Distance speed acquisition method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a distance and speed acquisition method, electronic equipment, a device and a storage medium, and the method comprises the steps: carrying out the IDFT of each column vector of a target matrix, carrying out the DFT of a part of row vectors in an IDFT result matrix, and obtaining the distance information and speed information of each to-be-sensed target in a sensing range; or, performing DFT on each row vector of the target matrix, and performing IDFT on part of column vectors in a DFT result matrix to obtain distance information and speed information of each to-be-sensed target in the sensing range. According to the embodiment of the invention, the method comprises the steps: carrying out the DFT of a part of row vectors in an IDFT result matrix; or performing IDFT on part of column vectors in the DFT result matrix to obtain the distance information and the speed information of each to-be-sensed target in the sensing range, and reducing the complexity at the same time of obtaining the distance information and the speed information of each to-be-sensed target in the sensing range.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a distance speed acquisition method, electronic equipment, device and storage medium. Background Art

[0002] The mainstream receiver distance and speed acquisition method in the next generation mobile communication (Next Generation Mobile Communication) Joint Communication and Sensing (JCAS) single-base mode is to perform a second-order discrete Fourier transform (2D-DFT) on the normalized modulation symbol matrix to obtain the distance information and speed information of the target to be sensed.

[0003] However, this method requires performing an inverse discrete Fourier transform (IDFT) on the modulation symbol matrix column by column, and then performing a discrete Fourier transform (DFT) on the result matrix row by row. When the accuracy of distance and speed acquisition is required to be high, the order of the discrete Fourier transform is high and the computational complexity is high. Summary of the invention

[0004] In view of the problems existing in the prior art, the embodiments of the present application provide a distance speed acquisition method, electronic equipment, device and storage medium.

[0005] In a first aspect, the embodiments of the present application provide a distance speed acquisition method, an electronic device, a device, and a storage medium method, including:

[0006] Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; or,

[0007] Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range;

[0008] The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

[0009] In some embodiments, after performing inverse discrete Fourier transform on each column vector of the target matrix, the method further includes:

[0010] The number of rows of the partial row vectors is determined based on the element numbers of the elements whose values ​​are greater than the adjacent elements in the discrete Fourier inverse transform result vector of any column vector of the target matrix.

[0011] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0012] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the inverse discrete Fourier transform result vector, obtaining the distance information of all the targets to be sensed within the sensing range;

[0013] Based on the discrete Fourier transform result of any row vector in the partial row vectors in the discrete Fourier inverse transform result matrix, obtaining the speed information of all the targets to be sensed within the sensing range;

[0014] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0015] In some embodiments, after performing inverse discrete Fourier transform on each column vector of the target matrix, the method further includes:

[0016] A discrete Fourier inverse transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of the partial row vector is determined based on a peak position in the range domain radar map.

[0017] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0018] Based on the discrete Fourier transform results of the part of row vectors in the inverse discrete Fourier transform result matrix, obtaining a first range-speed radar chart;

[0019] Based on the first distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0020] In some embodiments, after performing discrete Fourier transform on each row vector of the target matrix, the method further includes:

[0021] The number of columns of the partial column vectors is determined based on the element numbers of the discrete Fourier transform result vectors of any row vector of the target matrix whose values ​​are greater than the adjacent elements.

[0022] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0023] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the discrete Fourier transform result vector, obtaining the speed information of all the targets to be sensed within the sensing range;

[0024] Based on the inverse discrete Fourier transform result of any column vector in the partial column vectors in the discrete Fourier transform result matrix, obtaining distance information of all to-be-perceived targets within the perception range;

[0025] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0026] In some embodiments, after performing discrete Fourier transform on each row vector of the target matrix, the method further includes:

[0027] A discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of the partial column vector is determined based on a peak position in the velocity domain radar map.

[0028] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0029] Based on the inverse discrete Fourier transform results of the part of column vectors in the discrete Fourier transform result matrix, obtaining a second range-speed radar chart;

[0030] Based on the second distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0031] In some embodiments, the method further comprises:

[0032] Based on the relationship between the distance information of each target to be sensed within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be sensed within the perception range and the preset maximum detection speed, the sending density of the perception resources within the perception range is adjusted.

[0033] In a second aspect, an embodiment of the present application further provides an electronic device, including a memory, a transceiver, and a processor; the memory is used to store a computer program; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer program in the memory and execute the distance speed acquisition method described in the first aspect.

[0034] In a third aspect, an embodiment of the present application further provides a distance and speed acquisition device, comprising:

[0035] A first acquisition unit is used to perform a discrete Fourier inverse transform on each column vector of the target matrix, and to perform a discrete Fourier transform on some row vectors in the discrete Fourier inverse transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range; or,

[0036] The second acquisition unit is used to perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range;

[0037] The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

[0038] In some embodiments, the first acquiring unit is further configured to:

[0039] The number of rows of the partial row vectors is determined based on the element numbers of the elements whose values ​​are greater than the adjacent elements in the discrete Fourier inverse transform result vector of any column vector of the target matrix.

[0040] In some embodiments, the first acquiring unit is further configured to:

[0041] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the inverse discrete Fourier transform result vector, obtaining the distance information of all the targets to be sensed within the sensing range;

[0042] Based on the discrete Fourier transform result of any row vector in the partial row vectors in the discrete Fourier inverse transform result matrix, obtaining the speed information of all the targets to be sensed within the sensing range;

[0043] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0044] In some embodiments, the first acquiring unit is further configured to:

[0045] A discrete Fourier inverse transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of the partial row vector is determined based on a peak position in the range domain radar map.

[0046] In some embodiments, the first acquiring unit is further configured to:

[0047] Based on the discrete Fourier transform results of the part of row vectors in the inverse discrete Fourier transform result matrix, obtaining a first range-speed radar chart;

[0048] Based on the first distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0049] In some embodiments, the second acquiring unit is further configured to:

[0050] The number of columns of the partial column vectors is determined based on the element numbers of the discrete Fourier transform result vectors of any row vector of the target matrix whose values ​​are greater than the adjacent elements.

[0051] In some embodiments, the second acquiring unit is further configured to:

[0052] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the discrete Fourier transform result vector, obtaining the speed information of all the targets to be sensed within the sensing range;

[0053] Based on the inverse discrete Fourier transform result of any column vector in the partial column vectors in the discrete Fourier transform result matrix, obtaining distance information of all to-be-perceived targets within the perception range;

[0054] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0055] In some embodiments, the second acquiring unit is further configured to:

[0056] A discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of the partial column vector is determined based on a peak position in the velocity domain radar map.

[0057] In some embodiments, the second acquiring unit is further configured to:

[0058] Based on the inverse discrete Fourier transform results of the part of column vectors in the discrete Fourier transform result matrix, obtaining a second range-speed radar chart;

[0059] Based on the second distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0060] In some embodiments, the apparatus further comprises:

[0061] An adjustment unit is used to adjust the sending density of the perception resources within the perception range based on the relationship between the distance information of each target to be perceived within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be perceived within the perception range and the preset maximum detection speed.

[0062] In a fourth aspect, an embodiment of the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the distance speed acquisition method provided in the first aspect as described above.

[0063] In a fifth aspect, an embodiment of the present application further provides a non-transitory readable storage medium, wherein the non-transitory readable storage medium stores a computer program, wherein the computer program is used to enable a computer to execute the distance speed acquisition method provided in the first aspect as described above.

[0064] In a sixth aspect, an embodiment of the present application further provides a communication device, wherein a computer program is stored in the communication device, and the computer program is used to enable the communication device to execute the distance speed acquisition method provided in the first aspect as described above.

[0065] In a seventh aspect, an embodiment of the present application further provides a chip product, wherein a computer program is stored in the chip product, and the computer program is used to enable the chip product to execute the distance speed acquisition method provided in the first aspect as described above.

