Radar target detection and identification method, radar system, computer equipment and storage medium

Abstract

The invention relates to the technical field of wireless communication, and discloses a radar target detection and recognition method, a radar system, computer equipment and a storage medium, and the method comprises the steps: determining a first echo signal corresponding to a first transmission signal and a second echo signal corresponding to a second transmission signal; wherein the first echo signal has a first range profile relative to the scattering center, and the second echo signal has a second range profile relative to the scattering center; determining a splicing frequency band of the first echo signal and the second echo signal and an initial fusion range profile of the first range profile and the second range profile; constructing a signal fusion model based on the spliced frequency band and the initial fusion range profile; and carrying out iterative solution according to the signal fusion model to obtain a target fusion range profile so as to represent the relative position relationship between the radar and the scattering center. Therefore, on the basis of the signal fusion model, the frequency band width is expanded, so that the distance and azimuth resolution is improved, the target details are clearer, and the target detection accuracy is improved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a radar target detection and recognition method, a radar system, a computer device and a storage medium. Background Art

[0002] With the rapid growth of the wireless communication industry, spectrum resources are becoming increasingly tight, but the integrated radar communication system in related technologies still has limitations. A method is needed to improve the target detection and recognition accuracy of the radar communication system. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the present application proposes a radar target detection and recognition method, a radar system, a computer device and a storage medium. The main technical solutions adopted by the present application include:

[0004] In a first aspect, an embodiment of the present application provides a radar target detection and recognition method, the method comprising: determining a first echo signal corresponding to a first transmitted signal and a second echo signal corresponding to a second transmitted signal; wherein the first echo signal is used to represent the reflected part of the first transmitted signal by the scattering center; the second echo signal is used to represent the reflected part of the second transmitted signal by the scattering center, and the first echo signal has a first range image relative to the scattering center, and the second echo signal has a second range image relative to the scattering center; determining a spliced ​​frequency band of the first echo signal and the second echo signal, and an initial fused range image of the first range image and the second range image; constructing a signal fusion model based on the spliced ​​frequency band and the initial fused range image; wherein the signal fusion model is used to reflect the correspondence between the spliced ​​frequency band and the fused range image in a matrix form; performing iterative solution according to the signal fusion model to obtain a target fused range image to represent the relative position relationship between the radar and the scattering center.

[0005] In a second aspect, an embodiment of the present application provides a radar system, comprising: a signal transmitting module for transmitting radar signals of different frequency bands; a signal receiving module for receiving echo signals reflected by a scattering center; a signal processing module for executing any of the above-mentioned radar target detection and recognition methods; and a display module for displaying a target fused range image.

[0006] In a third aspect, an embodiment of the present application provides a radar target detection and identification device, which includes: a signal determination module, used to determine a first echo signal corresponding to a first transmitted signal and a second echo signal corresponding to a second transmitted signal; wherein the first echo signal is used to represent the reflected part of the first transmitted signal by the scattering center; the second echo signal is used to represent the reflected part of the second transmitted signal by the scattering center, and the first echo signal has a first range image relative to the scattering center, and the second echo signal has a second range image relative to the scattering center; a signal processing module, used to determine a spliced ​​frequency band of the first echo signal and the second echo signal, and an initial fused range image of the first range image and the second range image; a model construction module, used to construct a signal fusion model based on the spliced ​​frequency band and the initial fused range image; wherein the signal fusion model is used to reflect the correspondence between the spliced ​​frequency band and the fused range image in a matrix form; a result solving module, used to perform iterative solving according to the signal fusion model to obtain a target fused range image to represent the relative position relationship between the radar and the scattering center.

[0007] In a fourth aspect, the present application further provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the above methods when executing the computer program.

[0008] In a fifth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when the computer program is executed by a processor.

[0009] In a sixth aspect, the present invention provides a computer program product, comprising a computer program, which implements the steps of any of the above methods when executed by a processor.

[0010] In the above embodiment, based on the splicing frequency band and signal fusion model, the frequency band width is expanded, thereby improving the distance and azimuth resolution and making the target details clearer. In addition, the multiple frequency band signals after splicing and fusion are iteratively calculated, which effectively reduces the problem of missing and incomplete data and ensures the reliability of signal fusion. At the same time, the noise interference in the signal is effectively eliminated, and the target feature information is enhanced, so that the target fusion distance image obtained more accurately reflects the real relative position relationship between the radar and the scattering center, so as to improve the accuracy of target detection and more reliably identify the target. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1a A flowchart of a radar target detection and recognition method provided according to an embodiment of the present application;

[0013] Figure 1b A schematic diagram of the geometric shapes of a radar and a target provided according to an embodiment of the present application;

[0014] Figure 1c A time-frequency relationship diagram of different transmission signals provided according to an embodiment of the present application;

[0015] Figure 1d A time-frequency relationship diagram of different echo signals provided according to an embodiment of the present application;

[0016] Figure 1e A range image result diagram in a single frequency band operation mode provided according to an embodiment of the present application;

[0017] Figure 1f A range image result diagram in another single frequency band operation mode provided according to an embodiment of the present application;

[0018] Figure 1g A fused range image result diagram provided according to an embodiment of the present application;

[0019] Figure 1h A schematic diagram of the position of a moving target at an initial moment provided according to an embodiment of the present application;

[0020] Figure 1i A range image result diagram in a single frequency band operation mode provided according to yet another embodiment of the present application;

[0021] Figure 1j A range image result diagram in another single frequency band operation mode provided according to yet another embodiment of the present application;

[0022] Figure 1k A fused range image result diagram provided according to another embodiment of the present application;

[0023] Figure 2 A flowchart of a method for constructing a signal fusion model according to an embodiment of the present application;

[0024] Figure 3a A flowchart of a method for obtaining a target fused range image according to an embodiment of the present application;

[0025] Figure 3b A time-frequency relationship diagram of an objective function provided according to an embodiment of the present application;

[0026] Figure 3cA time-frequency relationship diagram of a spliced ​​frequency band provided according to an embodiment of the present application;

[0027] Figure 3d A time-frequency relationship diagram of a matrix operation provided according to an embodiment of the present application;

[0028] Figure 3e A time-frequency relationship diagram of a matrix operation provided according to an embodiment of the present application;

[0029] Figure 3f A time-frequency relationship diagram of a matrix operation provided according to an embodiment of the present application;

[0030] Figure 4 A flowchart of a method for obtaining a target fused range image according to another embodiment of the present application;

[0031] Figure 5a A flowchart of a method for determining an initial phase difference according to an embodiment of the present application;

[0032] Figure 5b A time-frequency relationship diagram of a processed signal provided according to an embodiment of the present application;

[0033] Figure 6a A flowchart of a method for determining a splicing frequency band according to an embodiment of the present application;

[0034] Figure 6b A time-frequency relationship diagram of a processed signal provided according to another embodiment of the present application;

[0035] Figure 7 A flowchart for determining an initial fused range image according to yet another embodiment of the present application;

[0036] Figure 8 is a structural block diagram of a radar target detection and recognition device according to an embodiment of the present application;

[0037] Fig. 9 The figure is a diagram of the internal structure of a computer device according to one embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present application.

