present, there are two ways to open and close the electric tailgate of a car. One is a control structure based on the traditional manual button-type opening or closing. This control structure requires a person to manually press a button to open or close. When the person's hands are not free, this control method is not applicable and is not convenient enough. The other is a capacitive control structure. This structure is generally placed under the rear bumper of the vehicle. A capacitive electric field emitting electrode is placed at two positions according to a strict installation position and spacing. When an action occurs in the detection area, the capacitor will produce a specific change. According to a certain change rule, it can be determined whether the action is a kicking action, and then the signal quantity can be used to achieve the purpose of controlling the car tailgate. However, this method is easily affected by factors such as temperature, humidity or dust, resulting in insensitive control and false triggering. Summary of the invention

[0004] In view of this, the present invention provides a method and system for controlling an electric tailgate of an automobile, aiming to improve the control accuracy of the electric tailgate of the automobile.

[0005] A first aspect of the present application provides a method for controlling an electric tailgate of an automobile, the method comprising:

[0006] Periodically collect N frames of echo data from the tailgate of the car based on UWB radar;

[0007] For each frame of the echo data, the echo data is processed to obtain a range-Doppler map of the echo data;

[0008] Using a preset kicking speed-distance threshold range, the distance-Doppler graph of each frame of the echo data is clipped; wherein the clipped distance-Doppler graph includes multiple amplitudes;

[0009] Selecting each amplitude greater than a preset amplitude threshold from a plurality of amplitudes of the range-Doppler graph of each frame of echo data after clipping as each target amplitude of the echo data of each frame;

[0010] determining a kick feature of each frame of echo data according to each target amplitude of each frame of echo data;

[0011] The kicking action recognition model is used to recognize the kicking features of the echo data of each frame to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network using real kicking training data and non-real kicking training data;

[0012] If the recognition result is a kicking action, the tailgate of the vehicle is controlled to be opened or closed.

[0013] Optionally, the preset kicking speed-distance threshold range includes a kicking speed threshold range and a kicking distance threshold range;

[0014] The method of cutting the distance-Doppler graph of each frame of the echo data by using the preset kicking speed-distance threshold range comprises:

[0015] Determine the row index number of the distance-Doppler graph of each frame of the echo data according to the kick distance threshold range;

[0016] Determine the column index number of the range-Doppler graph of each frame of the echo data according to the kicking speed threshold range;

[0017] For each frame of the range-Doppler map of the echo data, the range-Doppler map of the echo data is cropped according to the row index number and the column index number of the range-Doppler map of the echo data.

[0018] Optionally, determining the row index number of the distance-Doppler map of each frame of the echo data according to the kick distance threshold range includes:

[0019] For each frame of the range-Doppler map of the echo data, according to the kicking distance threshold range, determining the maximum value and the minimum value of the kicking action distance from the range-Doppler map of the echo data;

[0020] Determine the maximum row number of the characteristic value in the distance dimension of the range-Doppler map according to the maximum value of the kicking action distance and the distance resolution;

[0021] Determine the minimum row number of the characteristic value in the distance dimension of the range-Doppler map according to the minimum value of the kicking action distance and the distance resolution;

[0022] A row index number of the range-Doppler map is determined according to the maximum row number and the minimum row number.

[0023] Optionally, the kicking speed threshold range includes a positive threshold range of the speed dimension and a negative threshold range of the speed dimension;

[0024] Determining the column index number of the distance-Doppler graph of each frame of the echo data according to the kicking speed threshold range includes:

[0025] For each frame of the distance-Doppler graph of the echo data, the distance-Doppler graph of the echo data is divided into two equal columns, with the vertical axis as the y-axis and the rows as the x-axis to construct a two-dimensional array in a spatial xy coordinate system;

[0026] The two-dimensional array is processed according to the positive threshold range of the velocity dimension and the negative threshold range of the velocity dimension to obtain a column index number of the range-Doppler map of the echo data.

[0027] Optionally, the processing of the two-dimensional array according to the positive threshold range of the velocity dimension and the negative threshold range of the velocity dimension to obtain the column index number of the range-Doppler map includes:

[0028] Determining a maximum value of the first kicking motion speed and a minimum value of the first kicking motion speed from the two-dimensional array according to the positive threshold range of the speed dimension;

[0029] According to the negative threshold range of the speed dimension, determining the maximum value and the minimum value of the second kicking action speed from the two-dimensional array;

[0030] Determine a first maximum column number of a characteristic value within a positive threshold range of a velocity dimension of the two-dimensional array according to a maximum value and a velocity resolution of the first kicking motion velocity, and determine a first minimum column number of a characteristic value within a positive threshold range of a velocity dimension of the two-dimensional array according to a minimum value and a velocity resolution of the first kicking motion velocity;

[0031] Determine a second maximum column number of the eigenvalues ​​within the negative threshold range of the velocity dimension of the two-dimensional array according to the maximum value of the second kicking motion speed and the velocity resolution, and determine a second minimum column number of the eigenvalues ​​within the negative threshold range of the velocity dimension of the two-dimensional array according to the minimum value of the second kicking motion speed and the velocity resolution;

[0032] A column index number of the range-Doppler map is determined according to the first maximum column number, the second maximum column number, the first minimum column number, and the second minimum column number.

[0033] Optionally, determining the kicking feature of each frame of the echo data according to each target amplitude of each frame of the echo data includes:

[0034] Calculate the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of each frame of echo data according to each target amplitude of each frame of echo data;

[0035] For each frame of the echo data, the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of the echo data are spliced ​​to obtain the kicking feature of the echo data.

[0036] Optionally, the step of training a neural network using real kicking training data and non-real kicking training data to obtain a kicking action recognition model includes:

[0037] Acquire real kick training data and non-real kick training data; wherein the real kick training data includes N frames of first historical echo data with kicking action; the non-real kick training data includes N frames of second historical echo data without kicking action;

[0038] Processing each frame of the first historical echo data to obtain a first historical range-Doppler map of each frame of the first historical echo data, and processing each frame of the second historical echo data to obtain a second historical range-Doppler map of each frame of the second historical echo data;

[0039] Using a preset kicking speed-distance threshold range, the first historical distance-Doppler graph of each frame of the first historical echo data and the second historical distance-Doppler graph of each frame of the second historical echo data are respectively clipped; wherein the clipped first historical distance-Doppler graph includes a plurality of first historical amplitudes, and the clipped second distance-Doppler graph includes a plurality of second historical amplitudes;

[0040] From the plurality of first historical amplitudes of the first historical range-Doppler of each frame of the first historical echo data after trimming, selecting each first historical amplitude greater than a preset threshold as each target first historical amplitude of each frame of the first historical echo data;

[0041] From the plurality of second historical amplitudes of the second historical range-Doppler of each frame of the cropped second historical echo data, selecting each second historical amplitude greater than the preset threshold as each target second historical amplitude of each frame of the second historical echo data;

[0042] Determining a first historical kick feature of each frame of the first historical echo data according to each target first historical amplitude of each frame of the first historical echo data;

[0043] Determining a second historical kick feature of each frame of the second historical echo data according to each target second historical amplitude of each frame of the second historical echo data;

[0044] The first historical kicking features of each frame of the first historical echo data and the second historical kicking features of each frame of the second historical echo data are used to train a neural network to obtain a kicking action recognition model.