[0066] The distance and speed acquisition method, electronic device, apparatus and storage medium provided in the embodiments of the present application perform an inverse discrete Fourier transform on each column vector of the target matrix and perform a discrete Fourier transform on some row vectors in the discrete Fourier transform result matrix; or, perform a discrete Fourier transform on each row vector of the target matrix and perform a discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, thereby obtaining the distance information and speed information of each target to be perceived within the perception range while reducing the complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1 It is a schematic diagram of the distribution of the perceived signals of the grid-shaped rectangular resource blocks provided by the related art;

[0069] Figure 2It is a schematic diagram of the framework of an OFDM radar signal transceiver provided by the related technology;

[0070] Figure 3 It is a schematic diagram of the process of obtaining 2D-DFT distance speed provided by the related technology;

[0071] Figure 4 It is a schematic diagram of a distance speed radar diagram provided by the related art;

[0072] Figure 5 This is one of the flow charts of the distance speed acquisition method provided in the embodiment of the present application;

[0073] Figure 6 It is a distance domain radar chart provided in an embodiment of the present application;

[0074] Figure 7 It is one of the speed domain radar charts provided in the embodiments of the present application;

[0075] Figure 8 It is one of the distance speed radar diagrams provided in the embodiment of the present application;

[0076] Fig. 9 This is the second flow chart of the distance speed acquisition method provided in the embodiment of the present application;

[0077] Fig.10 This is the second distance speed radar diagram provided in the embodiment of the present application;

[0078] Fig.11 This is the third distance speed radar diagram provided in the embodiment of the present application;

[0079] Fig.12 This is the fourth distance speed radar diagram provided in the embodiment of the present application;

[0080] Fig.13 This is the second speed domain radar chart provided in the embodiment of the present application;

[0081] Fig.14 This is the fifth distance speed radar diagram provided in the embodiment of the present application;

[0082] Fig.15 This is the sixth distance-speed domain radar chart provided in the embodiment of the present application;

[0083] Fig.16 This is the third flow chart of the distance speed acquisition method provided in the embodiment of the present application;

[0084] Fig.17 This is the seventh distance speed radar diagram provided in the embodiment of the present application;

[0085] Fig.18 This is the eighth distance speed radar diagram provided in the embodiment of the present application;

[0086] Fig.19 This is the ninth distance speed radar diagram provided in the embodiment of the present application;

[0087] Fig. 20 It is one of the perception signal waveform diagrams provided in the embodiment of the present application;

[0088] Fig.21 This is the second perception signal waveform diagram provided in the embodiment of the present application;

[0089] Fig. 22 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0090] Fig.23 It is a schematic diagram of the structure of the distance and speed acquisition device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0091] In the related art, the 2D-DFT distance speed acquisition method is introduced as follows:

[0092] In order to reduce the perception signal overhead, the synaesthesia integrated waveform based on Orthogonal Frequency Division Multiplexing (OFDM) usually adopts a grid-structured perception signal distribution. Figure 1 is a schematic diagram of the distribution of sensing signals of a grid-shaped rectangular resource block provided by the related art, such as Figure 1 As shown in the figure, Symbol represents symbol, Slot represents time slot, Subcarrier No. represents subcarrier number, Sensing signal symbol represents sensing signal, Communication symbol represents communication symbol, T b Represents the duration of the perceived signal in time domain.

[0093] from Figure 1 It can be seen that in the frequency domain, 120 perception signals are included, and in the speed domain, 120 perception signals are also included. The number of perception signals included in the frequency domain and the speed domain can be the same or different. The perception signal resource block waveform can realize a synaesthesia integrated system with a distance resolution of 1.5m, a speed resolution of 0.71m / h, a maximum detection distance of 180m, and a maximum detection speed of 85m / s.

[0094] Figure 2 It is a schematic diagram of the framework of the OFDM radar signal transceiver provided by the relevant technology, such as Figure 2 As shown, Rx represents a receiver (Receiver), and Tx represents a transmitter (Transmitter).

[0095] The transmitter senses the signal dTx (m,n), m and n represent the number of perception signals in the frequency domain and the number of perception signals in the time domain respectively. After the Inverse Fast Fourier Transform (IFFT), Insertion of Cyclic Prefix (CP), and Digital-to-Analog conversion, the perception signal is sent by the RF transmitting antenna. The perception signal is reflected by the target to be sensed in space, and the echo is received by the RF receiving antenna. After analog-to-digital conversion, removal of CP, and Fast Fourier Transform (FFT), the receiving end perception signal d is generated. Rx (m,n).d Rx The expression for (m,n) is as follows:

[0096]

[0097] Among them, d Rx (m,n) represents the received signal, A(m,n) represents the signal strength change, d Tx (m,n) represents the perceived signal at the sender, and the exponential term Carrying the distance information R of the target to be sensed, exponential term Carrying the speed information v of the target to be sensed. Where j represents the imaginary unit, T sym represents the OFDM symbol duration, Δf represents the subcarrier spacing, T sym =1 / Δf, c0 represents the speed of light.

[0098] Put d Rx (m,n) divided by d Tx (m,n) can eliminate the data information carried by the perception signal and express it in matrix form as follows:

[0099]

[0100] Among them, each column of the matrix D(m,n) represents an OFDM symbol, each row represents a subcarrier, N t Represents the duration of the perceived signal in time domain T b Number of interoceptive signals, N f Represents the number of sensed signals within bandwidth B. The column vector and row vector in the matrix describe the distance of the reflector and the phase shift caused by the Doppler frequency shift, respectively.

[0101] Figure 3 This is a flow chart of 2D-DFT distance and speed acquisition provided by related technologies, such as Figure 3As shown in the figure, IDFT transformation is performed on each column of the matrix D(m,n), and then DFT transformation is performed on each row of the IDFT transformation result matrix after passing through the intermediate buffer. Then, the range-velocity profile in the range domain and the velocity domain can be obtained, and a two-dimensional radar image is created, which is called the range-speed response pattern.

[0102] In the range-speed radar chart, the horizontal axis is speed (Speed), the unit is meter / second (m / s), the vertical axis is range (Range), the unit is meter (Meters), and Power represents the signal power. In the range-domain radar chart, the horizontal axis is the IDFT index number (Index), and the vertical axis is the normalized IDFT result (Normalized IDFT results). In the speed-domain radar chart, the horizontal axis is the DFT index number, and the vertical axis is the normalized DFT result (Normalized DFT results).

[0103] Figure 4 It is a schematic diagram of a distance speed radar diagram provided by related technologies, such as Figure 4 As shown in FIG. 1 , the synaesthesia integrated base station working in the single-base mode uses the existing 2D-DFT distance and speed acquisition method to sense two targets with the same radar cross section (RCS) and obtains Figure 4 The distance and speed radar diagram shown in the figure. One target is 120 meters away from the base station, and its radial speed relative to the base station is 30m / s; the other target is 140 meters away from the base station, and its radial speed relative to the base station is 20m / s. Figure 4 The two bright spots in the range-velocity radar diagram shown, i.e., the peak positions in the 2D-DFT results, can be used to read out the range and velocity of the two targets.

[0104] However, in the current distance and speed acquisition method based on 2D-DFT, the normalized modulation symbol matrix is ​​subjected to a second-order discrete Fourier transform: the modulation symbol matrix is ​​subjected to IDF T column by column, and then the result matrix is ​​subjected to DFT row by row to obtain the distance and speed information of the target to be sensed. The main disadvantage of this method is that the computational complexity is too high. When the accuracy of distance and speed acquisition is high, the order of discrete Fourier transform will be very high, and the computational complexity will be extremely high. Figure 1 Taking the perceptual signal waveform shown in the figure as an example, the computational complexity of a DFT is O(N 2 ), N is the order of DFT. Figure 1The computational complexity of performing 2D-DFT on a grid-shaped perceptual signal resource block of the perceptual signal waveform shown is 120 times of 120-dimensional IDFT operations and 120 times of 120-dimensional DFT operations. The total computational complexity is as high as 2NO(N 2 )=240O(N 2 ), that is, 2N 3 = 3456000 complex number multiplication operations are required to obtain a distance speed radar chart.

[0105] In response to the above-mentioned problems existing in the related art, the embodiments of the present application provide a distance and speed acquisition method, electronic device, apparatus and storage medium, by performing a discrete Fourier inverse transform on each column vector of the target matrix, and performing a discrete Fourier transform on some row vectors in the discrete Fourier inverse transform result matrix; or, performing a discrete Fourier transform on each row vector of the target matrix, and performing a discrete Fourier inverse transform on some column vectors in the discrete Fourier transform result matrix, thereby obtaining the distance information and speed information of each target to be perceived within the perception range while reducing the complexity.

[0106] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0107] In the embodiments of the present application, the term "plurality" refers to two or more than two, and other quantifiers are similar.

[0108] The technical solution provided in the embodiments of the present application can be applicable to a variety of systems, especially 6G systems.

[0109] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0110] The application scenarios of the embodiments of the present application may include: scenarios where the synaesthesia integration system working in the single-base mode needs to obtain distance and speed at the same time. For example, road monitoring scenarios, autonomous driving scenarios, drone detection scenarios, indoor factory monitoring scenarios, etc. The single-base mode synaesthesia integration system means that the transmitter and receiver that send the perception signal are in the same position in space, or the transmitter and receiver are the same hardware device.