[0039] With the rapid growth of the wireless communication industry, the spectrum has become increasingly crowded. As a result, the value of wireless communication bands has risen sharply in recent years. To this end, researchers are exploring the sharing of radar and communication bands to achieve integrated radar communication systems. Radar systems have made extensive contributions to various scientific applications, including remote sensing, hydrological monitoring, and security surveillance. In order to expand the application of communication systems, the fusion of radar sensing and wireless communication has become increasingly important for future missions. The 3GPP standard specifies ten FDD bands in the 1-3GHz range with bandwidths ranging from 40 to 200MHz. Due to these bandwidth limitations, using these communication bands for target detection results in insufficient resolution. However, communication base stations can usually carry multiple frequencies and exchange center frequencies and bandwidths. This capability provides the potential to fuse target detection signals on multiple communication bands.

[0040] In related technologies, multi-frequency fusion technology merges echoes from different frequency bands at the signal level, thereby generating a signal with a larger bandwidth and achieving higher resolution. Multi-band signal fusion has been widely studied in the field of radar. One method is to first establish a signal autoregressive model and then use a bandwidth extrapolation method to predict the frequency response outside the radar operating band, thereby increasing the effective bandwidth. Cabrera proposed an adaptive extrapolation harmonic decomposition method based on optimal basis selection. Sacchi introduced a nonparametric iterative method suitable for line spectrum estimation, which improves the extrapolation accuracy by minimizing the cost function based on Bayesian theory. Cetin proposed a norm regularization method to fill in missing data and perform imaging. Stoica proposed a missing data recovery method using an iterative adaptive algorithm (IAA), which works under uniform and non-uniform sampling conditions by using a weighted least squares method. Bai used the Gapped Data Amplitude and Phase Estimation (GAPES) algorithm to fill in the missing band data and then used the complete band data for scatterer estimation. Hu interpolated sparse band data based on an autoregressive (AR) model and then reconstructed the interpolated signal using the SL0 algorithm to obtain a high-resolution range profile (HRRP). Zhou applied the probability model to sparse frequency band signals and used the sparse Bayesian method for fusion imaging. However, the above methods have their limitations and cannot effectively compensate for the phase errors on multiple sub-bands. Using the above methods for target detection will result in insufficient resolution and low accuracy.

[0041] Based on this, according to an embodiment of the present application, a radar target detection and recognition method, a radar system, a computer device and a storage medium method embodiment are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0042] In this embodiment, a radar target detection and recognition method is provided. Figure 1a : is a flow chart of a radar target detection and recognition method according to an embodiment of the present application, the process includes the following steps:

[0043] S110. Determine a first echo signal corresponding to the first transmit signal and a second echo signal corresponding to the second transmit signal.

[0044] Among them, the first transmission signal and the second transmission signal may refer to multiple groups of electromagnetic wave signals transmitted by the radar system at a specific time or frequency band. Exemplarily, the signal transmitted in the first frequency band working mode may be referred to as the first transmission signal, and the signal transmitted in the second frequency band working mode may be referred to as the second transmission signal. The signal received by the radar system after the transmission signal is reflected by the target can be referred to as the first echo signal and the second echo signal under the two frequency band working modes. Specifically, the first echo signal is used to represent the reflected part of the first transmission signal by the scattering center, and the second echo signal is used to represent the reflected part of the second transmission signal by the scattering center. Among them, the scattering center can also be referred to as a target, which refers to a point or area that can reflect the radar signal. The reflection characteristics of the scattering center determine the representation of the target in the radar image, so that the target can be identified and classified. It should be understood that the radar image may refer to a distance image that reflects the distance distribution of the target under the condition of the transmission signal, that is, the distance information of each scattering center on the target to the radar, also known as the distance image. Specifically, the first echo signal has a first range image relative to the scattering center, and the second echo signal has a second range image relative to the scattering center. These range images show the distance information from each scattering center to the radar under different transmission signal conditions.

[0045] For example, the geometry of the radar and the target can be referred to Figure 1b As shown in the figure, s 1 (t) as the first transmission signal, s 2 (t) is the second transmission signal. The three blue target positions on the right are different scattering center points. If the radar uses a linear frequency modulation signal, then in one repetition period, the radar transmission signals of the two frequency band working modes, i.e., the first transmission signal s 1 (t) and the second transmission signal s 2 (t) can be expressed in the following form:

[0046]

[0047] In the formula, B 1 is the working bandwidth of the first transmission signal; B 2 is the working bandwidth of the second transmission signal; f c1 is the carrier frequency of the first transmission signal; fc2 k is the carrier frequency of the second transmission signal; 1 k is the modulation frequency of the first transmitting signal; 2 is the modulation frequency of the second transmission signal; T 1 is the pulse width of the first transmitting signal; T 2 is the pulse width of the second transmission signal; t is a time variable, indicating the change of the signal over time.

[0048] in, Representing the time domain pulse shape of the signal, there is u is a normalized time variable. For example, the time-frequency relationship of different transmission signals can be referred to Figure 1c , the horizontal axis in the figure represents time, the vertical axis represents frequency, the intercept represents the center frequency, and the slope represents the modulation frequency.

[0049] Furthermore, the first echo signal and the second echo signal can be expressed as follows:

[0050]

[0051] In the formula, A i is the amplitude of the target scattering response, that is, the amplitude of the i-th scattering center, indicating the intensity of the reflected signal of the scattering center; p is the number of scattering centers; τ 1i is the time delay from the ith scattering center to the radar in the first frequency band operating mode; τ 2i is the time delay from the i-th scattering center to the radar in the first frequency band working mode; t is the time variable, which indicates the change of the signal in time. It should be noted that τ 1i and τ 2i Varies due to different operating modes and system errors.