[0045] A second aspect of the present application provides a vehicle tailgate control system, the system comprising:

[0046] A periodic acquisition unit, used for periodically acquiring N frames of echo data of the tailgate of a car based on the UWB radar;

[0047] A first processing unit, configured to process the echo data for each frame of the echo data to obtain a range-Doppler map of the echo data;

[0048] A first clipping unit is used to clip the distance-Doppler graph of each frame of the echo data using a preset kicking speed-distance threshold range; wherein the clipped distance-Doppler graph includes multiple amplitudes;

[0049] A first selection unit is used to select each amplitude greater than a preset amplitude threshold from multiple amplitudes of the range-Doppler map of each frame of echo data after trimming as each target amplitude of each frame of the echo data;

[0050] A first determining unit, configured to determine a kicking feature of each frame of the echo data according to each target amplitude of each frame of the echo data;

[0051] A recognition unit, used for recognizing the kicking features of the echo data of each frame by using a pre-trained kicking action recognition model to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network by a training unit using real kicking training data and non-real kicking training data;

[0052] A control unit is used to control the opening or closing of the tailgate of the automobile if the recognition result is a kicking action.

[0053] Optionally, the preset kicking speed-distance threshold range includes a kicking speed threshold range and a kicking distance threshold range, and the first clipping unit includes:

[0054] A second determining unit, configured to determine a row index number of a range-Doppler graph of each frame of the echo data according to the kick distance threshold range;

[0055] A third determining unit, configured to determine a column index number of a range-Doppler graph of each frame of the echo data according to the kicking speed threshold range;

[0056] The first cropping subunit is used to crop the range-Doppler map of the echo data of each frame according to the row index number and the column index number of the range-Doppler map of the echo data.

[0057] Optionally, the second determining unit includes:

[0058] a fourth determining unit, configured to determine, for each frame of the range-Doppler map of the echo data, a maximum value of the kicking action distance and a minimum value of the kicking action distance from the range-Doppler map of the echo data according to the kicking distance threshold range;

[0059] a fifth determining unit, configured to determine a maximum row number of a characteristic value in a distance dimension of the range-Doppler map according to a maximum value of the kicking action distance and a distance resolution;

[0060] a sixth determining unit, configured to determine a minimum row number of characteristic values ​​in the distance dimension of the range-Doppler map according to the minimum value of the kicking action distance and the distance resolution;

[0061] A seventh determining unit is used to determine a row index number of the range-Doppler map according to the maximum row number and the minimum row number.

[0062] The embodiment of the present invention provides a method and system for controlling an electric tailgate of an automobile. A neural network is trained by using real kick training data and non-real kick training data to obtain a kick recognition model that can recognize kicking actions. When collecting N frames of echo data of the tailgate of an automobile based on a UWB radar, each frame of the collected echo data is processed to obtain a distance-Doppler graph of each frame of echo data, and the distance-Doppler graph of each frame of echo data is cropped according to a preset kick speed-distance threshold range to remove unnecessary background in the distance-Doppler graph of each frame of echo data. Information can be obtained, redundancy in the distance-Doppler map can be reduced, and if a kicking action really exists at present, the features of the kicking action in the distance-Doppler map can be highlighted; the kicking features are constructed by using the cropped distance-Doppler map of each frame of echo data, and a pre-trained kicking action recognition model is used to identify whether there is a kicking action at present according to the constructed kicking features. It can be seen that the present invention does not need to place a capacitive electric field emitting electrode at two positions according to a strict installation position and spacing, and can ensure the accuracy of kicking action recognition in various environments, and has strong anti-interference ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0064] Figure 1 A schematic flow chart of a method for controlling an electric tailgate of an automobile provided by an embodiment of the present invention;

[0065] Figure 2 A flowchart of a method for training a kicking action recognition model provided by an embodiment of the present invention;

[0066] Figure 3 A schematic structural diagram of an automobile electric tailgate control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0069] See also Figure 1 , shows a flow chart of a method for controlling an electric tailgate of an automobile provided by an embodiment of the present invention, the method specifically comprising the following steps:

[0070] S101: periodically collecting N frames of echo data of the car based on the UWB radar.

[0071] In the embodiment of the present invention, the period of a complete kicking action is usually longer than one frame of echo data, so N frames of echo data and their timestamps of the tailgate of the car can be periodically collected by ultra-wide band (UWB) radar, where N is an integer greater than 1.

[0072] It should be noted that a complete kicking action may be: the UBW radar kicks from left to right, or from right to left, or from directly below the radar to directly above the radar, which is not limited in this embodiment of the present invention.

[0073] S102: For each frame of the echo data, the echo data is processed to obtain a range-Doppler map of the echo data.

[0074] In the specific process of executing step S102, for each frame of first echo data, a range-Doppler fast Fourier transform may be performed on the first echo data to obtain a first range-Doppler map of the echo data.

[0075] It should be noted that the data form corresponding to the range-Doppler diagram of each frame of echo data can be mathematically expressed as an m*n two-dimensional matrix, where each value in the matrix represents the amplitude of a "grid", m represents the total number of "grids" in the distance dimension, n represents the total number of "grids" in the velocity dimension, and a "grid" represents a specific resolution size.

[0076] It is worth noting that when the waveform and various software and hardware of the UBW radar are certain, the distance resolution and velocity resolution of the echo data collected by the UBW radar are also certain; for example, if the velocity resolution is determined to be DopplerRes, then n×DopplerRes can represent its maximum detection speed. Similarly, if the distance resolution is determined to be RangeRes, then the maximum detection distance can be expressed as n×RangeRes.

[0077] S103: using a preset kicking speed-distance threshold range, respectively cropping the distance-Doppler graph of each frame of the echo data; wherein the cropped distance-Doppler graph includes a plurality of amplitudes.

[0078] In an embodiment of the present invention, the applicant has found through research that a kicking action has a certain movement trend, and a kicking action is usually within a certain speed and distance range. Therefore, a corresponding kicking speed-distance threshold range can be set in advance, wherein the kicking speed-distance threshold range can include a kicking speed threshold range and a kicking distance threshold range; the pre-set kicking speed threshold range and kicking distance threshold range can be used to crop the distance-Doppler map of each frame of echo data to remove unnecessary background information in the distance-Doppler map of each frame of echo data.

[0079] It should be noted that unnecessary background information can be interpreted as: signal data outside the range of the kicking action. Because the UWB radar can detect speed and distance within a certain range, the distance-Doppler map may include some signal data outside the range of the kicking action. For example, the UWB radar here can detect a maximum speed of 10m / s and a distance of 10m. The echo data collected by the UBW radar after 2DFFT is a 10x10 matrix. The 10 grids in the row direction represent 10m, that is, one grid represents 1m. However, the kicking action may only be 1-2m (within the kicking threshold range) of the radar. Therefore, the distance-Doppler map can be cropped by the kicking speed threshold range and the kicking distance threshold range to remove unnecessary background information in the distance-Doppler map.

[0080] Optionally, the process of cropping the distance-Doppler map of each frame of the echo data using a preset kicking speed-distance threshold range can be specifically as follows: determining the row index number of the distance-Doppler map of each frame of the echo data according to the kicking distance threshold range; determining the column index number of the distance-Doppler map of each frame of the echo data according to the kicking speed threshold range; and for each frame of the distance-Doppler map of the echo data, cropping the distance-Doppler map of the echo data according to the row index number and column index number of the distance-Doppler map of the echo data.