[0111] Figure 5is one of the flow charts of the distance speed acquisition method provided in the embodiment of the present application, such as Figure 5 As shown, the execution subject of the method may be a perception signal processing module, which may be located in a synaesthesia integration system transmitter or a synaesthesia integration system receiver, or may be a separate perception signal processing module. The method includes at least the following steps:

[0112] Step 5011: Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range. Or,

[0113] Step 5012: Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0114] The target matrix is ​​determined based on the sensing signal matrix of the transmitting end and the sensing signal matrix of the receiving end, and is used to characterize the distance information and speed information of all the targets to be sensed within the sensing range.

[0115] Specifically, the perception signal processing module receives: the sender perception signal matrix d sent by the sender Tx (m,n), and the receiving end perception signal matrix d Rx (m,n).

[0116] The target matrix is ​​determined based on the sensing signal matrix of the transmitting end and the sensing signal matrix of the receiving end. Specifically, the sensing signal processing module converts the matrix d RX (m,n) is divided by matrix d term by term Tx (m,n), and obtain the target matrix D(m,n). This operation can eliminate the data information carried by the perception signal and only retain the distance information and speed information of the target to be perceived.

[0117] After obtaining the target matrix, the target matrix can be processed by column vectors first, or by row vectors first.

[0118] One implementation method is to first perform an IDFT transformation on each column vector of the target matrix, and then perform a DFT transformation on some of the row vectors in the IDFT transformation result matrix to obtain the distance information and speed information of each target to be sensed within the perception range. Specifically, by performing an IDFT transformation on each column vector of the target matrix, the distance information of the target to be sensed within the perception range can be obtained, and the number of targets to be sensed can also be estimated based on the IDFT transformation result. Therefore, when performing a DFT transformation on the row vectors of the IDFT transformation result matrix, only some necessary row vectors can be DFT transformed to obtain the speed information of the target to be sensed, and match it with the distance information of the target to be sensed, so as to obtain the distance information and speed information corresponding to each target to be sensed within the perception range, as well as the actual number of targets to be sensed.

[0119] One implementation method is to perform a DFT transformation on each row vector of the target matrix, and perform an IDFT transformation on some column vectors in the DFT transformation result matrix, so as to obtain the distance information and speed information of each target to be perceived within the perception range. Specifically, by performing a DFT transformation on each row vector of the target matrix, the speed information of the target to be perceived within the perception range can be obtained, and the number of targets to be perceived can also be estimated based on the DFT transformation result. Therefore, when performing an IDFT transformation on the column vectors of the DFT transformation result matrix, only some necessary column vectors can be IDFT transformed, so as to obtain the distance information of the target to be perceived, and match it with the speed information of the target to be perceived, so as to obtain the distance information and speed information corresponding to each target to be perceived within the perception range, as well as the actual number of targets to be perceived.

[0120] The distance and speed acquisition method provided in the embodiment of the present application performs a discrete Fourier inverse transform on each column vector of the target matrix and a discrete Fourier transform on some row vectors in the discrete Fourier transform result matrix; or, performs a discrete Fourier transform on each row vector of the target matrix and a discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, thereby obtaining the distance information and speed information of each target to be perceived within the perception range while reducing the complexity.

[0121] In some embodiments, in step 5011: after performing inverse discrete Fourier transform on each column vector of the target matrix, the following steps are further included:

[0122] Determines the number of rows of the partial row vectors in the inverse discrete Fourier transform result matrix.

[0123] Specifically, before performing discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix, the number of rows of some row vectors in the inverse discrete Fourier transform result matrix needs to be determined. Specifically, the number of rows can be determined based on the IDFT result vector of any column vector of the target matrix.

[0124] In some embodiments, in step 5011: after performing inverse discrete Fourier transform on each column vector of the target matrix, the following steps are further included:

[0125] Based on the element numbers of the inverse discrete Fourier transform result vector of any column vector of the target matrix whose values ​​are greater than the adjacent elements, the number of rows of some row vectors in the inverse discrete Fourier transform result matrix is ​​determined.

[0126] Specifically, any column vector in the target matrix contains N f elements, this N f The linear phase change of the elements contains the distance information of the target to be sensed, which can be obtained through IDFT transformation. f There will be one or more sampling point peaks among the sampling points, that is, N in the IDFT result vector f There are one or more local maxima in the elements, that is, there are one or more elements in the IDFT result vector whose values ​​are greater than the adjacent elements. According to the sequence numbers of these elements and the corresponding formulas, the distance information of the target to be sensed corresponding to each element can be determined.

[0127] Since the duration of a perception signal time-frequency resource block is extremely short, usually in the millisecond level, it can be considered that the distance of the target to be perceived remains approximately unchanged in multiple measurements within the time domain duration of the perception signal, that is, the distance information of the target to be perceived obtained based on the IDFT result vector of any column vector of the target matrix is ​​considered to be the same.

[0128] Based on the element numbers of the IDFT result vector of any column vector of the target matrix whose values ​​are greater than the adjacent elements, the number of rows of some row vectors in the IDFT result matrix is ​​determined. Specifically, when there are multiple element numbers, a number range is determined based on the element number with the smallest value and the element number with the largest value, corresponding to the number of rows of some row vectors that need to be DFT transformed in the IDFT result matrix. For example, the element number with the smallest value is 80 and the element number with the largest value is 93, then the number of rows of some row vectors is determined to be 80 to 93. In order to further improve the accuracy of the results, the number of rows of some row vectors can also be determined to be 78 to 95.

[0129] The distance speed acquisition method provided in the embodiment of the present application determines the number of rows of some row vectors that undergo DFT transformation in the IDFT result matrix through the element sequence number corresponding to the local maximum value in the IDFT result vector of any column vector of the target matrix, thereby reducing the computational complexity while ensuring the accuracy of the results.

[0130] In some embodiments, in step 5011: obtaining distance information and speed information of each target to be sensed within the sensing range includes:

[0131] Based on the element numbers of the discrete Fourier inverse transform result vector whose values ​​are greater than the adjacent elements, the distance information of all the targets to be sensed within the sensing range is obtained;

[0132] Based on the discrete Fourier transform result of any row vector in some row vectors in the discrete Fourier inverse transform result matrix, the speed information of all the targets to be sensed within the sensing range is obtained;

[0133] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0134] Specifically, any column vector in the target matrix contains N f elements, this N f The linear phase change of each element contains the distance information of the target to be sensed, which can be obtained through IDFT transformation. Similarly, any row vector in the target matrix contains N t elements, this N t The linear phase change of each element contains the speed information of the target to be sensed, which can be obtained through DFT transformation.

[0135] According to the IDFT result vector of any column vector in the target matrix, the distance information of all the targets to be sensed within the perception range can be obtained. Optionally, according to the number of local maxima in the IDFT result vector, the number of targets to be sensed can also be estimated. Further, according to the DFT result of any row vector in some row vectors in the IDFT result matrix, the speed information of all the targets to be sensed within the perception range can be obtained. Combined with the IDFT result vectors of all column vectors in the target matrix and the DFT results of some row vectors in the IDFT result vector matrix, the distance information and speed information of all the targets to be sensed within the perception range are matched to obtain the distance information and speed information of each target to be sensed within the perception range.

[0136] In some embodiments, in step 5011: after performing inverse discrete Fourier transform on each column vector of the target matrix, the following steps are further included:

[0137] The inverse discrete Fourier transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of some row vectors is determined based on the peak position in the range domain radar map.

[0138] Specifically, the radar chart can be used to determine the element number corresponding to the local maximum in the IDFT result vector of any column vector of the target matrix. The IDFT result vector of any row vector of the target matrix is ​​normalized to obtain the range domain radar chart.

[0139] The horizontal coordinate of the peak value in the range domain radar chart is the element number of the local maximum value in the IDFT result vector corresponding to any column vector of the target matrix.

[0140] In some embodiments, in step 5011: obtaining distance information and speed information of each target to be sensed within the sensing range includes:

[0141] Based on discrete Fourier transform results of some row vectors in the inverse discrete Fourier transform result matrix, a first range speed radar chart is obtained;

[0142] Based on the first distance and speed radar map, the distance information and speed information of each target to be sensed within the sensing range are obtained.