[0052] For example, the time-frequency relationship of different echo signals can be referred to Figure 1d , taking three scattering centers as an example, the yellow signal in the figure is the first echo signal, τ 11 Represents the time delay of the first echo signal returning to the radar from the first scattering center; τ 12 Represents the time delay of the first echo signal returning to the radar from the second scattering center; τ 13 Represents the time delay of the first echo signal from the third scattering center back to the radar. The green signal is the second echo signal, τ 21 represents the time delay of the second echo signal returning to the radar from the first scattering center; τ 22 represents the time delay of the second echo signal returning to the radar from the second scattering center; τ 23 Represents the time delay of the second echo signal returning to the radar from the third scattering center.

[0053] S120: Determine a splicing frequency band of the first echo signal and the second echo signal, and an initial fused range image of the first range image and the second range image.

[0054] Among them, the splicing frequency band can refer to the splicing result obtained by merging or connecting the frequency ranges of multiple signals, which can present a wider frequency bandwidth. Specifically, to obtain the splicing frequency band result, the first echo signal and the second echo signal can be firstly subjected to spectrum analysis to find the overlapping part of the frequency ranges of the two echo signals. Then, the range of the splicing frequency band can be expanded as needed, and multi-band fusion expansion can be performed on the basis of the overlapping frequency range. The extended range should cover the main frequency components of the two echo signals to make full use of the information of the signal, thereby ensuring that the spliced ​​frequency band can effectively cover the reflection characteristics of the target and improve the accuracy of target detection. Based on this, the initial fusion range image can refer to the range image formed by the preliminary fusion of the first range image and the second range image on the basis of the splicing frequency band, which reflects the distance distribution of the target under the splicing frequency band condition. Specifically, the determination of the initial fusion range image needs to consider the characteristics of the two range images and the characteristics of the splicing frequency band, and combine the information of the two range images through a certain fusion algorithm to form a preliminary fusion result.

[0055] S130: construct a signal fusion model based on the spliced ​​frequency bands and the initial fusion range image.

[0056] Among them, the signal fusion model is used to reflect the corresponding relationship between the spliced ​​frequency band and the fused distance image in the form of a matrix. Specifically, the signal fusion model can use matrix operations to correspond the frequency components in the spliced ​​frequency band to the distance information in the fused distance image, so as to integrate the signal information of different frequency bands, thereby improving the signal resolution and the accuracy of target detection. Further, the signal fusion model is constructed to establish a matrix representation, define the matrix dimension, fill the matrix elements and perform normalization. Exemplarily, after determining the spliced ​​frequency band and the initial fused distance image, a matrix representation can be established first, and the frequency components in the spliced ​​frequency band are used as the rows of the matrix by defining the matrix dimension, and the distance points in the initial fused distance image are used as the columns of the matrix, so as to construct a matrix reflecting the corresponding relationship between the spliced ​​frequency band and the fused distance image. Then, according to the specific data of the spliced ​​frequency band and the initial fused distance image, each element in the matrix is ​​filled, and these elements represent the relationship strength between the specific frequency component and the specific distance point. Further, in order to ensure that the numerical range of the matrix elements is reasonable, the matrix can also be normalized so that the values ​​of the matrix elements are in the range of [0,1]. Finally, a complete signal fusion model is constructed to provide a basis for subsequent iterative solutions and target detection.

[0057] S140. Perform an iterative solution according to the signal fusion model to obtain a target fusion range image to represent the relative position relationship between the radar and the scattering center.

[0058] Specifically, based on the information of the spliced ​​frequency band and the initial fused range image contained in the signal fusion model, the solution calculation is performed to update the model parameters. The updated parameter information is used as the basis for the next round of solution. Repeat the above steps, calculate and optimize through feedback and multiple iterations, gradually adjust the reconstruction results of the signal, improve the quality of the signal and finally obtain a high-resolution range image result, that is, obtain the target fused range image to accurately represent the relative position relationship between the radar and the scattering center.

[0059] For example, after the signal fusion model is obtained, a simulation experiment can be performed to verify the performance of the signal fusion model. Specifically, the parameters used for simulation data can be as shown in Table 1.

[0060] Table 1 Parameters of simulation data

[0061]

[0062] Similarly, taking three scattering centers as an example, three point targets located at 360.004 km, 360.011 km and 360.050 km are used as simulated scattering centers. It should be understood that before obtaining the spliced ​​frequency band, the received signal can be processed using dechirp. Among them, the reference time delay is a preset parameter introduced in the Dechirp processing echo. Taking the situation in the first transmission signal operation mode as an example, the reference time delay can be obtained by the following formula:

[0063] τ 1s =2×R ref / c

[0064] In the formula, τ 1s represents the reference time delay in the first frequency band working mode; R ref represents the Dechirp reference distance; c is the speed of light.

[0065] Furthermore, after simulation, the simulation results of stationary targets can be referred to Figure 1e , Figure 1f and Figure 1g As shown, the red line indicates the actual position of the target. Figure 1e represents the result in Band 1 operation mode (Signal 1), Figure 1f The results for Band 2 operation mode (signal 2) are shown in Figure 2. The performance and fusion distance of the two bands are as follows: Figure 1g As shown. Figure 1e and Figure 1fIt can be seen that the signals from the two frequency bands exhibit higher side lobes and wider main lobes, while the results obtained after solving with the signal fusion model exhibit narrower main lobes and lower side lobes, thereby improving the positioning accuracy. This enables two targets that cannot be distinguished within a single frequency band to become distinguishable in the fused frequency band signal.

[0066] Furthermore, simulation of moving targets can also be carried out. Exemplarily, taking three scattering centers as an example again, these moving targets rotate simultaneously at an angular velocity of 0.15 degrees per second, and their positions at the initial moment can be as Figure 1h shown. The 512 pulses obtained in the first frequency band operation mode (signal 1) can be as Figure 1i shown, and the 512 pulses obtained in the second frequency band operation mode (signal 1) can be as Figure 1j shown. It can be seen from Figure 1i and Figure 1j that the detection results of two of the targets will gradually approach and become indistinguishable. However, the high-resolution target fusion range image obtained by solving with the signal simulation model makes the target signal clearer and the details richer, which means that within the same distance range, the structure and characteristics of the target can be seen more clearly. The result of the target fusion range image can be as Figure 1k shown. It can be seen from the figure that the two target signals that gradually approached under single frequency band operation have separated, forming two independent two lines, that is, the target signals have been effectively separated and can thus be clearly distinguished.