[0081] As an implementation method of an embodiment of the present invention, the process of determining the row index number of the distance-Doppler map of each frame of the echo data according to the kick distance threshold range can be specifically as follows: for each frame of the distance-Doppler map of the echo data, according to the kick distance threshold range, determine the maximum value of the kicking action distance and the minimum value of the kicking action distance from the distance-Doppler map of the echo data; according to the maximum value of the kicking action distance and the distance resolution, determine the maximum row number of the eigenvalue on the distance dimension of the distance-Doppler map; according to the minimum value of the kicking action distance and the distance resolution, determine the minimum row number of the eigenvalue on the distance dimension of the distance-Doppler map; according to the maximum row number and the minimum row number, determine the row index number of the distance-Doppler map.

[0082] In actual application, the corresponding range resolution RangeRes can be pre-set according to the waveform and software and hardware of the UBW radar; if the pre-set kick distance threshold range is [RangeThresMin, RangeThresMax], the value corresponding to RangeThresMax in the range-Doppler map can be determined as the maximum value of the kick action distance, and the value corresponding to RangeThresMin in the range-Doppler map can be determined as the minimum value of the kick action distance; the value obtained by dividing the minimum value of the kick action distance by the range resolution is rounded down to obtain the minimum row number of the eigenvalue in the distance dimension of the range-Doppler map, as shown in formula (1); the value obtained by dividing the maximum value of the kick action distance by the range resolution is rounded down to obtain the maximum row number of the eigenvalue in the distance dimension of the range-Doppler map, as shown in formula (2).

[0083]

[0084]

[0085] Among them, RangeThresMin1 is the minimum value of the kicking action distance, RangeThresMax1 is the maximum value of the kicking action distance, MinRow is the minimum row number, MaxRow is the maximum row number, and floor() is rounded down.

[0086] It should be noted that after determining the row index number of the range-Doppler map, the row index number can be used to crop the range-Doppler map from the row of the range-Doppler map, as shown in formula (3); it is worth noting that the range-Doppler map can be imagined as a two-dimensional array (a matrix of m*n rows), and then a small matrix can be cropped from this two-dimensional array (a matrix of m*n rows) according to the row index number.

[0087] The cut matrix is ​​the matrix in formula (3)

[0088]

[0089] in, is the range-Doppler map after clipping using the row index number.

[0090] Optionally, the kicking speed threshold range includes a positive threshold range of the speed dimension and a negative threshold range of the speed dimension. According to the kicking speed threshold range, the process of determining the column index number of the distance-Doppler map of each frame of the echo data can be specifically as follows: for the distance-Doppler map of each frame of the echo data, the distance-Doppler map of the echo data is divided into two equal columns with the vertical axis as the y-axis and the rows as the x-axis to construct a two-dimensional array in a spatial xy coordinate system; the two-dimensional array is processed according to the positive threshold range of the speed dimension and the negative threshold range of the speed dimension to obtain the column index number of the distance-Doppler map of the echo data.

[0091] In the embodiment of the present invention, the applicant has found through research that there is a distinction between positive and negative in the velocity dimension of the distance-Doppler diagram. Therefore, the distance-Doppler diagram can be divided into two equal parts by columns, and the distance-Doppler diagram is constructed into a two-dimensional array in a spatial xy coordinate system with the vertical axis as the y-axis and the rows as the x-axis, so as to determine the maximum value of the first kicking action speed and the minimum value of the first kicking action speed from the two-dimensional array according to the positive threshold range of the velocity dimension; determine the maximum value of the second kicking action speed and the minimum value of the second kicking action speed from the two-dimensional array according to the negative threshold range of the velocity dimension; determine the positive threshold value of the velocity dimension of the velocity dimension in the two-dimensional array according to the maximum value of the first kicking action speed and the velocity resolution. According to the first maximum column number of the eigenvalues ​​in the value range, and according to the minimum value of the first kicking action speed and the speed resolution, determine the first minimum column number of the eigenvalues ​​in the positive threshold range of the speed dimension of the two-dimensional array; according to the maximum value of the second kicking action speed and the speed resolution, determine the second maximum column number of the eigenvalues ​​in the negative threshold range of the speed dimension of the two-dimensional array, and according to the minimum value of the second kicking action speed and the speed resolution, determine the second minimum column number of the eigenvalues ​​in the negative threshold range of the speed dimension of the two-dimensional array; according to the first maximum column number, the second maximum column number, the first minimum column number and the second minimum column number, determine the column index number of the distance-Doppler map.

[0092] In actual application, the distance-Doppler graph is divided into two equal parts by columns, and a two-dimensional array in a spatial xy coordinate system is constructed with the vertical axis as the y-axis and the rows as the x-axis; if the positive threshold range of the velocity dimension is [DopplerThresMin, DopplerThresMax], since the maximum positive and negative Doppler velocities of the kick are roughly equal, the negative threshold range of the velocity dimension can be [-DopplerThresMin, -DopplerThresMax]; the value corresponding to DopplerThresMax in the two-dimensional array can be determined as the maximum value of the first kicking action speed, and the value corresponding to DopplerThresMin in the two-dimensional array can be determined as the minimum value of the first kicking action speed; the value corresponding to -DopplerThresMax in the two-dimensional array can be determined as the maximum value of the second kicking action speed, and the value corresponding to -DopplerThresMin in the two-dimensional array can be determined as the minimum value of the second kicking action speed.

[0093] The value obtained by dividing the minimum value of the first kicking action speed by the speed resolution is rounded down to obtain the first minimum row number of the eigenvalue on the speed dimension of the two-dimensional array. The specific calculation formula can be found in formula (4); the value obtained by dividing the maximum value of the first kicking action speed by the speed resolution is rounded down to obtain the first maximum row number of the eigenvalue on the speed dimension of the two-dimensional array. The specific calculation formula can be found in formula (5). The value obtained by dividing the minimum value of the second kicking action speed by the speed resolution is rounded down to obtain the second minimum row number of the eigenvalue on the speed dimension of the two-dimensional array. The specific calculation formula can be found in formula (4); the value obtained by dividing the maximum value of the second kicking action speed by the speed resolution is rounded down to obtain the second maximum row number of the eigenvalue on the speed dimension of the two-dimensional array. The specific calculation formula can be found in formula (5); finally, [the first maximum column number, the first minimum column number] and [the second maximum column number, the second minimum column number] are concatenated to obtain the column index number of the range-Doppler map.

[0094]

[0095] Among them, DopplerMin1 is the minimum value of the first kicking action speed / the minimum value of the second kicking action speed, DopplerMax1 is the maximum value of the first kicking action speed / the maximum value of the second kicking action speed, Mincolumn is the first minimum column number / the second minimum column number, and Maxcolumn is the first maximum column number / the second maximum column number.

[0096] It should be noted that after determining the column index number of the range-Doppler map, the column index number can be used to crop the range-Doppler map after cropping using the row index number. The specific cropping method can be referred to formula (6); it is worth noting that the range-Doppler map after cropping using the row index number can be imagined as a two-dimensional array ( The matrix of rows), and then according to the row index number from this two-dimensional array ( A small matrix is ​​cut out from the matrix with rows of 100, and the cut out matrix is ​​the matrix in formula (6)

[0097]

[0098] It should also be noted that since the Doppler velocity has positive and negative values, the distance-Doppler graph f n =matrix m×n The vertical axis divided into two equal parts by the column is the y-axis, and the maximum axis of the row is the x-axis to construct a two-dimensional array in the spatial xy coordinate system, so that the range-Doppler map clipped according to a certain speed-distance threshold range can be obtained according to formulas (4)-(6). in,

[0099] S104: Selecting each amplitude greater than a preset amplitude threshold from a plurality of amplitudes of the range-Doppler graph of each frame of echo data after trimming as each target amplitude of the echo data of each frame.