[0143] Specifically, with the help of the radar chart, a DFT transformation is performed on some row vectors in the IDFT result matrix to obtain a first distance-speed radar chart. The horizontal axis of the distance-speed radar chart is the speed, and the vertical axis is the distance. The number of bright spots in the distance-speed radar chart is the number of targets to be sensed, and the coordinates of the bright spots are the distance information and speed information of the corresponding targets to be sensed.

[0144] The distance speed acquisition method provided in the embodiment of the present application further reduces the complexity by normalizing and constructing a radar chart.

[0145] In some embodiments, in step 5012: after performing discrete Fourier transform on each row vector of the target matrix, the method further includes:

[0146] Determines the number of columns of the partial column vector in the discrete Fourier transform result matrix.

[0147] Specifically, before performing inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, the number of columns of some column vectors in the discrete Fourier transform result matrix needs to be determined. Specifically, the number of columns can be determined based on the DFT transform result vector of any row vector of the target matrix.

[0148] In some embodiments, in step 5012: after performing discrete Fourier transform on each row vector of the target matrix, the method further includes:

[0149] Based on the element numbers of the discrete Fourier transform result vector of any row vector of the target matrix whose values ​​are greater than the adjacent elements, the number of columns of some column vectors is determined.

[0150] Specifically, any row vector in the target matrix contains N t elements, this N t The linear phase change of N elements contains the speed information of the target to be sensed, which can be obtained through DFT transformation. t There will be one or more sampling point peaks among the sampling points, that is, N in the DFT result vector t There are one or more local maxima in the elements, that is, there are one or more elements in the DFT result vector whose values ​​are greater than the adjacent elements. According to the sequence numbers of these elements and the corresponding formulas, the speed information of the target to be sensed corresponding to each element can be determined.

[0151] Since the frequency difference between each subcarrier of a perception signal time-frequency resource block is extremely small compared to the carrier frequency, it can be considered that the Doppler frequency shift of the target to be perceived remains unchanged in each subcarrier, that is, the speed information of the target to be perceived obtained based on the DFT result vector of any row vector of the target matrix is ​​the same.

[0152] Based on the element numbers of the DFT result vector of any row vector of the target matrix that are greater than the adjacent elements, the number of columns of some column vectors in the DFT result matrix is ​​determined. Specifically, when there are multiple element numbers, a number range is determined based on the element number with the smallest value and the element number with the largest value, corresponding to the number of columns of some column vectors in the DFT result matrix that need to be IDFT transformed. For example, if the element number with the smallest value is 30 and the element number with the largest value is 41, the number of columns of some column vectors is determined to be 30 to 41. In order to further improve the accuracy of the results, the number of columns of some column vectors can also be determined to be 28 to 43.

[0153] The distance speed acquisition method provided in the embodiment of the present application determines the number of columns of some column vectors in the DFT result matrix that undergo IDFT transformation through the element sequence number corresponding to the local maximum value in the DFT result vector of any row vector of the target matrix, thereby reducing the computational complexity while ensuring the accuracy of the results.

[0154] In some embodiments, in step 5012: obtaining distance information and speed information of each target to be sensed within the sensing range includes:

[0155] Based on the element numbers of the discrete Fourier transform result vector whose values ​​are greater than the adjacent elements, the speed information of all the targets to be sensed within the sensing range is obtained;

[0156] Based on the inverse discrete Fourier transform result of any column vector in some column vectors in the discrete Fourier transform result matrix, the distance information of all the targets to be sensed within the sensing range is obtained;

[0157] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0158] Specifically, any column vector in the target matrix contains N f elements, this N f The linear phase change of each element contains the distance information of the target to be sensed, which can be obtained through IDFT transformation. Similarly, any row vector in the target matrix contains N t elements, this N t The linear phase change of each element contains the speed information of the target to be sensed, which can be obtained through DFT transformation.

[0159] According to the DFT result vector of any row vector in the target matrix, the speed information of all the targets to be perceived within the perception range can be obtained. Optionally, according to the number of local maxima in the DFT result vector, the number of targets to be perceived can also be estimated. Further, according to the IDFT result of any column vector in some row vectors in the DFT result matrix, the distance information of all the targets to be perceived within the perception range can be obtained. Combined with the DFT result vectors of all row vectors in the target matrix, and the IDFT results of some column vectors in the DFT result vector matrix, the distance information and speed information of all the targets to be perceived within the perception range are matched to obtain the distance information and speed information of each target to be perceived within the perception range.

[0160] In some embodiments, in step 5012: after performing discrete Fourier transform on each row vector of the target matrix, the method further includes:

[0161] The discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of some column vectors is determined based on the peak position in the velocity domain radar map.

[0162] Specifically, the radar chart can be used to determine the element number corresponding to the local maximum value in the DFT result vector of any row vector of the target matrix. The DFT result vector of any row vector of the target matrix is ​​normalized to obtain the velocity domain radar chart.

[0163] The horizontal coordinate of the peak value in the velocity domain radar chart is the element number of the local maximum value in the DFT result vector corresponding to any row vector of the target matrix.

[0164] In some embodiments, in step 5012: obtaining distance information and speed information of each target to be sensed within the sensing range includes:

[0165] Based on the inverse discrete Fourier transform results of some column vectors in the discrete Fourier transform result matrix, a second range speed radar chart is obtained;

[0166] Based on the second distance and speed radar chart, the distance information and speed information of each target to be sensed within the sensing range are obtained.

[0167] Specifically, with the help of the radar chart, IDFT transformation is performed on some column vectors in the DFT result matrix to obtain a second distance and speed radar chart. The horizontal axis of the distance and speed radar chart is the speed, and the vertical axis is the distance. The number of bright spots in the distance and speed radar chart is the number of targets to be sensed, and the coordinates of the bright spots are the distance information and speed information of the corresponding targets to be sensed.

[0168] The distance speed acquisition method provided in the embodiment of the present application further reduces the complexity by normalizing and constructing a radar chart.

[0169] In some embodiments, the distance and speed acquisition method further includes:

[0170] Based on the relationship between the distance information of each target to be perceived within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be perceived within the perception range and the preset maximum detection speed, adjust the sending density of the perception resources within the perception range.

[0171] Specifically, after obtaining the distance information and speed information of each target to be sensed within the sensing range, the sending density of the sensing resources within the sensing range can be adjusted. Specifically, it can be: when the distance of the target is close to the maximum detection distance, increase the density of the frequency domain sensing resources to increase the maximum sensing distance; when the speed of the target is close to the maximum detection speed, increase the density of the time domain sensing resources to increase the maximum sensing speed; when the distance of the perceived target is already very different from the maximum detection distance, or when the speed of the perceived target is very different from the maximum detection speed, reduce the density of the frequency domain and / or time domain sensing resources to reduce the sensing signal overhead.

[0172] The technical solution of the embodiments of the present application is further described below through several specific examples.

[0173] The transmitter of the synaesthesia integrated system sends a rectangular sensing signal resource block with a certain bandwidth and duration according to the distance and speed acquisition index requirements. Figure 1The sensing signal resource block shown has a bandwidth of 100MHz and a duration of 7.5ms, which can achieve distance resolution of 1.5m, speed resolution of 0.71m / h, maximum detection distance of 180m, and maximum detection speed of 85m / s. The transmitter sends the sensing signal d Tx (m,n). Perception signal d Tx (m,n) is reflected by the target in space, and the echo is received by the receiver. The sensing signal received by the receiver is d Rx (m,n). The sender sends the sensed signal d Tx (m,n), the receiving end will receive the sensing signal d Rx (m,n) is transmitted to the sensory signal processing module for processing. The sensory signal processing module converts the matrix d Rx (m,n) is divided by matrix d term by term Tx (m,n) can eliminate the data information carried by the perception signal and only retain the distance and speed information of the target to be perceived. The matrix after item-by-item division is expressed as D(m,n) as follows:

[0174]

[0175] Example 1: The number of velocity domain DFT operations is reduced by using the distance domain IDFT result to reduce the computational complexity of the 2D-DFT distance-velocity acquisition method.

[0176] The matrix D(m,n) is a matrix with 120 rows and 120 columns. The first column vector (D(0,0), D(1,0), ..., D(N)) of D(m,n) is processed by the sensor signal processing module. f -1,0)) to perform a 120-order IDFT operation, and we can get a vector with 120 elements (Y r (0,0),Y r (1,0),……,Y r (N f -1,0)). By vector (Y r (0,0),Y r (1,0),……,Y r (N f -1,0)) can be used to obtain a range domain radar chart, and the distance information of the target to be sensed within the sensing range can be solved by the peak position IDFT index number in the range domain radar chart.