[0067] In the above embodiment, based on the spliced frequency band and the signal fusion model, the frequency band width is expanded, thereby improving the range and azimuth resolution and making the target details clearer. And iterative calculation is performed on the multiple frequency band signals after splicing and fusion, effectively reducing the problems of data loss and incompleteness, and ensuring the reliability of signal fusion.

[0068] In some embodiments, before constructing the signal fusion model based on the spliced frequency band and the initial fusion range image, please refer to Appendix Figure 2 , and the method further includes:

[0069] S210. Determine the initial phase difference between the first echo signal and the second echo signal.

[0070] Specifically, the initial phase difference between the first echo signal and the second echo signal can be determined by subtracting the first echo signal from the second echo signal. Exemplarily, the first echo signal and the second echo signal in the two-band working mode can be preprocessed to remove noise and normalize, and then their phase spectra are extracted by Fourier transform, and then the phase spectra are aligned and subtracted point by point to obtain the initial phase difference. Optionally, the initial phase difference can also be corrected according to system errors or environmental factors, and finally its accuracy is verified by error analysis or phase consistency test.

[0071] S220: Accordingly, a signal fusion model is constructed based on the spliced ​​frequency band and the initial fusion range image, including:

[0072] S222. Construct a signal fusion model according to the spliced ​​frequency band, the initial fusion range image and the initial phase difference.

[0073] Specifically, based on the spliced ​​frequency band and the initial fused range image, the matrix dimension can be defined, the frequency components of the spliced ​​frequency band are set as matrix rows, and the distance points of the initial fused range image are set as matrix columns, so as to construct a matrix reflecting the corresponding relationship between the two; then, combined with the initial phase difference information, the elements in the matrix are compensated, adjusted and optimized to accurately represent the relationship between different frequency components and distance points.

[0074] Exemplarily, the spliced ​​frequency band may be expressed as follows:

[0075]

[0076] Where S 1 represents the matrix form in the first frequency band working mode; S 2 represents the matrix form in the first frequency band working mode; N is the number of signal sampling points.

[0077] Furthermore, the signal fusion model constructed according to the spliced ​​frequency band, the initial fusion range image and the initial phase difference can be shown as follows:

[0078] S=EDFX

[0079] Where S represents the splicing frequency band; X represents the initial fusion range image; F represents the Fourier transform matrix; D represents the range from the entire frequency band to S in the entire frequency band 1 and S 2 The sampling matrix of the frequency band can be expressed as I N represents the NxN identity matrix; E represents the phase compensation matrix constructed based on the initial phase difference; N is the number of signal sampling points.

[0080] It should be understood that after obtaining the initial phase difference, a phase error compensation matrix E of the overall offset of the time-frequency trajectory of the two signals can also be established based on one of the signals as a reference signal to compensate for the phase error. Taking the first frequency band working mode (signal 1) as a reference signal as an example, the phase error compensation matrix E can be shown as follows:

[0081]

[0082] In the formula, I N represents the NxN identity matrix; N is the number of signal sampling points; E 12 The phase error matrix of the second frequency band working mode (signal 2) based on signal 1 is: in, represents the initial phase difference.

[0083] In the above-mentioned embodiment, by determining the initial phase difference between the first echo signal and the second echo signal, and constructing a signal fusion model based on the spliced ​​frequency band, the initial fused range image and the initial phase difference, it is possible to effectively integrate the signal information of different frequency bands and compensate for the phase error, thereby improving the signal resolution and the accuracy of target detection, and ultimately obtaining a high-resolution target fused range image that accurately represents the relative position relationship between the radar and the scattering center.

[0084] In some implementations, the signal fusion model is iteratively solved to obtain the target fusion range image. Figure 3a ,include:

[0085] S310, solving the signal fusion model, and updating the initial fusion range image and the initial phase difference according to the solution results to obtain an updated range image and an updated phase difference.

[0086] It should be understood that before solving the signal fusion model, considering the sparsity of the target, the signal fusion model can be improved again by adding multiple constraints to it to form a minimization function form of the optimization problem. The result can be shown as follows:

[0087]

[0088] In the formula, λ 1 is the regularization parameter, which represents the coefficient of the sparsity of the reconstructed target; 2 is also a regularization parameter, which indicates the degree of phase error compensation constraint; S represents the splicing band; X represents the initial fusion range image; F represents the Fourier transform matrix; S 1 The matrix form representing the first frequency band working mode (signal 1); S 2The matrix form represents the second frequency band working mode (signal 2); D represents the whole frequency band from the whole frequency band to S 1 and S 2 The sampling matrix of the frequency band; E represents the phase compensation matrix constructed based on the initial phase difference; E 12 Represents the phase error matrix of signal 2 based on signal 1.

[0089] It can be seen from the formula that the objective function can be divided into two parts, where λ 1 ||X|| 1 is the constraint condition introduced on the sparsity of the reconstruction target, ||X|| 1 Indicates the sparsity of the distance distribution. The constraint condition of the phase error compensation constraint degree introduced into the objective function is also in the form of a regularization term. Specifically, its meaning can be expressed as Figure 3b As shown, it represents the overall offset between the time-frequency traces of the two sub-bands estimated according to the least squares criterion. It is a criterion for estimating the range image of the complete frequency band based on the spliced ​​sub-band signal, and can minimize the difference between the spliced ​​sub-band signal and the estimated complete frequency band signal.

[0090] It is important to understand that according to The minimum criterion for finding the distance image X and the phase difference E can be equivalent to the basis The distance image X and the phase difference E are obtained because the distance image X and the phase difference E are selected so that After the minimum, is also the smallest. In the formula, S represents the splicing frequency band; E H represents the matrix used to align the time-frequency traces of two signals, D H Indicates that the two sub-band signals are extended to their actual frequency positions. The complete band signal FX is estimated based on the least squares criterion. For details, please refer to Figure 3c , Figure 3d , Figure 3e and Figure 3f In the figure, the yellow line represents the signal of the first frequency band working mode (signal 1), and the green line represents the signal of the second frequency band working mode (signal 2). Figure 3c represents the time-frequency relationship of S, Figure 3d Represents E H The time-frequency relationship of S, Figure 3e Representative D H E H The time-frequency relationship of S, Figure 3f Representative D H E H The time-frequency relationship between S and FX. The figure also verifies that Calculate the feasibility of the distance image X and the phase difference E.