[0100] In the embodiment of the present invention, the applicant has found through research that when the UWB radar detects a kicking action, according to the detection principle of the radar, there must be a strong amplitude change on the "grid" greater than a certain speed and distance dimension. Therefore, different amplitude thresholds can be set according to different UWB radar hardware and software properties, so that after the distance-Doppler map of each frame of echo data is cropped, a preset amplitude threshold matching the currently used UBW radar can be determined from the pre-set amplitude thresholds, and each amplitude greater than the preset amplitude threshold is selected from the multiple amplitudes of the distance-Doppler map of each frame of echo data after cropping as each target amplitude of the echo data of each frame.

[0101] As an implementation method of the embodiment of the present application, the preset amplitude threshold may be a topk threshold, and then each amplitude greater than the topk threshold may be selected from multiple amplitudes of the range-Doppler graph of the clipped echo data, and the selected amplitudes are sorted from large to small, and finally the top K amplitudes are used as the K target amplitudes of the range-Doppler graph of the echo data, and the two-dimensional coordinates of the selected K target amplitudes are set to C={(x 1， y1),(x 2，y2),...,(x k， y k )}, where K is greater than 2.

[0102] S105: Determine the kicking feature of each frame of the echo data according to each target amplitude of the echo data of each frame.

[0103] In the process of specifically executing step S105, after selecting each target amplitude of each frame of echo data, for each frame of echo data, multiple characteristic values ​​of the echo data can be calculated according to the various target amplitudes of the echo data, and the kicking characteristics of the echo data can be determined according to the various characteristic values ​​of the echo data.

[0104] Optionally, the process of determining the kick feature of each frame of echo data according to the target amplitudes of each frame of echo data can be specifically as follows: according to the target amplitudes of each frame of echo data, the weighted Doppler (weighted doppler), weighted positive Doppler (weighted positive doppler), weighted negative Doppler (weighted negative doppler) and weighted distance of each frame of echo data are calculated; for each frame of echo data, the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of the echo data are spliced ​​to obtain the kick feature of the echo data.

[0105] In some embodiments, for each frame of echo data, the x-coordinate, positive x-coordinate, negative x-coordinate, y-coordinate, positive y-coordinate and negative y-coordinate of each target amplitude of the echo data on the distance-Doppler diagram of the corresponding cropped echo data can be determined, and the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of the echo data can be calculated based on each target amplitude of the echo data and its x-coordinate, positive x-coordinate, negative x-coordinate, y-coordinate, positive y-coordinate and negative y-coordinate. The specific calculation method is shown in Formula (7) to Formula (10).

[0106]

[0107]

[0108] Among them, WeightedDoppler, WeightedPosDoppler, WeightNegDoppler, and WeightedRange represent weighted Doppler, weighted positive Doppler, weighted negative Doppler, and weighted range, respectively. i y i ) means that according to the coordinate (x i ,y i ) in the cropped range-Doppler map The kth amplitude value taken from i 、xposi 、x negi ,y i ,y posi and negi Indicates that the i-th amplitude is The x coordinate under the coordinates of , positive x coordinate, negative x coordinate and the y coordinate, positive y coordinate, negative y coordinate.

[0109] In the actual application process, after obtaining the WeightedDoppler, WeightedPosDoppler, WeightNegDoppler, and WeightedRange of each frame of echo data, the WeightedDoppler, WeightedPosDoppler, WeightNegDoppler, and WeightedRange of each frame of echo data can be used to generate the topk feature point set F N =(f1, f2, ..., f N ), where f N =(WeightedDoppler, WeightedPosDoppler, WeightNegDoppler, WeightedRange), and then f can be N The WeightedDoppler, WeightedPosDoppler, WeightNegDoppler, and WeightedRange in the function are concatenated into a feature vector of length N*4 to represent f. N A complete kick feature.

[0110] S106: Recognize the kicking features of the echo data of each frame through a pre-trained kicking action recognition model to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network using real kicking training data and non-real kicking training data.

[0111] In the specific process of executing step S106, after obtaining the kicking features of each frame of echo data, the kicking features of each frame of echo data can be input into a pre-trained kicking action recognition model, so that the kicking action recognition model uses the input kicking features of each frame of echo data to perform kicking action recognition and obtain corresponding recognition results; wherein the recognition result can be a kicking action or a non-kicking action.

[0112] In the embodiment of the present invention, the kicking action recognition model is obtained by training a neural network using real kicking training data and non-real kicking training data.

[0113] See also Figure 2, shows a flow chart of a method for training a kicking action recognition model provided by an embodiment of the present invention, and the vehicle electric tailgate control method specifically comprises the following steps:

[0114] S201: Acquire real kick training data and non-real kick training data; wherein the real kick training data includes N frames of first historical echo data with kicking action; and the non-real kick training data includes N frames of second historical echo data without kicking action.

[0115] In an embodiment of the present invention, a kick recognition data set for machine learning can be produced, wherein the kick recognition data set includes real kick training data and non-real kick training data; the real kick training data is N frames of first historical echo data and their timestamps with kicking actions collected based on UBW radar; the non-real kick training data is N frames of second historical echo data with no kicking actions collected based on UBW.

[0116] It should be noted that the non-real kicking training data may be interference data, for example, the non-real kicking training data may be walking data near a car, which is not limited in this embodiment of the present invention.

[0117] S202: Process each frame of the first historical echo data to obtain a first historical range-Doppler map of each frame of the first historical echo data, and process each frame of the second historical echo data to obtain a second historical range-Doppler map of each frame of the second historical echo data.

[0118] In the process of specifically executing step S202, for each frame of first historical echo data, a range-dimensional-Doppler-dimensional fast Fourier transform can be performed on the first historical echo data to obtain a first historical range-Doppler map of the first historical echo data; for each frame of second historical echo data, a range-dimensional-Doppler-dimensional fast Fourier transform can be performed on the second historical echo data to obtain a second historical range-Doppler map of the second historical echo data.

[0119] It should be noted that, no matter it is the first historical distance-Doppler map or the second historical distance-Doppler map, the corresponding data form can be specifically expressed as an m*n two-dimensional matrix in mathematics.

[0120] S203: Using a preset kicking speed-distance threshold range, cropping the first historical distance-Doppler graph of each frame of the first historical echo data and the second historical distance-Doppler graph of each frame of the second historical echo data, respectively; wherein the cropped first historical distance-Doppler graph includes multiple first historical amplitudes, and the cropped second distance-Doppler graph includes multiple second historical amplitudes.

[0121] In an embodiment of the present invention, the kicking speed-distance threshold range may include a kicking speed threshold range and a kicking distance threshold range, and the pre-set kicking speed threshold range and kicking distance threshold range can be used to crop the first historical distance-Doppler map of each frame of the first historical echo data and the second historical distance-Doppler map of each frame of the second historical echo data to remove unnecessary background information in each first historical distance-Doppler map and each second historical distance-Doppler map.