[0177] Assume that there are two targets within the sensing range, one of which is 120 meters away from the synesthesia integrated base station, and its radial speed relative to the synesthesia integrated base station is 30 m / s; the other target is 140 meters away from the synesthesia integrated base station, and its radial speed relative to the synesthesia integrated base station is 20 m / s. Figure 6The distance domain radar map provided by the embodiment of the present application is obtained by performing IDFT operation on the first column vector of D(m,n) by the perception signal processing module. Figure 6 As shown. The target at a distance of 120 meters forms a peak at IDFT index number 80, and the target at a distance of 140 meters forms a peak at IDFT index number 93. Since the RCS of the two targets is the same, the echo signal power of the target at a distance of 120 meters is 2.7 dB higher than that of the target at a distance of 140 meters, that is, the peak at index number 80 is 2.7 dB higher than the peak at index number 93. From IDFT index numbers 80 and 93, the perception signal processing module can calculate that the distances of the two targets are 120 meters and 140 meters respectively.

[0178] The sensor signal processing module performs IDFT operation on each column vector of D(m,n) until the last column vector of D(m,n) is subjected to 120-order IDFT operation, and a vector (Y r (0,N t -1),Y r (1,N t -1),……,Y r (N f -1,N t -1)). By vector (Y r (0,N t -1),Y r (1,N t -1),……,Y r (N f -1,N t -1)) can obtain a range domain radar map, in which the IDFT index number of the peak value contains the distance information of the target to be sensed within the sensing range.

[0179] The sensor signal processing module performs 120 IDFT operations on D(m,n) to obtain 120 range domain radar images. Since the duration of a sensor signal time-frequency resource block is extremely short (7.5ms), it can be considered that the distance between the two targets remains approximately unchanged during the 120 measurements of 7.5ms. That is, the range domain radar images obtained by the 120 IDFT operations are the same, as shown in Figure 6 As shown in Figure 2, the perception signal processing module can estimate the number of targets to be perceived within the perception range based on the number of peaks in the range domain radar map. Figure 6 There are two peaks in the radar chart, and the signal processing module estimates that there are two targets to be sensed within the sensing range.

[0180] Furthermore, the perception signal processing module is only in D rThe DFT operation is performed on the necessary rows (m, n), thereby reducing the computational complexity of the existing 2D-DFT distance speed acquisition method.

[0181] The processing process of the existing 2D-DFT distance speed acquisition method is: the results of the above 120 IDFTs, that is, 120 N f Dimensional vector (Y r (0,0),Y r (1,0),……,Y r (N f -1,0))、(Y r (0,1),Y r (1,1),……,Y r (N f -1,1))、......、(Y r (0,N t -1),Y r (1,N t -1),……,Y r (N f -1,N t -1)) Transpose and arrange into matrix D r (m,n):

[0182]

[0183] Right D r Any row of (m,n), for example, the mth row vector (Y r (m,0),Y r (m,1),......,Y r (m,N t -1)) Do 120 steps (N t =120) DFT operation, we can get a vector with 120 elements (Y rv (m,0),Y rv (m,1),......,Y rv (m,N t -1)). By vector (Y rv (m,0),Y rv (m,1),......,Y rv (m,N t -1)) can be used to obtain a speed domain radar chart, where the peak value in the speed domain radar chart contains the speed information of the target to be sensed within the sensing range.

[0184] Figure 7 is one of the speed domain radar diagrams provided in the embodiment of the present application, such as Figure 7As shown, a target with a speed of 20 m / s forms a peak at the DFT index number 28, and a target with a speed of 30 m / s forms another peak at the DFT index number 42. The speeds of the two targets can be solved from the index numbers 28 and 42.

[0185] Right D r Although the speed of the two targets can be obtained by performing DFT on any row vector of (m,n), the target speeds obtained at this time cannot match the distances obtained above, that is, it is not possible to determine whether the speed of a target at a distance of 120 meters is 20m / s or 30m / s, and it is not possible to determine whether the speed of a target at a distance of 140 meters is 20m / s or 30m / s. r Each row of (m,n) is subjected to 120-order DFT operation, and a total of N f N t dimensional vector. f N t N-dimensional vector composition f Row N t The matrix D of columns rv (m,n):

[0186]

[0187] D rv (m,n) is plotted as a two-dimensional graph to obtain Figure 4 The distance speed radar chart shown, Figure 4 Each bright spot in the image corresponds to the distance and speed of a target, that is, the distance and speed of each target are matched.

[0188] In the embodiment of the present application, the processing is simplified: the perception signal processing module only processes D according to the IDFT index number of the peak in the range domain radar map. r The target distance and speed can be solved by performing DFT operation on the necessary rows in (m,n) without the need to calculate D r DFT operation is performed on each row of (m,n). Figure 4 As an example, the sensing signal processing module processes D r The 79th to 95th lines of (m,n) vector (Y r (78,0),Y r (78,1),......,Y r (78,N t -1)) to (Y r (94,0),Y r (94,1),......,Y r (94,N t -1)) After 17 120-order DFT operations, we get 17 N tdimensional vector. t Dimensional vector composed of 17 rows N t The matrix D of columns rv ′(m,n):

[0189]

[0190] Figure 8 is one of the distance speed radar images provided in the embodiment of the present application. The sensing signal processing module converts D rv ′(m,n) is plotted as a two-dimensional graph to obtain Figure 8 The distance speed radar chart shown is from Figure 8 Two bright spots can be read from the radar chart, and the distance and speed of the two targets can be obtained from the horizontal and vertical coordinates of the bright spots.

[0191] Since it has been estimated that there are two targets to be sensed within the sensing range, r (m,n) row 1 (Y r (0,0),Y r (0,1),......,Y r (0,N t -1)) to line 78 (Y r (77,0),Y r (77,1),......,Y r (77,N t -1)), and row 96 (Y r (95,0),Y r (95,1),......,Y r (95,N t -1)) to the last row (Y r (N f -1,0),Y r (N f -1,1),......,Y r (N f -1,N t -1))) The DFT calculations are not necessary, and these DFT calculations cannot obtain more distance and speed information of the two targets to be sensed.

[0192] By not performing these DFT operations, the computational complexity of the 2D-DFT distance and speed acquisition method can be reduced, and at the same time, the time delay of the 2D-DFT distance and speed acquisition method in obtaining distance and speed measurements can be reduced.

[0193] Fig. 9 This is a flow chart of the distance speed acquisition method provided in the embodiment of the present application. The flow chart of the low computational complexity 2D-DFT distance speed acquisition method described in Example 1 is as follows: Fig. 9 shown.

[0194] In Example 1, the low computational complexity 2D-DFT distance speed acquisition method proposed in the embodiment of the present application performs IDFT operation 120 times on the columns of the matrix D(m,n). r The row (m, n) performs DFT operation 17 times. Compared with the existing 2D-DFT distance and speed acquisition method which needs to perform 240 DFT operations, the computational complexity is reduced by (240-120-17) / 240=43%.

[0195] Example 2: If there are two targets to be sensed within the sensing range, one of which is 20 meters away and has a speed of 30 m / s; the other is 30 meters away and has a speed of 20 m / s.

[0196] Fig.10 This is the second distance speed radar diagram provided in the embodiment of the present application, such as Fig.10 As shown, using the existing 2D-FFT distance and speed acquisition method, 240 DFT operations are required to obtain Fig.10 Radar chart shown.

[0197] Fig.11 This is the third distance speed radar diagram provided in the embodiment of the present application, such as Fig.11 As shown, using the distance speed acquisition method provided in Example 1, it is only necessary to perform IDFT operations 120 times on the columns of the matrix D(m,n). r The (m, n) row is subjected to DFT operation 8 times, and two target bright spots in the radar image can be identified. Compared with the existing 2D-DFT distance and speed acquisition method, the computational complexity is reduced by (240-120-8) / 240=47%.

[0198] Example 3: The low computational complexity 2D-DFT distance and speed acquisition method in Example 1 may have the problem of misestimation of the number of targets to be sensed when the distances of multiple targets to be sensed are the same. Fig.12 This is the fourth distance speed radar diagram provided in the embodiment of the present application, such as Fig.12 As shown in FIG. 1 , a radar image is obtained by sensing two targets using the existing 2D-DFT distance-speed acquisition periodogram algorithm. The distance between the two targets is 100 meters, the speed of one target is 20 m / s, and the speed of the other target is 50 m / s.