[0091] Furthermore, the improved signal fusion model is iteratively solved, which can be further decomposed into two sub-problems: range image estimation and phase error estimation. The process can be expressed as:

[0092]

[0093] Where, X t+1 Represents the updated range image; E t+1 represents the updated phase error compensation matrix determined based on the updated phase difference; t is the number of iterations.

[0094] Among them, the solution for the range image estimation can be achieved through the following iterative method:

[0095] R t =X t +μ(E t DF) H (SE t DFX t )

[0096]

[0097] In the formula, R t For the convenience of calculation, λ 1 μ is the regularization threshold parameter.

[0098] To solve the phase error estimation, we can first update the phase error compensation matrix E t+1 The expression can be rewritten as follows:

[0099]

[0100] In the formula, S i represents the i-th row of the concatenated frequency band matrix; S 1i The i-th row of the signal 1 matrix representing the first frequency band operating mode; S 2i The i-th row of the signal 2 matrix representing the second frequency band operating mode.

[0101] Solving the above equation for the minimum value is equivalent to solving the minimum value of each term in the sum equation. First, for each individual term on the right side, the following equation can be obtained:

[0102]

[0103] Among them, the updated phase difference The resulting value is:

[0104]

[0105] Finally, in the solution process, the initial fused range image and the initial phase difference are updated according to the solution results to obtain the updated range image and the updated phase difference.

[0106] S320: Update the parameters of the signal fusion model using the updated range image and the updated phase difference to obtain a model after parameter update.

[0107] Among them, the updated range image may refer to a new range image obtained according to the updated model parameters during the iterative solution of the signal fusion model. The updated phase difference may refer to a new phase difference obtained according to the updated model parameters during the iterative solution of the signal fusion model. Different from the initial fusion range image and the initial phase difference, the updated range image and the updated phase difference are obtained after continuously optimizing the model parameters during the iterative solution. Specifically, after determining the updated range image and the updated phase difference, the updated range image can replace the initial fusion range image, and the updated phase difference can replace the initial phase difference, so as to update the relevant parameters in the model and obtain the parameter updated model. Because the parameter updated model has undergone iterative calculations and parameter updates, it can more accurately reflect the relative position relationship between the radar and the scattering center, and provide a more accurate basis for the next iterative solution.

[0108] S330: Use the model after parameter update as the signal fusion model, and repeat the above steps of solving the signal fusion model until the target fusion range image is obtained.

[0109] Specifically, after obtaining the model after parameter update, the updated range image and the updated phase difference are used as the calculation starting point to solve again, obtain the new range image and phase difference, and update the parameters of the signal fusion model again, and solve again. By repeating this process, iterative solving and repeated parameter updates are performed until the preset end condition is met, and the range image obtained by the last solution can be used as the target fusion range image.

[0110] The preset end condition refers to a condition pre-set in the iterative solution process for determining whether to stop the iteration, which can be determined based on the accuracy requirements of the solution results, the limitation of computing resources, or specific algorithm performance indicators. Exemplarily, the preset end condition can be the maximum number of iterations. When the number of iterations reaches this value, the iteration process will stop regardless of whether the result meets the accuracy requirements. The preset end condition can also be a convergence threshold. When the change in the results of two consecutive iterations is less than the convergence threshold, it is considered that the iteration has converged and the iteration can be stopped.

[0111] In the above implementation, by constructing a signal fusion model and performing iterative solving, the initial fused range image and initial phase difference are continuously updated to obtain an updated range image and phase difference, and then the model parameters are updated. This process is repeated until the preset end conditions are met, and finally a target fused range image that accurately represents the relative position relationship between the radar and the scattering center is obtained, which effectively improves the signal resolution and target detection accuracy. At the same time, by introducing the reconstructed target sparsity and phase error compensation constraints, the solution of the model is further optimized, thereby enhancing the target recognition and classification capabilities.

[0112] In some implementations, the signal fusion model is iteratively solved to obtain the target fusion range image. Figure 4 ,include:

[0113] S410: Perform one of range image solution and phase difference solution based on the signal fusion model, and update one of the initial fused range image and the initial phase difference accordingly, and obtain a first intermediate model accordingly.

[0114] S420, performing another operation of solving the range image and the phase difference based on the first intermediate model, and correspondingly updating the other of the initial fused range image and the initial phase difference, and correspondingly obtaining the second intermediate model.

[0115] S430: Use the second intermediate model as a signal fusion model and repeat the above steps of alternately solving the signal fusion model until a target fusion range image is obtained.

[0116] Among them, the first intermediate model may refer to an operation of first performing a range image solution or a phase difference solution based on the signal fusion model in the iterative solution process of the signal fusion model, and correspondingly updating one of the initial fused range image or the initial phase difference, and the intermediate model obtained reflects the result of partially updating the initial fused range image or the initial phase difference in the iterative solution process. Specifically, performing an operation of performing a range image solution or a phase difference solution based on the signal fusion model may refer to calculating an updated value of the initial fused range image according to the signal fusion model to minimize the difference between the spliced ​​frequency band and the estimated complete frequency band signal; or calculating an updated value of the initial phase difference according to the signal fusion model to minimize the overall offset between the time-frequency tracks of the two sub-band signals. Accordingly, updating one of the initial fused range image or the initial phase difference may refer to replacing the initial fused range image with the calculated range image update value to obtain an updated range image or replacing the initial phase difference with the calculated phase difference update value to obtain an updated phase difference. Finally, the updated range image or the updated phase difference is substituted into the signal fusion model to obtain the first intermediate model.

[0117] The second intermediate model may refer to a model obtained by performing another operation of range image solution or phase difference solution based on the first intermediate model after obtaining the first intermediate model, and updating the other of the initial fused range image or initial phase difference accordingly. This model is the signal fusion model after an alternating iterative parameter update. Finally, the above-mentioned alternating solution steps of the signal fusion model are repeated, that is, the second intermediate model is used as the new signal fusion model, and the alternating operations of range image solution and phase difference solution are performed again until the preset end condition is met to obtain the target fused range image.