[0122] Optionally, the process of clipping the historical distance-Doppler graph of each frame of the historical echo data using the preset kicking speed-distance threshold range can be specifically as follows: for each frame of the historical distance-Doppler graph of the historical echo data, the historical row index number of the historical distance-Doppler graph of each frame of the historical echo data is determined according to the kicking distance threshold range, and the historical column index number of the historical distance-Doppler graph of each frame of the historical echo data is determined according to the kicking speed threshold range. The historical distance-Doppler graph can be the first historical distance-Doppler graph or the second historical distance-Doppler graph.

[0123] As an implementation method of an embodiment of the present invention, the process of determining the historical row index number of the historical distance-Doppler map according to the kick distance threshold range can be specifically as follows: according to the kick distance threshold range, determining the maximum value of the historical kicking action distance and the minimum value of the historical kicking action distance from the historical distance-Doppler map; according to the maximum value of the historical kicking action distance and the distance resolution, determining the historical maximum row number of the characteristic value on the distance dimension of the historical distance-Doppler map; according to the minimum value of the kicking action distance and the distance resolution, determining the historical minimum row number of the characteristic value on the distance dimension of the historical distance-Doppler map; according to the historical maximum row number and the historical minimum row number, determining the historical row index number of the historical distance-Doppler map.

[0124] In actual application, the corresponding distance resolution can be pre-set according to the waveform and software and hardware of the UBW radar; if the pre-set kick distance threshold range is [RangeThresMin, RangeThresMax], the value corresponding to RangeThresMax in the historical range-Doppler map can be determined as the maximum value of the historical kick action distance, and the value corresponding to RangeThresMin in the historical range-Doppler map can be determined as the minimum value of the historical kick action distance; the value obtained by dividing the maximum value of the historical kick action distance by the distance resolution is rounded down to obtain the historical maximum row number of the characteristic value in the distance dimension of the historical range-Doppler map. The specific calculation method can be found in formula (2), which will not be repeated here; the value obtained by dividing the minimum value of the historical kick action distance by the distance resolution is rounded down to obtain the historical minimum row number of the characteristic value in the distance dimension of the historical range-Doppler map. The specific calculation method can be found in formula (1), which will not be repeated here.

[0125] It should be noted that after determining the historical row index number of the historical distance-Doppler map, the historical row index number can be used to crop the historical distance-Doppler map from the row of the historical distance-Doppler map. The specific cropping method can be referred to formula (3), which will not be repeated here. It is worth mentioning that the historical distance-Doppler map can be imagined as a two-dimensional array (a matrix of m*n rows), and then a small matrix can be cropped from this two-dimensional array (a matrix of m*n rows) according to the historical row index number.

[0126] As an implementation method of an embodiment of the present invention, the kicking speed threshold range includes a positive threshold range of the speed dimension and a negative threshold range of the speed dimension. The process of determining the historical column index number of the historical distance-Doppler map according to the kicking speed threshold range can be specifically as follows: the historical distance-Doppler map is divided into two equal columns, and the historical distance-Doppler map is constructed with the vertical axis as the y-axis and the rows as the x-axis in a spatial xy coordinate system; the historical two-dimensional array is processed according to the positive threshold range of the speed dimension and the negative threshold range of the speed dimension to obtain the historical column index number of the historical distance-Doppler map.

[0127] Optionally, the maximum value of the first historical kicking action speed and the minimum value of the first historical kicking action speed can be determined from the historical two-dimensional array according to the positive threshold range of the speed dimension; the maximum value of the second historical kicking action speed and the minimum value of the second historical kicking action speed can be determined from the historical two-dimensional array according to the negative threshold range of the speed dimension; the first historical maximum column number of the characteristic value within the positive threshold range of the speed dimension of the historical two-dimensional array can be determined according to the maximum value and speed resolution of the first historical kicking action speed, and the first historical maximum column number of the characteristic value within the historical two-dimensional array can be determined according to the minimum value and speed resolution of the first historical kicking action speed. The first historical minimum column number of the eigenvalue on the positive threshold range of the velocity dimension of the group; determining the second historical maximum column number of the eigenvalue on the negative threshold range of the velocity dimension of the historical two-dimensional array according to the maximum value and the velocity resolution of the second historical kicking action velocity, and determining the second historical minimum column number of the eigenvalue on the negative threshold range of the velocity dimension of the historical two-dimensional array according to the minimum value and the velocity resolution of the second historical kicking action velocity; determining the historical column index number of the historical distance-Doppler map according to the first historical maximum column number, the second historical maximum column number, the first historical minimum column number and the second historical minimum column number.

[0128] In actual application, the positive threshold range of the speed dimension is [DopplerThresMin, DopplerThresMax], and the negative threshold range of the speed dimension is [-DopplerThresMin, -DopplerThresMax]. The value corresponding to DopplerThresMax in the historical two-dimensional array is determined as the maximum value of the first historical kicking action speed, and the value corresponding to DopplerThresMin in the historical two-dimensional array is determined as the minimum value of the first historical kicking action speed; the value corresponding to -DopplerThresMax in the historical two-dimensional array is determined as the maximum value of the second historical kicking action speed, and the value corresponding to -DopplerThresMin in the historical two-dimensional array is determined as the minimum value of the second historical kicking action speed.

[0129] The value obtained by dividing the maximum value of the first historical kicking action speed by the speed resolution is rounded down to obtain the first historical maximum row number of the eigenvalue on the speed dimension of the two-dimensional array. The specific calculation formula can be found in formula (5), which will not be repeated here. The value obtained by dividing the minimum value of the first historical kicking action speed by the speed resolution is rounded down to obtain the first historical minimum row number of the eigenvalue on the speed dimension of the historical two-dimensional array. The specific calculation formula can be found in formula (4), which will not be repeated here. The value obtained by dividing the second historical kicking action speed by the speed resolution is rounded down to obtain the second historical maximum row number of the eigenvalue on the speed dimension of the historical two-dimensional array. The specific calculation formula can be found in formula (5), which will not be repeated here. The value obtained by dividing the second historical kicking action speed by the speed resolution is rounded down to obtain the second historical minimum row number of the eigenvalue on the speed dimension of the historical two-dimensional array. The specific calculation formula can be found in formula (4), which will not be repeated here. Finally, [the first historical maximum column number, the first historical minimum column number] and [the second historical maximum column number, the second historical minimum column number] are concatenated to obtain the column index number of the historical distance-Doppler map.

[0130] It should be noted that after determining the historical column index number of the historical distance-Doppler map, the historical column index number can be used to crop the historical distance-Doppler map that has been cropped using the historical row index number. The specific cropping method can be found in formula (6), which will not be described in detail here.

[0131] S204: From the multiple first historical amplitudes of the first historical distance-Doppler of each frame of the cropped first historical echo data, select each first historical amplitude that is greater than the preset threshold as each target first historical amplitude of each frame of the first historical echo data, and determine the first historical kick feature of each frame of the first historical echo data based on the each target first historical amplitude of each frame of the first historical echo data.

[0132] In the embodiment of the present invention, for each frame of the first historical echo data, after the range-Doppler graph of the first historical echo data is clipped, a preset amplitude threshold matching the UBW radar that collects the first historical echo data can be determined from the preset amplitude thresholds, and each first historical amplitude greater than the preset amplitude threshold is selected from the multiple first historical amplitudes of the range-Doppler graph of the clipped first historical echo data as each target first historical amplitude of the first historical echo data. According to each target first historical amplitude of the first historical echo data, multiple characteristic values ​​of the first historical echo data are calculated, and according to each characteristic value of the first historical echo data, the first historical kick feature of the first historical echo data is determined.