[0199] Fig.13 This is the second speed domain radar diagram provided in the embodiment of the present application, such as Fig.13As shown in the figure, using the low computational complexity 2D-DFT distance and speed acquisition method in Example 1, since the distance between the two targets to be sensed is 100 meters, the distance domain radar chart obtained by performing IDFT operation on each column vector of D(m,n) only contains one peak at IDFT index number 67. The number of targets to be sensed is incorrectly estimated to be 1.

[0200] Right D r The 67th row vector (Y r (66,0),Y r (66,1),......,Y r (66,N t -1)) to line 69 vector (Y r (68,0),Y r (68,1),......,Y r (68,N t -1)) Do 120 steps 3 times (N t =120) After DFT operation, we get 3 N t dimensional vector. t dimensional vectors consisting of 3 rows N t Matrix of columns

[0201]

[0202] Fig.14 This is the fifth distance speed radar diagram provided in the embodiment of the present application, such as Fig.14 As shown, D rv The model of each element of ′(m,n) is drawn into a two-dimensional graph, the distance speed radar chart, Fig.14 Two bright spots can be read in the radar chart. When the number of bright spots is greater than the estimated number of targets to be sensed, and the intensity of multiple bright spots is the same (the peak amplitude is the same because the distance is the same), it can be determined that there are multiple targets to be sensed with the same distance and different speeds within the sensing range. The distance and speed of each target can be obtained from the horizontal and vertical coordinates of each bright spot.

[0203] Example 4: The number of distance domain IDFT operations is reduced by using the velocity domain DFT results to reduce the computational complexity of the 2D-DFT distance-velocity acquisition method.

[0204] The matrix D(m,n) is a matrix with 120 rows and 120 columns. The perception signal processing module processes the first row vector (D(0,0), D(0,1), ..., D(0,N) of D(m,n). t -1)) Perform a 120-order DFT operation to obtain a vector with 120 elements (Y v (0,0),Y v(0,1),……,Y v (0,N t -1)). By vector (Y v (0,0),Y v (0,1),……,Y v (0,N t -1)) can be used to obtain a speed domain radar chart, and the speed of the target to be sensed within the sensing range can be solved by the DFT index number of the peak position in the speed domain radar chart.

[0205] Assume that there are two targets within the sensing range, one of which is 120 meters away from the synaesthesia base station and has a radial velocity of 30 m / s relative to the synaesthesia base station; the other is 140 meters away from the synaesthesia base station and has a radial velocity of 20 m / s relative to the synaesthesia base station. The velocity domain radar image obtained by the sensing signal processing module after performing DFT on the first row vector of the matrix D(m,n) is as follows: Figure 7 As shown in the figure, a target with a speed of 20 m / s forms a peak at DFT index number 28, and a target with a speed of 30 m / s forms a peak at DFT index number 42. Based on DFT index numbers 28 and 42, the perception signal processing module can calculate that the speeds of the two targets are 20 m / s and 30 m / s respectively.

[0206] The perception signal processing module performs DFT operation on each row of vectors of D(m,n) until the last row of vectors of D(m,n) is subjected to 120-order DFT operation, and a vector (Y v (N f -1,0),Y v (N f -1,1),……,Y v (N f -1,N t -1)). By vector (Y v (N f -1,0),Y v (N f -1,1),……,Y v (N f -1,N t -1)) can obtain a speed domain radar map, and the peak DFT sequence number in the speed domain radar map contains the speed information of the target to be sensed within the sensing range.

[0207] The sensor signal processing module performs 120 DFT operations on D(m,n) to obtain 120 velocity domain radar images. Since the frequency difference between each subcarrier of a sensor signal time-frequency resource block is very small compared to the carrier frequency, it can be considered that the Doppler frequency shift of the two targets remains unchanged in each subcarrier. That is, the velocity domain radar images obtained by 120 DFT operations are the same. Figure 7 As shown in Figure 2, the perception signal processing module can estimate the number of targets to be perceived within the perception range based on the number of peaks in the speed domain radar map. Figure 7 There are two peaks in the speed domain radar map, and the signal processing module estimates that there are two targets to be sensed within the sensing range.

[0208] Furthermore, the perception signal processing module is only in D v The IDFT operation is performed on the necessary column positions (m, n), thereby reducing the computational complexity of the existing 2D-DFT distance velocity acquisition method.

[0209] The processing process of the existing 2D-DFT distance and speed acquisition method is: the above 120 DFT results, that is, 120 N t Dimensional vector (Y v (0,0),Y v (0,1),……,Y v (0,N t -1))、(Y v (1,0),Y v (1,1),……,Y v (1,N t -1))、......、(Y v (N f -1,0),Y v (N f -1,1),……,Y v (N f -1,N t -1)) Arrange into matrix D v (m,n):

[0210]

[0211] Right D v Any column of (m,n), for example, the nth column vector (Y v (0,n),Y r (1,n),......,Y r (N f -1,n))120-order IDFT operation can obtain a vector with 120 elements (Y rv (0,n),Y rn (1,n),......,Y rv (N f -1,n)). By vector (Y rv (0,n),Y rv (1,n),......,Y rv (N f -1,n)) can be obtained as follows Figure 7 In the range domain radar chart shown, a target with a distance of 120 meters forms a peak at IDFT index number 80, and a target with a distance of 140 meters forms another peak at IDFT index number 93. The distances of the two targets can be calculated from index numbers 80 and 93.

[0212] Right D v Although the distance between two targets can be obtained by performing IDFT on any column vector of (m,n), the target distance obtained at this time cannot match the speed obtained above, that is, it is uncertain whether the distance of a target with a speed of 20m / s is 120m or 140m, and it is uncertain whether the distance of a target with a speed of 30m / s is 120m or 140m. r Each column of (m,n) is subjected to 120-order IDFT operation, and a total of N t N f dimensional vector. t N f N-dimensional vector composition f Row N t The matrix D of columns rv (m,n):

[0213]

[0214] D rv (m,n) is plotted as a two-dimensional graph to obtain Figure 4 The distance speed radar chart shown is Figure 4 Each bright spot in the image corresponds to the distance and speed of a target, that is, the distance and speed of each target are matched.

[0215] In the embodiment of the present application, it is simplified as follows: the perception signal processing module only processes DFT according to the number of targets to be perceived within the perception range obtained in step 1 and the DFT index number of the peak value. v The IDFT operation is performed on the necessary columns in (m,n) to solve the target range and speed without the need to calculate D v IDFT operation is performed on each column of (m,n). Figure 4 As an example, the sensing signal processing module processes D v The vectors (Y v (0,27),Y v (1,27),......,Y v (N f -1,27)) to (Y vv (0,42),Y v (1,42),......,Y v (N f-1,42)) After 16 120-order IDFT operations, 16 N f dimensional vector. f N-dimensional vector composition f Matrix D with 16 rows and columns rv ″(m,n):

[0216]

[0217] Fig.15 This is the sixth radar diagram of the distance and speed domain provided in the embodiment of the present application. The perception signal processing module converts D rv ″(m,n) is plotted as a two-dimensional graph to obtain Fig.15 The distance speed radar chart shown is from Fig.15 Two bright spots can be read from the radar chart, and the distance and speed of the two targets can be obtained from the horizontal and vertical coordinates of the bright spots.

[0218] Since it has been estimated that there are two targets to be sensed within the sensing range, v (m,n) Column 1 ((Y v (0,0),Y v (1,0),......,Y v (N f -1,0)) to column 27 (Y v (0,26),Y v (1,26),......,Y v (N f -1,26)) and the 44th column ((Y v (0,43),Y v (1,43),......,Y v (N f -1,43)) to the last column (Y v (0,N t -1),Y v (1,N t -1),......,Y v (N f -1,N t -1))) is no longer necessary, and these IDFT calculations cannot obtain more distance and speed information of the two targets to be sensed.

[0219] By not performing these IDFT operations, the computational complexity of the 2D-DFT distance-speed periodogram acquisition algorithm can be reduced, and at the same time, the delay of the 2D-DFT distance-speed periodogram acquisition algorithm in obtaining distance-speed measurements can be reduced.

[0220] Fig.16This is a flow chart of the distance speed acquisition method provided in the embodiment of the present application. The flow chart of the low computational complexity 2D-DFT distance speed acquisition method described in Example 4 is as follows: Fig.16 shown.