[0118] For example, taking updating the range image first and then updating the phase difference, and taking the maximum number of iterations as 30 as the preset end condition, the alternating solution algorithm for the signal fusion model can be shown in Table 2 below:

[0119] Table 2 Alternating solution algorithm

[0120]

[0121]

[0122] Among them, S 1 The matrix form representing the first frequency band working mode (signal 1); S 2 The matrix form represents the second frequency band working mode (signal 2); D represents the whole frequency band from the whole frequency band to S 1 and S 2 The sampling matrix of the frequency band; T represents the maximum number of iterations; λ 1 is the regularization parameter, which represents the coefficient of the sparsity of the reconstructed target; 2 It is also a regularization parameter, which indicates the degree of phase error compensation constraint; X t Represents the updated range image; E t represents an updated phase error compensation matrix determined based on the updated phase difference.

[0123] In the above-mentioned embodiment, based on the alternating iterative solution of the signal fusion model, firstly one of the initial fusion range image or the initial phase difference is updated to obtain the first intermediate model, and then the other is updated to obtain the second intermediate model. Then, the second intermediate model is used as the new signal fusion model to repeat the above-mentioned alternating solution steps until the preset end condition is met, and finally a target fusion range image that accurately represents the relative position relationship between the radar and the scattering center is obtained, thereby effectively improving the signal resolution and target detection accuracy.

[0124] In some embodiments, the initial phase difference between the first echo signal and the second echo signal is determined. Figure 5a ,include:

[0125] S510 , performing a differential operation on the first echo signal and the second echo signal to obtain a phase difference signal.

[0126] Specifically, the phases of the two signals can be extracted first. For example, the phase information can be extracted from the time domain signal by Fourier transform or other phase analysis methods. Then, a signal is selected as a reference signal, and the phase of the signal is used as the reference phase. The phases of the two signals are subtracted point by point to obtain the phase difference. For example, the phase of the first echo signal is used as the reference phase, and the phase difference signal can be obtained by subtracting the phase of the first echo signal from the phase of the second echo signal. The phase difference signal between the two signals after Dechirp processing can be shown as follows:

[0127]

[0128] In the formula, is the phase difference signal; Δτ 1i is the relative delay of different scattering centers under the first echo signal; Δτ 2i is the relative delay of different scattering centers under the second echo signal.

[0129] S520 , performing coupling analysis on the phase difference signal to obtain an initial phase difference including a residual misalignment phase error term and a linear phase error term.

[0130] Among them, the residual misaligned phase error term refers to the error term related to the scattering center position. The linear phase error term refers to the error caused by the overall misalignment of the time-frequency trajectory between the two signals due to the overall translation of the signal time-frequency trajectory. For example, please refer to Figure 5b , the vertical axis represents the time delay of each scattering center in the two frequency band signals, and the horizontal axis represents the bandwidth and frequency band position occupied by the two frequency band signals. The yellow signal is the first echo signal, and the green signal is the second echo signal. Each horizontal line in the figure represents the relative delay of a scattering center under a frequency signal operation, such as Δτ 11 is the relative delay of the first scattering center under the first echo signal. Similarly, taking the phase of the first echo signal as the reference phase as an example, the residual misalignment phase error term can be represented in the figure as the residual misalignment of the two signal time-frequency trajectories on the time-frequency trajectory of the second echo signal due to the different translations of each scattering center. The linear phase error term can be represented in the figure as the overall translation of the time-frequency trajectory of the second echo signal relative to the time-frequency trajectory of the first echo signal, resulting in the overall misalignment of the time-frequency trajectories of the two signals.

[0131] Specifically, since different scattering centers correspond to different phase differences, the phase difference signal cannot accurately compensate the entire echo signal. Therefore, after obtaining the phase difference signal, the phase difference signal can be further coupled with the parameters of the scattering center. At this time, the phase difference signal is sorted, and the initial phase difference obtained by sorting can be written as follows:

[0132]

[0133] In the formula, represents the initial phase difference; ε i represents the residual misalignment phase error, ε i =τ 2i -τ 1i ; α represents the linear phase error, α=τ 2s -τ 1s , where τ 1s represents the reference time delay in the first frequency band working mode; τ 2s Represents the reference time delay in the second frequency band working mode.

[0134] It should be noted that in actual radar observations, the reference time delay τ 1s and τ 2s , may not be equal in the two band operation modes.

[0135] In the above embodiment, a phase difference signal is obtained by performing a differential operation on the first echo signal and the second echo signal, and then a coupling analysis is performed on the phase difference signal to decompose it into a residual misalignment phase error term related to the scattering center position and a linear phase error term caused by the overall translation of the signal time-frequency trajectory, thereby obtaining the initial phase difference, which provides more accurate phase information for subsequent signal fusion and target detection, and effectively improves the measurement accuracy and target recognition capability of the radar system.

[0136] In some embodiments, the splicing frequency band of the first echo signal and the second echo signal is determined. Figure 6a ,include:

[0137] S610: Perform de-linear frequency modulation processing on the first echo signal and the second echo signal to obtain a first intermediate echo signal and a second intermediate echo signal.

[0138] Among them, the first intermediate echo signal and the second intermediate echo signal may refer to the intermediate results obtained by performing de-linear frequency modulation processing on the original echo signal during the radar signal processing. It can be understood that the signal transmitted by the radar system is usually a linear frequency modulation signal, and its frequency changes linearly with time. De-linear frequency modulation processing refers to mixing the received echo signal with the transmitted signal, and then filtering out the high-frequency component through a low-pass filter to obtain an intermediate frequency signal to eliminate the linear frequency modulation component in the signal and retain the phase and amplitude information of the signal. Make the signal easier to process and analyze later.

[0139] Exemplarily, the first echo signal and the second echo signal may be processed using a Dechirp method to obtain a signal in the following form:

[0140]

[0141] In the formula, s 1 (t) is the first intermediate echo signal; s 2 (t) is the second intermediate echo signal; Δτ 1i is the relative time delay of different scattering centers in the first frequency band working mode, and Δτ 1i =τ 1i -τ 1s ; Δτ 2i is the relative time delay of different scattering centers in the second frequency band working mode, and Δτ 2i =τ 2i -τ 2s ; τ 1i is the time delay from the i-th scattering center to the radar in the first frequency band operating mode; τ 2i is the time delay from the ith scattering center to the radar in the second frequency band operating mode; τ 1s represents the reference time delay in the first frequency band working mode; τ 2s Represents the reference time delay in the second frequency band working mode.