[0133] Optionally, the process of determining the first historical kick feature of each frame of first historical echo data based on the first historical amplitudes of each target in each frame of first historical echo data can be specifically as follows: according to the first historical amplitudes of each target in each frame of the first historical echo data, the first historical weighted Doppler, the first historical weighted positive Doppler, the first historical weighted negative Doppler and the first historical weighted distance of each frame of the first historical echo data are calculated; for each frame of the first historical echo data, the first historical weighted Doppler, the first historical weighted positive Doppler, the first historical weighted negative Doppler and the first historical weighted distance of the first historical echo data are spliced ​​to obtain the first historical kick feature of the first historical echo data.

[0134] It should be noted that, according to the first historical amplitudes of each target in each frame of the first historical echo data, the specific calculation method of calculating the first historical weighted Doppler, the first historical weighted positive Doppler, the first historical weighted negative Doppler and the first historical weighted distance of the first historical echo data of each frame can be referred to formula (7) to formula (10), which will not be repeated here.

[0135] S205: From the multiple second historical amplitudes of the second historical range-Doppler of each frame of the cropped second historical echo data, select each second historical amplitude greater than the preset threshold as each target second historical amplitude of each frame of the second historical echo data, and determine the second historical kick feature of each frame of the second historical echo data based on the each target second historical amplitude of each frame of the second historical echo data.

[0136] In the embodiment of the present invention, for each frame of the second historical echo data, after the range-Doppler graph of the second historical echo data is clipped, a preset amplitude threshold matching the UBW radar that collects the second historical echo data can be determined from the preset amplitude thresholds, and each second historical amplitude greater than the preset amplitude threshold is selected from the multiple second historical amplitudes of the range-Doppler graph of the clipped second historical echo data as each target second historical amplitude of the second historical echo data. According to each target second historical amplitude of the second historical echo data, multiple characteristic values ​​of the second historical echo data are calculated, and according to each characteristic value of the second historical echo data, the second historical kick feature of the second historical echo data is determined.

[0137] Optionally, the process of determining the second historical kick feature of each frame of second historical echo data based on the second historical amplitudes of each target in each frame of second historical echo data can be specifically as follows: according to the second historical amplitudes of each target in each frame of the second historical echo data, the second historical weighted Doppler, the second historical weighted positive Doppler, the second historical weighted negative Doppler and the second historical weighted distance of each frame of the second historical echo data are calculated; for each frame of the second historical echo data, the second historical weighted Doppler, the second historical weighted positive Doppler, the first historical weighted negative Doppler and the second historical weighted distance of the second historical echo data are spliced ​​to obtain the second historical kick feature of the second historical echo data.

[0138] It should be noted that, according to the second historical amplitude of each target in each frame of the second historical echo data, the specific calculation method of calculating the second historical weighted Doppler, the second historical weighted positive Doppler, the second historical weighted negative Doppler and the second historical weighted distance of each frame of the first historical echo data can be referred to formula (7) to formula (10), which will not be repeated here.

[0139] S206: Train a neural network using the first historical kicking features of each frame of the first historical echo data and the second historical kicking features of each frame of the second historical echo data to obtain a kicking action recognition model.

[0140] In the process of specifically executing step S206, after obtaining the first historical kicking features of the first historical echo data of each frame and the second historical kicking features of the second historical echo data of each frame, the first historical kicking features of the first historical echo data of each frame and the second historical kicking features of the second historical echo data of each frame can be input into the neural network to be trained, so that the neural network is trained using the first historical kicking features of the first historical echo data of each frame and the second historical kicking features of the second historical echo data of each frame until the neural network converges and a kicking action recognition model that can recognize kicking actions and non-kicking actions is obtained.

[0141] S107: Determine whether the recognition result is a kicking action; if the recognition result is a kicking action, execute step S108; if the recognition result is not a kicking action, return to execute step S101.

[0142] In the specific process of executing step S107, after obtaining the corresponding recognition result by identifying the kicking features of the echo data of each frame through the pre-trained kicking action recognition model, it can be further determined whether the obtained recognition result is a kicking action; if so, step S108 can be executed, and when the tailgate of the car is currently open, the tailgate of the car is controlled to be closed; when the tailgate of the car is currently closed, the tailgate of the car is controlled to be opened.

[0143] S108: Control the tailgate of the vehicle to open or close.

[0144] The embodiment of the present invention provides a method for controlling an electric tailgate of an automobile. A neural network is trained by using real kick training data and non-real kick training data to obtain a kick recognition model that can recognize kicking actions. When collecting N frames of echo data of the tailgate of an automobile based on a UWB radar, each frame of the collected echo data is processed to obtain a distance-Doppler graph of each frame of echo data, and the distance-Doppler graph of each frame of echo data is cropped according to a preset kick speed-distance threshold range to remove unnecessary background information in the distance-Doppler graph of each frame of echo data. , reducing redundancy in the distance-Doppler map, and if a kicking action really exists at present, it can also highlight the features of the kicking action in the distance-Doppler map; using the cropped distance-Doppler map of each frame of echo data to construct the kicking features, and using the pre-trained kicking action recognition model to identify whether there is a kicking action at present according to the constructed kicking features. It can be seen that the present invention does not need to place a capacitive electric field transmitting electrode at two positions according to a strict installation position and spacing, and can ensure the accuracy of kicking action recognition in various environments, and has strong anti-interference ability.

[0145] Based on the above-mentioned automobile tailgate control method provided by the embodiment of the present invention, correspondingly, the embodiment of the present invention also provides an automobile tailgate control system, such as Figure 3 As shown, the system includes:

[0146] A periodic acquisition unit 31 is used to periodically acquire N frames of echo data of the tailgate of the vehicle based on the UWB radar;

[0147] A first processing unit 32 is used to process the echo data for each frame of the echo data to obtain a range-Doppler map of the echo data;

[0148] A first clipping unit 33 is used to clip the distance-Doppler graph of each frame of the echo data using a preset kicking speed-distance threshold range; wherein the clipped distance-Doppler graph includes multiple amplitudes;

[0149] A first selection unit 34 is used to select each amplitude greater than a preset amplitude threshold from multiple amplitudes of the range-Doppler map of each frame of echo data after trimming as each target amplitude of each frame of the echo data;

[0150] A first determining unit 35 is used to determine the kicking feature of each frame of the echo data according to each target amplitude of each frame of the echo data;

[0151] The recognition unit 36 ​​is used to recognize the kicking features of the echo data of each frame by using a pre-trained kicking action recognition model to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network by a training unit using real kicking training data and non-real kicking training data;

[0152] The control unit 37 is used to control the tailgate of the vehicle to open or close if the recognition result is a kicking action.

[0153] The above-mentioned embodiment of the present invention discloses the specific principles and execution processes of each unit in the automobile tailgate control system, which is the same as the automobile tailgate control method disclosed in the above-mentioned embodiment of the present invention. Please refer to the corresponding parts of the automobile tailgate control method disclosed in the above-mentioned embodiment of the present invention, and no further details will be given here.