[0221] In Example 4, the low computational complexity 2D-DFT distance and speed acquisition periodogram algorithm proposed in the embodiment of the present application only needs to perform DFT operations 120 times on the rows of the matrix D(m,n) and perform IDFT operations 16 times on the columns of the matrix D_v(m,n) to identify the two target bright spots in the radar map. Compared with the existing 2D-DFT distance and speed acquisition periodogram algorithm, the computational complexity is reduced by (240-120-16) / 240=42%.

[0222] Example 5: The low computational complexity 2D-DFT distance and speed acquisition method in Example 4 may have the problem of misestimation of the number of targets to be sensed when the speeds of multiple targets to be sensed are the same. Fig.17 This is the seventh distance speed radar diagram provided in the embodiment of the present application, such as Fig.17 As shown in FIG. 1 , a radar image is obtained by sensing two targets using the existing 2D-DFT distance-speed periodogram algorithm. The speed of both targets is 30 m / s, the distance of one target is 50 meters, and the distance of the other target is 100 meters.

[0223] Fig.18 This is the eighth distance speed radar diagram provided by the embodiment of the present application, such as Fig.18 As shown, using the low computational complexity 2D-DFT distance-speed periodogram acquisition algorithm proposed in Example 4, since the speeds of the two targets are both 30 m / s, the radar chart obtained by performing DFT calculations on each row vector of D(m,n) contains only one peak at DFT index number 42, so the number of targets to be sensed will be incorrectly estimated to be one.

[0224] Right D v The 42nd to 44th vectors of (m,n) are calculated three times using formula (5) of 120 order (N f =120) After IDFT operation, we get 3 N f dimensional vector. f N-dimensional vector composition f Matrix D with 3 rows and 3 columns rv ″(m,n).

[0225]

[0226] Fig.19 This is the ninth distance speed radar diagram provided in the embodiment of the present application, such as Fig.19 As shown, D rvThe model of each element of ″(m,n) is plotted into a two-dimensional graph to obtain the distance speed radar map. Fig.19 Two bright spots can be read in the radar chart. When the number of bright spots is greater than the estimated number of targets to be sensed, it can be determined that there are multiple targets to be sensed with the same speed but different distances within the sensing range. The distances and speeds of the multiple targets can be obtained from the horizontal and vertical coordinates of each bright spot.

[0227] Example 6: Assume that the target to be sensed obtained in Example 1 is 170 meters away from the inter-sensing integrated base station and has a speed of 80m / s. Then the target may be at a distance exceeding the maximum sensing distance of 180m and a speed exceeding the maximum sensing speed of 85m / s. The sensing signal processing module has preset maximum distance and speed thresholds. For example, the maximum distance threshold of the target is 160m, and the maximum speed threshold of the target is 75m / s.

[0228] When the perception signal processing module senses that the distance and speed of the target exceeds the preset maximum distance and speed threshold, the perception signal processing module will send a perception signal configuration change command to the transmitter of the synaesthesia integration system to transmit the perception signal with a higher density in the frequency domain and time domain to increase the maximum perception distance and maximum perception speed.

[0229] At the same time, the perception signal processing module will send a perception signal configuration notification to the synaesthesia integration system receiving end. After the receiving end obtains the new perception signal configuration, it will receive the d Rx (m,n). For example, Fig. 20 is one of the perception signal waveforms provided in the embodiment of the present application, such as Fig. 20 As shown, after the new perception signal waveform takes effect, the new perception waveform will increase the supported maximum perception distance and maximum perception speed to 625 meters and 320m / s.

[0230] Example 7: Assume that the target to be sensed obtained in Example 1 is 50 meters away from the telepathic integrated base station and its speed is 10m / s. Then the distance and speed of the target are much smaller than Figure 1 The maximum sensing distance and maximum sensing speed supported by the sensing signal waveform shown. The sensing signal processing module is preset with a minimum distance and speed threshold. For example, the target minimum distance threshold is 60m, and the target minimum speed threshold is 30m / s.

[0231] When the perception signal processing module senses that the distance speed of the target is less than the preset minimum distance speed threshold, the perception signal processing module will send a perception signal configuration change command to the transmitter of the synaesthesia integration system to transmit the perception signal with a smaller density in the frequency domain and time domain to reduce the maximum perception distance and maximum perception speed, thereby achieving the purpose of reducing the perception signal overhead.

[0232] At the same time, the perception signal processing module will send a perception signal configuration notification to the synaesthesia integration system receiving end. After the receiving end obtains the new perception signal configuration, it will receive the d Rx (m,n). For example, Fig.21 This is the second perception signal waveform diagram provided in the embodiment of the present application, such as Fig.21 As shown in the figure, after the new sensing signal waveform takes effect, the new sensing waveform will reduce the maximum sensing distance and maximum sensing speed supported by it to 90 meters and 42 m / s. The benefits brought are that the sensing signal overhead is reduced by 75% and the 2D-DFT calculation complexity is reduced by 75%.

[0233] Fig. 22 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Fig. 22 As shown, the terminal includes a memory 2201, a transceiver 2202, and a processor 2203, wherein:

[0234] The memory 2201 is used to store computer programs; the transceiver 2202 is used to send and receive data under the control of the processor 2203.

[0235] Specifically, the transceiver 2202 is used to receive and send data under the control of the processor 2203.

[0236] Among them, Fig. 22 In the embodiment, the bus architecture may include any number of interconnected buses and bridges, specifically linking together various circuits of one or more processors represented by processor 2203 and memory represented by memory 2201. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface.

[0237] The transceiver 2202 may be a plurality of components, i.e., a transmitter and a receiver, and provides a unit for communicating with various other devices on a transmission medium, such as a wireless channel, a wired channel, an optical cable, etc. The processor 2203 is responsible for managing the bus architecture and general processing, and the memory 2201 may store data used by the processor 2203 when performing operations.

[0238] Processor 2203 can be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a complex programmable logic device (CPLD), and the processor can also adopt a multi-core architecture.

[0239] The processor 2203 is configured to read the computer program in the memory 2201 and perform the following operations:

[0240] Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; or,

[0241] Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range;

[0242] The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

[0243] In some embodiments, the processor 2203, for reading the computer program in the memory 2201, further performs the following operations:

[0244] The number of rows of the partial row vectors is determined based on the element numbers of the elements whose values ​​are greater than the adjacent elements in the discrete Fourier inverse transform result vector of any column vector of the target matrix.

[0245] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0246] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the inverse discrete Fourier transform result vector, obtaining the distance information of all the targets to be sensed within the sensing range;

[0247] Based on the discrete Fourier transform result of any row vector in the partial row vectors in the discrete Fourier inverse transform result matrix, obtaining the speed information of all the targets to be sensed within the sensing range;

[0248] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0249] In some embodiments, the processor 2203, for reading the computer program in the memory 2201, further performs the following operations:

[0250] A discrete Fourier inverse transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of the partial row vector is determined based on a peak position in the range domain radar map.

[0251] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0252] Based on the discrete Fourier transform results of the part of row vectors in the inverse discrete Fourier transform result matrix, obtaining a first range-speed radar chart;

[0253] Based on the first distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0254] In some embodiments, the processor 2203, for reading the computer program in the memory 2201, further performs the following operations:

[0255] The number of columns of the partial column vectors is determined based on the element numbers of the discrete Fourier transform result vectors of any row vector of the target matrix whose values ​​are greater than the adjacent elements.

[0256] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0257] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the discrete Fourier transform result vector, obtaining the speed information of all the targets to be sensed within the sensing range;

[0258] Based on the inverse discrete Fourier transform result of any column vector in the partial column vectors in the discrete Fourier transform result matrix, obtaining distance information of all to-be-perceived targets within the perception range;

[0259] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0260] In some embodiments, the processor 2203, for reading the computer program in the memory 2201, further performs the following operations:

[0261] A discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of the partial column vector is determined based on a peak position in the velocity domain radar map.

[0262] In some embodiments, obtaining the distance information and speed information of each target to be sensed within the sensing range includes:

[0263] Based on the inverse discrete Fourier transform results of the part of column vectors in the discrete Fourier transform result matrix, obtaining a second range-speed radar chart;

[0264] Based on the second distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0265] In some embodiments, the processor 2203, for reading the computer program in the memory 2201, further performs the following operations:

[0266] Based on the relationship between the distance information of each target to be sensed within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be sensed within the perception range and the preset maximum detection speed, the sending density of the perception resources within the perception range is adjusted.

[0267] It should be noted here that the above-mentioned electronic device provided by the embodiment of the present invention can implement all the method steps implemented by the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects that are the same as the method embodiment in this embodiment will not be described in detail here.