[0142] It can be understood that the reference time delay τ 1s and τ 2s It is possible to introduce a preset parameter in the Dechirp echo processing.

[0143] Furthermore, the time-frequency relationship of the signal obtained after Dechirp processing can be shown as Figure 6b As shown in the figure, the vertical axis represents the delay of each scattering center in the two frequency band signals, and the horizontal axis represents the bandwidth and frequency band position occupied by the two frequency band signals. The yellow signal is the middle echo signal, and the green signal is the second middle echo signal. Each horizontal line in the figure represents the frequency offset of a scattering center under a frequency signal operation. For example, k 1Δτ 11 represents the frequency offset of the first scattering center in the first frequency band operating mode, where k 1 is the frequency modulation slope of the first echo signal, and Δτ 11 is the relative delay of the first scattering center in the second frequency band operating mode.

[0144] S620. Perform time-frequency conversion and simplification processing on the first intermediate echo signal and the second intermediate echo signal to obtain a first frequency-domain echo signal and a second frequency-domain echo signal.

[0145] Exemplarily, it can be set to perform time-frequency conversion on the first intermediate echo signal and the second intermediate echo signal to obtain a signal in the following form:

[0146]

[0147] In the formula, represents the first intermediate echo signal in the form of a frequency-domain variable in the first frequency band operating mode; represents the second intermediate echo signal in the form of a frequency-domain variable in the second frequency band operating mode; is the residual time-frequency phase in the first frequency band operating mode; is the residual time-frequency phase in the second frequency band operating mode; represents the frequency-domain variable transformed from the time-domain variable t.

[0148] It can be understood that due to the residual time-frequency phases and being relatively and being very small; and k 1 Δτ 1i and k 2 Δτ 2i being relatively small with respect to f c1 and f c2 as well, these phase terms can be ignored to perform simplification processing on the above signal form, and the simplified result, that is, the first frequency-domain echo signal and the second frequency-domain echo signal, can be shown as follows:

[0149]

[0150] In the formula, is the first frequency-domain echo signal in the first frequency band operating mode; is the second frequency-domain echo signal in the second frequency band operating mode; Δτ 1i is the relative time delay of different scattering centers in the first frequency band operating mode; Δτ 2i is the relative time delay of different scattering centers in the second frequency band operating mode; Represents the frequency domain variable after substitution from the time domain variable t.

[0151] Furthermore, the time-frequency relationship between the first frequency domain echo signal and the second frequency domain echo signal after the variable replacement can continue to refer to Figure 5b As shown, the vertical axis represents the time delay of each scattering center in the two frequency band signals, and the horizontal axis represents the bandwidth and frequency band position occupied by the two frequency band signals. Each horizontal line in the figure represents the relative delay of a scattering center in a frequency band working mode.

[0152] S630 , performing sampling fusion processing based on the first frequency domain echo signal and the second frequency domain echo signal to obtain a spliced ​​frequency band.

[0153] Exemplarily, the first frequency domain echo signal is still used as the reference signal, and the initial phase difference is substituted into the second frequency domain echo signal, which can be expressed as follows:

[0154]

[0155] In the formula, is a second frequency domain echo signal in a second frequency band working mode; represents the initial phase difference; Δτ 1i is the relative delay of different scattering centers in the first frequency band working mode.

[0156] Furthermore, the first frequency domain echo signal and the second frequency domain echo signal are sampled to represent the echo signals in matrix form and multiplied by the phase error matrix, and finally the matrix expression shown in the following formula can be obtained:

[0157] S 2 =E 12 S 1

[0158] In the formula, S 1 The matrix form of the first frequency domain echo signal (signal 1) in the first frequency band working mode; S 2 The matrix form of the second frequency domain echo signal (signal 2) in the second frequency band working mode; E 12 Represents the phase error matrix of signal 2 based on signal 1.

[0159] Finally, the obtained sampled frequency components are spliced ​​to form a continuous spectrum, that is, the spectra of the two signals are superimposed or spliced ​​in the frequency domain and fused to form a wider frequency band signal, ensuring that the fused signal can accurately reflect the frequency characteristics of the target.

[0160] Exemplarily, the spliced ​​frequency band may be expressed as follows:

[0161]

[0162] Where S 1 represents the matrix form of the first frequency band working mode (signal 1); S 2 Represents the matrix form of the second frequency band working mode (signal 2); N is the number of signal sampling points.

[0163] In the above-mentioned embodiment, the first echo signal and the second echo signal are de-linearized to obtain the first intermediate echo signal and the second intermediate echo signal, and then the two intermediate signals are time-frequency converted and simplified to obtain the first frequency domain echo signal and the second frequency domain echo signal. Finally, sampling and fusion processing are performed based on the two frequency domain signals, and their spectra are superimposed or spliced ​​in the frequency domain and fused to form a wider frequency band signal, i.e., a spliced ​​frequency band, thereby effectively integrating signal information of different frequency bands and improving the measurement accuracy and target recognition capability of the radar system.

[0164] In some embodiments, the initial fused range image of the first range image and the second range image is obtained by the following method: Figure 7 ,include:

[0165] S710 , perform de-linear frequency modulation processing on the first echo signal and the second echo signal to obtain a first intermediate echo signal and a second intermediate echo signal.

[0166] S720: Perform time-frequency conversion and simplification processing on the first intermediate echo signal and the second intermediate echo signal to obtain a first frequency domain echo signal and a second frequency domain echo signal.

[0167] It should be noted that, for the specific limitations of S710 and S720, reference may be made to the limitations of other embodiments above, which will not be repeated here.

[0168] S730 . Apply inverse Fourier transform to the first frequency domain echo signal to obtain a first range image, and apply inverse Fourier transform to the second frequency domain echo signal to obtain a second range image.

[0169] The first range image and the second range image may both refer to a bar graph or waveform graph result reflecting the reflection characteristics of the target in the distance direction, which is essentially one-dimensional signal data. Specifically, the first range image and the second range image may be obtained by multiplying the first frequency domain echo signal and the second frequency domain echo signal by the inverse of the Fourier transform matrix. As shown in the following formula:

[0170] X 1 =F -1 S 1

[0171] X 2 =F -1S 2

[0172] Where F represents the Fourier transform matrix; S 1 represents the matrix form of the first frequency band working mode (signal 1); S 2 represents the matrix form of the second frequency band working mode (signal 2); X 1 represents the first range image in matrix form; X 2 Represents the second range image in matrix form.