[0154] The embodiment of the present invention is a vehicle electric tailgate control system. A neural network is trained by using real kick training data and non-real kick training data to obtain a kick recognition model that can recognize kicking actions. When collecting N frames of echo data of the tailgate of the vehicle based on a UWB radar, each frame of the collected echo data is processed to obtain a distance-Doppler graph of each frame of echo data, and the distance-Doppler graph of each frame of echo data is cropped according to a preset kick speed-distance threshold range to remove unnecessary background information in the distance-Doppler graph of each frame of echo data. , reducing redundancy in the distance-Doppler map, and if a kicking action really exists at present, it can also highlight the features of the kicking action in the distance-Doppler map; using the cropped distance-Doppler map of each frame of echo data to construct the kicking features, and using the pre-trained kicking action recognition model to identify whether there is a kicking action at present according to the constructed kicking features. It can be seen that the present invention does not need to place a capacitive electric field transmitting electrode at two positions according to a strict installation position and spacing, and can ensure the accuracy of kicking action recognition in various environments, and has strong anti-interference ability.

[0155] Optionally, the preset kicking speed-distance threshold range includes a kicking speed threshold range and a kicking distance threshold range, and the first clipping unit includes:

[0156] A second determining unit, configured to determine a row index number of a range-Doppler graph of each frame of the echo data according to the kick distance threshold range;

[0157] A third determining unit, configured to determine a column index number of a range-Doppler graph of each frame of the echo data according to the kicking speed threshold range;

[0158] The first cropping subunit is used to crop the range-Doppler map of the echo data of each frame according to the row index number and the column index number of the range-Doppler map of the echo data.

[0159] Optionally, the second determining unit includes:

[0160] a fourth determining unit, configured to determine, for each frame of the range-Doppler map of the echo data, a maximum value of the kicking action distance and a minimum value of the kicking action distance from the range-Doppler map of the echo data according to the kicking distance threshold range;

[0161] a fifth determining unit, configured to determine a maximum row number of a characteristic value in a distance dimension of the range-Doppler map according to a maximum value of the kicking action distance and a distance resolution;

[0162] a sixth determining unit, configured to determine a minimum row number of characteristic values ​​in the distance dimension of the range-Doppler map according to the minimum value of the kicking action distance and the distance resolution;

[0163] A seventh determining unit is used to determine a row index number of the range-Doppler map according to the maximum row number and the minimum row number.

[0164] Optionally, the third determining unit includes:

[0165] A construction unit, for constructing a two-dimensional array in a spatial xy coordinate system by dividing the distance-Doppler map of each frame of echo data into two equal columns with the vertical axis as the y-axis and the rows as the x-axis;

[0166] The second processing unit is used to process the two-dimensional array according to the positive threshold range of the velocity dimension and the negative threshold range of the velocity dimension to obtain the column index number of the range-Doppler map of the echo data.

[0167] Optionally, the second processing unit includes:

[0168] an eighth determining unit, configured to determine a maximum value of the first kicking action speed and a minimum value of the first kicking action speed from the two-dimensional array according to the positive threshold range of the speed dimension;

[0169] a ninth determining unit, configured to determine a maximum value of the second kicking action speed and a minimum value of the second kicking action speed from the two-dimensional array according to the negative threshold range of the speed dimension;

[0170] a tenth determining unit, configured to determine a first maximum column number of the characteristic value in the positive threshold range of the velocity dimension of the two-dimensional array according to the maximum value and the velocity resolution of the first kicking action velocity, and to determine a first minimum column number of the characteristic value in the positive threshold range of the velocity dimension of the two-dimensional array according to the minimum value and the velocity resolution of the first kicking action velocity;

[0171] an eleventh determining unit, configured to determine a second maximum column number of the eigenvalues ​​in the negative threshold range of the velocity dimension of the two-dimensional array according to the maximum value of the second kicking motion velocity and the velocity resolution, and to determine a second minimum column number of the eigenvalues ​​in the negative threshold range of the velocity dimension of the two-dimensional array according to the minimum value of the second kicking motion velocity and the velocity resolution;

[0172] A twelfth determining unit is configured to determine a column index number of the range-Doppler map according to the first maximum column number, the second maximum column number, the first minimum column number, and the second minimum column number.

[0173] Optionally, the first determining unit includes:

[0174] A first calculation unit, used for calculating the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of each frame of the echo data according to each target amplitude of each frame of the echo data;

[0175] The splicing unit is used to splice the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of the echo data for each frame of the echo data to obtain the kicking feature of the echo data.

[0176] Optional training modules include:

[0177] An acquisition unit, used for acquiring real kicking training data and non-real kicking training data; wherein the real kicking training data includes N frames of first historical echo data with kicking action; and the non-real kicking training data includes N frames of second historical echo data without kicking action;

[0178] a third processing unit, configured to process each frame of the first historical echo data to obtain a first historical range-Doppler map of each frame of the first historical echo data, and to process each frame of the second historical echo data to obtain a second historical range-Doppler map of each frame of the second historical echo data;

[0179] A second clipping unit is used to clip the first historical distance-Doppler map of each frame of the first historical echo data and the second historical distance-Doppler map of each frame of the second historical echo data respectively by using a preset kicking speed-distance threshold range; wherein the clipped first historical distance-Doppler map includes a plurality of first historical amplitudes, and the clipped second distance-Doppler map includes a plurality of second historical amplitudes;

[0180] A third clipping unit is used to select each first historical amplitude greater than the preset threshold from the plurality of first historical amplitudes of the first historical range-Doppler of each frame of the clipped first historical echo data as each target first historical amplitude of each frame of the first historical echo data;

[0181] A second selection unit is used to select each second historical amplitude greater than the preset threshold from the plurality of second historical amplitudes of the second historical range-Doppler of each frame of the cropped second historical echo data as each target second historical amplitude of each frame of the second historical echo data;

[0182] a thirteenth determining unit, configured to determine a first historical kick feature of each frame of the first historical echo data according to each target first historical amplitude of each frame of the first historical echo data;

[0183] a fourteenth determining unit, configured to determine a second historical kick feature of each frame of the second historical echo data according to each target second historical amplitude of each frame of the second historical echo data;

[0184] The training subunit is used to train the neural network using the first historical kicking features of each frame of the first historical echo data and the second historical kicking features of each frame of the second historical echo data to obtain a kicking action recognition model.

[0185] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, in which the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0186] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0187] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0188] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling an electric tailgate of an automobile, characterized in that: The method comprises: Periodically collect N frames of echo data from the tailgate of the car based on UWB radar; For each frame of the echo data, the echo data is processed to obtain a range-Doppler map of the echo data; Using a preset kicking speed-distance threshold range, the distance-Doppler graph of each frame of the echo data is clipped; wherein the clipped distance-Doppler graph includes multiple amplitudes; Selecting each amplitude greater than a preset amplitude threshold from a plurality of amplitudes of the range-Doppler graph of each frame of echo data after clipping as each target amplitude of the echo data of each frame; determining a kick feature of each frame of echo data according to each target amplitude of each frame of echo data; The kicking action recognition model is used to recognize the kicking features of the echo data of each frame to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network using real kicking training data and non-real kicking training data; If the recognition result is a kicking action, the tailgate of the vehicle is controlled to be opened or closed.

2. The method according to claim 1, characterized in that The preset kicking speed-distance threshold range includes a kicking speed threshold range and a kicking distance threshold range; The method of cutting the distance-Doppler graph of each frame of the echo data by using the preset kicking speed-distance threshold range comprises: Determine the row index number of the distance-Doppler graph of each frame of the echo data according to the kick distance threshold range; Determine the column index number of the range-Doppler graph of each frame of the echo data according to the kicking speed threshold range; For each frame of the range-Doppler map of the echo data, the range-Doppler map of the echo data is cropped according to the row index number and the column index number of the range-Doppler map of the echo data.