[0268] Fig.23 is a schematic diagram of the structure of the distance and speed acquisition device provided in the embodiment of the present application. Fig.23 As shown, the device comprises:

[0269] The first acquisition unit 2301 is used to perform a discrete Fourier inverse transform on each column vector of the target matrix, and to perform a discrete Fourier transform on some row vectors in the discrete Fourier inverse transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range; or

[0270] The second acquisition unit is used to perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range;

[0271] The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

[0272] In some embodiments, the first acquiring unit 2301 is further used to:

[0273] The number of rows of the partial row vectors is determined based on the element numbers of the elements whose values ​​are greater than the adjacent elements in the discrete Fourier inverse transform result vector of any column vector of the target matrix.

[0274] In some embodiments, the first acquiring unit 2301 is further used to:

[0275] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the inverse discrete Fourier transform result vector, obtaining the distance information of all the targets to be sensed within the sensing range;

[0276] Based on the discrete Fourier transform result of any row vector in the partial row vectors in the discrete Fourier inverse transform result matrix, obtaining the speed information of all the targets to be sensed within the sensing range;

[0277] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0278] In some embodiments, the first acquiring unit 2301 is further used to:

[0279] A discrete Fourier inverse transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of the partial row vector is determined based on a peak position in the range domain radar map.

[0280] In some embodiments, the first acquiring unit 2301 is further used to:

[0281] Based on the discrete Fourier transform results of the part of row vectors in the inverse discrete Fourier transform result matrix, obtaining a first range-speed radar chart;

[0282] Based on the first distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0283] In some embodiments, the second acquiring unit 2302 is further configured to:

[0284] The number of columns of the partial column vectors is determined based on the element numbers of the discrete Fourier transform result vectors of any row vector of the target matrix whose values ​​are greater than the adjacent elements.

[0285] In some embodiments, the second acquiring unit 2302 is further configured to:

[0286] Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the discrete Fourier transform result vector, obtaining the speed information of all the targets to be sensed within the sensing range;

[0287] Based on the inverse discrete Fourier transform result of any column vector in the partial column vectors in the discrete Fourier transform result matrix, obtaining distance information of all to-be-perceived targets within the perception range;

[0288] The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

[0289] In some embodiments, the second acquiring unit 2302 is further configured to:

[0290] A discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of the partial column vector is determined based on a peak position in the velocity domain radar map.

[0291] In some embodiments, the second acquiring unit 2302 is further configured to:

[0292] Based on the inverse discrete Fourier transform results of the part of column vectors in the discrete Fourier transform result matrix, obtaining a second range-speed radar chart;

[0293] Based on the second distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

[0294] In some embodiments, the apparatus further comprises:

[0295] An adjustment unit is used to adjust the sending density of the perception resources within the perception range based on the relationship between the distance information of each target to be perceived within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be perceived within the perception range and the preset maximum detection speed.

[0296] The methods and devices provided in the various embodiments of the present application are based on the same application concept. Since the methods and devices solve problems based on similar principles, the implementation of the devices and methods can refer to each other, and the repeated parts will not be repeated.

[0297] It should be noted that the division of units in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional unit in each embodiment of the present application may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0298] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (Processor) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0299] It should be noted here that the above-mentioned device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0300] On the other hand, an embodiment of the present application further provides a non-transitory readable storage medium, wherein the processor-readable storage medium stores a computer program, wherein the computer program is used to enable the processor to execute the distance speed method provided in the above embodiments, for example, including:

[0301] Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; or,

[0302] Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range;

[0303] The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

[0304] The non-transitory readable storage medium can be any available medium or data storage device that can be accessed, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)), etc.

[0305] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0306] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer executable instructions. These computer executable instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0307] These processor executable instructions may also be stored in a processor readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the processor readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0308] These processor-executable instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0309] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A distance speed acquisition method, characterized in that: include: Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; or, Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

2. The distance speed acquisition method according to claim 1, characterized in that: After performing inverse discrete Fourier transform on each column vector of the target matrix, the method further includes: The number of rows of the partial row vectors is determined based on the element numbers of the elements whose values ​​are greater than the adjacent elements in the discrete Fourier inverse transform result vector of any column vector of the target matrix.

3. The distance speed acquisition method according to claim 2, characterized in that: The obtaining of distance information and speed information of each target to be sensed within the sensing range includes: Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the inverse discrete Fourier transform result vector, obtaining the distance information of all the targets to be sensed within the sensing range; Based on the discrete Fourier transform result of any row vector in the partial row vectors in the discrete Fourier inverse transform result matrix, obtaining the speed information of all the targets to be sensed within the sensing range; The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

4. The distance speed acquisition method according to claim 1, characterized in that: After performing inverse discrete Fourier transform on each column vector of the target matrix, the method further includes: A discrete Fourier inverse transform result vector of any column vector of the target matrix is ​​normalized to obtain a range domain radar map, and the number of rows of the partial row vector is determined based on a peak position in the range domain radar map.

5. The distance speed acquisition method according to claim 4, characterized in that: The obtaining of distance information and speed information of each target to be sensed within the sensing range includes: Based on the discrete Fourier transform results of the part of row vectors in the inverse discrete Fourier transform result matrix, obtaining a first range-speed radar chart; Based on the first distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

6. The distance speed acquisition method according to claim 1, characterized in that: After performing discrete Fourier transform on each row vector of the target matrix, the method further includes: The number of columns of the partial column vectors is determined based on the element numbers of the discrete Fourier transform result vectors of any row vector of the target matrix whose values ​​are greater than the adjacent elements.

7. The distance speed acquisition method according to claim 6, characterized in that: The obtaining of distance information and speed information of each target to be sensed within the sensing range includes: Based on the sequence numbers of elements whose values ​​are greater than the adjacent elements in the discrete Fourier transform result vector, obtaining the speed information of all the targets to be sensed within the sensing range; Based on the inverse discrete Fourier transform result of any column vector in the partial column vectors in the discrete Fourier transform result matrix, obtaining distance information of all to-be-perceived targets within the perception range; The distance information and speed information of all the targets to be sensed within the sensing range are matched to obtain the distance information and speed information of each target to be sensed within the sensing range.

8. The distance speed acquisition method according to claim 1, characterized in that: After performing discrete Fourier transform on each row vector of the target matrix, the method further includes: A discrete Fourier transform result vector of any row vector of the target matrix is ​​normalized to obtain a velocity domain radar map, and the number of columns of the partial column vector is determined based on a peak position in the velocity domain radar map.

9. The distance speed acquisition method according to claim 8, characterized in that: The obtaining of distance information and speed information of each target to be sensed within the sensing range includes: Based on the inverse discrete Fourier transform results of the part of column vectors in the discrete Fourier transform result matrix, obtaining a second range-speed radar chart; Based on the second distance and speed radar map, distance information and speed information of each target to be sensed within the sensing range are obtained.

10. The distance speed acquisition method according to any one of claims 1 to 9, characterized in that: The method further comprises: Based on the relationship between the distance information of each target to be sensed within the perception range and the preset maximum detection distance, and / or the relationship between the speed information of each target to be sensed within the perception range and the preset maximum detection speed, the sending density of the perception resources within the perception range is adjusted.

11. An electronic device comprising a memory, a transceiver, and a processor; characterized in that: A memory for storing a computer program; a transceiver for transmitting and receiving data under the control of the processor; and a processor for reading the computer program in the memory and performing the following operations: Perform an inverse discrete Fourier transform on each column vector of the target matrix, and perform a discrete Fourier transform on some row vectors in the inverse discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; or, Perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix to obtain the distance information and speed information of each target to be sensed within the sensing range; The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

12. A distance speed acquisition device, characterized in that: include: The first acquisition unit is used to perform a discrete Fourier inverse transform on each column vector of the target matrix, and to perform a discrete Fourier transform on some row vectors in the discrete Fourier inverse transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range; or, The second acquisition unit is used to perform discrete Fourier transform on each row vector of the target matrix, and perform inverse discrete Fourier transform on some column vectors in the discrete Fourier transform result matrix, so as to obtain the distance information and speed information of each target to be sensed within the sensing range; The target matrix is ​​determined based on the transmitter perception signal matrix and the receiver perception signal matrix, and is used to characterize the distance information and speed information of all the targets to be perceived within the perception range.

13. A non-transitory readable storage medium, characterized in that: The non-transitory readable storage medium stores a computer program, and the computer program is used to enable a computer to execute the distance speed acquisition method according to any one of claims 1 to 9.

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