3. The method according to claim 2, characterized in that Determining the row index number of the distance-Doppler map of each frame of the echo data according to the kick distance threshold range includes: For each frame of the range-Doppler map of the echo data, according to the kicking distance threshold range, determining the maximum value and the minimum value of the kicking action distance from the range-Doppler map of the echo data; Determine the maximum row number of the characteristic value in the distance dimension of the range-Doppler map according to the maximum value of the kicking action distance and the distance resolution; Determine the minimum row number of the characteristic value in the distance dimension of the range-Doppler map according to the minimum value of the kicking action distance and the distance resolution; A row index number of the range-Doppler map is determined according to the maximum row number and the minimum row number.

4. The method according to claim 2, characterized in that: The kicking speed threshold range includes a positive threshold range of the speed dimension and a negative threshold range of the speed dimension; Determining the column index number of the distance-Doppler graph of each frame of the echo data according to the kicking speed threshold range includes: For each frame of the distance-Doppler map of the echo data, the distance-Doppler map of the echo data is divided into two equal columns, with the vertical axis as the y-axis and the rows as the x-axis to construct a two-dimensional array in a spatial xy coordinate system; The two-dimensional array is processed according to the positive threshold range of the velocity dimension and the negative threshold range of the velocity dimension to obtain a column index number of the range-Doppler map of the echo data.

5. The method according to claim 4, characterized in that The processing of the two-dimensional array according to the positive threshold range of the velocity dimension and the negative threshold range of the velocity dimension to obtain the column index number of the range-Doppler map includes: Determining a maximum value of the first kicking motion speed and a minimum value of the first kicking motion speed from the two-dimensional array according to the positive threshold range of the speed dimension; According to the negative threshold range of the speed dimension, determining the maximum value of the second kicking action speed and the minimum value of the second kicking action speed from the two-dimensional array; Determine a first maximum column number of a characteristic value within a positive threshold range of a velocity dimension of the two-dimensional array according to a maximum value and a velocity resolution of the first kicking motion velocity, and determine a first minimum column number of a characteristic value within a positive threshold range of a velocity dimension of the two-dimensional array according to a minimum value and a velocity resolution of the first kicking motion velocity; Determine a second maximum column number of the eigenvalues ​​within the negative threshold range of the velocity dimension of the two-dimensional array according to the maximum value and velocity resolution of the second kicking motion velocity, and determine a second minimum column number of the eigenvalues ​​within the negative threshold range of the velocity dimension of the two-dimensional array according to the minimum value and velocity resolution of the second kicking motion velocity; A column index number of the range-Doppler map is determined according to the first maximum column number, the second maximum column number, the first minimum column number, and the second minimum column number.

6. The method according to claim 1, characterized in that Determining the kicking feature of each frame of echo data according to each target amplitude of each frame of echo data includes: Calculate the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of each frame of echo data according to each target amplitude of each frame of echo data; For each frame of the echo data, the weighted Doppler, weighted positive Doppler, weighted negative Doppler and weighted distance of the echo data are spliced ​​to obtain the kicking feature of the echo data.

7. The method according to claim 1, characterized in that The method of training the neural network using the real kicking training data and the non-real kicking training data to obtain the kicking action recognition model includes: Acquire real kick training data and non-real kick training data; wherein the real kick training data includes N frames of first historical echo data with kicking action; the non-real kick training data includes N frames of second historical echo data without kicking action; Processing each frame of the first historical echo data to obtain a first historical range-Doppler map of each frame of the first historical echo data, and processing each frame of the second historical echo data to obtain a second historical range-Doppler map of each frame of the second historical echo data; Using a preset kicking speed-distance threshold range, the first historical distance-Doppler graph of each frame of the first historical echo data and the second historical distance-Doppler graph of each frame of the second historical echo data are respectively clipped; wherein the clipped first historical distance-Doppler graph includes a plurality of first historical amplitudes, and the clipped second distance-Doppler graph includes a plurality of second historical amplitudes; From the plurality of first historical amplitudes of the first historical range-Doppler of each frame of the first historical echo data after trimming, selecting each first historical amplitude greater than a preset threshold as each target first historical amplitude of each frame of the first historical echo data; From the plurality of second historical amplitudes of the second historical range-Doppler of each frame of the cropped second historical echo data, selecting each second historical amplitude greater than the preset threshold as each target second historical amplitude of each frame of the second historical echo data; Determining a first historical kick feature of each frame of the first historical echo data according to each target first historical amplitude of each frame of the first historical echo data; Determining a second historical kick feature of each frame of the second historical echo data according to each target second historical amplitude of each frame of the second historical echo data; The first historical kicking features of each frame of the first historical echo data and the second historical kicking features of each frame of the second historical echo data are used to train a neural network to obtain a kicking action recognition model.

8. A car tailgate control system, characterized in that: The system comprises: A periodic acquisition unit, used for periodically acquiring N frames of echo data of the tailgate of a car based on the UWB radar; A first processing unit, configured to process the echo data for each frame of the echo data to obtain a range-Doppler map of the echo data; A first clipping unit is used to clip the distance-Doppler graph of each frame of the echo data using a preset kicking speed-distance threshold range; wherein the clipped distance-Doppler graph includes a plurality of amplitudes; A first selection unit is used to select each amplitude greater than a preset amplitude threshold from multiple amplitudes of the range-Doppler diagram of each frame of echo data after clipping as each target amplitude of each frame of the echo data; A first determining unit, configured to determine a kicking feature of each frame of the echo data according to each target amplitude of each frame of the echo data; A recognition unit, used for recognizing the kicking features of the echo data of each frame by using a pre-trained kicking action recognition model to obtain a corresponding recognition result; wherein the kicking action recognition model is obtained by training a neural network by a training unit using real kicking training data and non-real kicking training data; A control unit is used to control the opening or closing of the tailgate of the automobile if the recognition result is a kicking action.

9. The system according to claim 8, characterized in that The preset kicking speed-distance threshold range includes a kicking speed threshold range and a kicking distance threshold range, and the first clipping unit includes: A second determining unit, configured to determine a row index number of a range-Doppler graph of each frame of the echo data according to the kick distance threshold range; A third determining unit, configured to determine a column index number of a range-Doppler graph of each frame of the echo data according to the kicking speed threshold range; The first cropping subunit is used to crop the range-Doppler map of the echo data of each frame according to the row index number and the column index number of the range-Doppler map of the echo data.

10. The system according to claim 9, characterized in that The second determining unit includes: a fourth determining unit, configured to determine, for each frame of the range-Doppler map of the echo data, a maximum value of the kicking action distance and a minimum value of the kicking action distance from the range-Doppler map of the echo data according to the kicking distance threshold range; a fifth determining unit, configured to determine a maximum row number of a characteristic value in a distance dimension of the range-Doppler map according to a maximum value of the kicking action distance and a distance resolution; a sixth determining unit, configured to determine a minimum row number of characteristic values ​​in the distance dimension of the range-Doppler map according to the minimum value of the kicking action distance and the distance resolution; A seventh determining unit is used to determine a row index number of the range-Doppler map according to the maximum row number and the minimum row number.

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