[0173] S740: Perform sampling and fusion processing on the first range image and the second range image to obtain an initial fused range image.

[0174] Similarly, similar to the method of obtaining the spliced ​​frequency band, the first range image and the second range image can be aligned to ensure the consistency of the two range images on the range axis. Based on the alignment, the two range images are fused using a certain fusion algorithm to generate an initial fused range image that reflects the range distribution of the target under the spliced ​​frequency band condition.

[0175] In the above-mentioned embodiment, the first echo signal and the second echo signal are de-linearized to obtain the first intermediate echo signal and the second intermediate echo signal, and then the two intermediate signals are time-frequency converted and simplified to obtain the first frequency domain echo signal and the second frequency domain echo signal, and then the two frequency domain signals are respectively subjected to inverse Fourier transform to obtain the first range image and the second range image, and finally the first range image and the second range image are sampled and fused, and the two range images are aligned and fused to generate an initial fused range image reflecting the distance distribution of the target under the splicing frequency band condition, which provides a basis for subsequent signal fusion and target detection.

[0176] It should be understood that, although the various steps in the above flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above flowchart may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0177] The embodiment of this specification also provides a radar system, which includes: a signal transmitting module for transmitting radar signals of different frequency bands; a signal receiving module for receiving echo signals reflected by the scattering center; a signal processing module for the content of the above-mentioned radar target detection and identification method; and a display module for displaying the target fusion range image. The specific definition of a radar system can be found in the definition of a radar target detection and identification method above, which will not be repeated here.

[0178] The present specification also provides a radar target detection and recognition device 800, such as Figure 8 As shown, it includes: a signal determination module 810, a signal processing module 820, a model building module 830 and a result solving module 840:

[0179] The signal determination module 810 is used to determine a first echo signal corresponding to a first transmitted signal and a second echo signal corresponding to a second transmitted signal; wherein the first echo signal is used to represent the reflected portion of the first transmitted signal by the scattering center; the second echo signal is used to represent the reflected portion of the second transmitted signal by the scattering center, and the first echo signal has a first range image relative to the scattering center, and the second echo signal has a second range image relative to the scattering center.

[0180] The signal processing module 820 is used to determine a splicing frequency band of the first echo signal and the second echo signal, and an initial fused range image of the first range image and the second range image.

[0181] The model building module 830 is used to build a signal fusion model based on the spliced ​​frequency bands and the initial fused range image; wherein the signal fusion model is used to reflect the corresponding relationship between the spliced ​​frequency bands and the fused range image in a matrix form.

[0182] The result solving module 840 is used to perform iterative solving according to the signal fusion model to obtain the target fusion range image to represent the relative position relationship between the radar and the scattering center.

[0183] In some embodiments, the model building module 830 is further used to determine the initial phase difference between the first echo signal and the second echo signal before building the signal fusion model based on the stitching frequency band and the initial fusion range image; accordingly, building the signal fusion model based on the stitching frequency band and the initial fusion range image includes: building the signal fusion model according to the stitching frequency band, the initial fusion range image and the initial phase difference.

[0184] In some embodiments, the result solving module 840 is also used to perform iterative solving according to the signal fusion model to obtain a target fusion range image, including: solving the signal fusion model, updating the initial fusion range image and the initial phase difference according to the solution results, respectively, to obtain an updated range image and an updated phase difference; using the updated range image and the updated phase difference to update the parameters of the signal fusion model to obtain a parameter-updated model; using the parameter-updated model as the signal fusion model, and repeating the above steps of solving the signal fusion model until the target fusion range image is obtained.

[0185] For the specific definition of a radar target detection and identification device, please refer to the definition of a radar target detection and identification method above, which will not be repeated here. Each module in the above-mentioned radar target detection and identification device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0186] A radar target detection and recognition device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more fixed programs, and / or other devices that can provide the above functions.

[0187] The embodiment of the present application also provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a radar target detection and recognition method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0188] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0189] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0190] The embodiment of the present application provides a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method of any embodiment of the present application.

[0191] For the convenience of description, when describing the above device, various units are divided into functions and described respectively. Of course, when implementing the present application, the function of each unit can be realized in the same one or more software and / or hardware. It should be understood by those skilled in the art that the embodiments of the present application can be provided as methods, systems, or computer program products. It should be understood that the combination of each flow process and / or square frame in the flow chart and / or block diagram and the flow chart and / or square frame in the flow chart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processing machine or other programmable data processing equipment to produce a machine, so that the instruction executed by the processor of a computer or other programmable data processing equipment produces a device for realizing the function specified in one flow process or multiple flow processes and / or one square frame or multiple square frames of a flow chart.

[0192] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0193] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. Since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0194] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0195] Although the embodiments of the present application are described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A radar target detection and recognition method, characterized in that: The method comprises: Determine a first echo signal corresponding to a first transmitted signal and a second echo signal corresponding to a second transmitted signal; wherein the first echo signal is used to represent a reflected portion of the first transmitted signal by a scattering center; the second echo signal is used to represent a reflected portion of the second transmitted signal by the scattering center, and the first echo signal has a first range image relative to the scattering center, and the second echo signal has a second range image relative to the scattering center; determining a splicing frequency band of the first echo signal and the second echo signal, and an initial fused range image of the first range image and the second range image; Constructing a signal fusion model based on the spliced ​​frequency band and the initial fused range image; wherein the signal fusion model is used to reflect the corresponding relationship between the spliced ​​frequency band and the fused range image in a matrix form; An iterative solution is performed according to the signal fusion model to obtain a target fusion range image to represent the relative position relationship between the radar and the scattering center.

2. The method according to claim 1, characterized in that Before constructing the signal fusion model based on the spliced ​​frequency band and the initial fused range image, the method further includes: determining an initial phase difference between the first echo signal and the second echo signal; Accordingly, the constructing of a signal fusion model based on the spliced ​​frequency band and the initial fusion range image includes: The signal fusion model is constructed according to the spliced ​​frequency band, the initial fusion range image and the initial phase difference.

3. The method according to claim 2, characterized in that The iterative solution is performed according to the signal fusion model to obtain the target fusion range image, including: Solving the signal fusion model, and updating the initial fused range image and the initial phase difference according to the solution results to obtain an updated range image and an updated phase difference; Using the updated range image and the updated phase difference to update the parameters of the signal fusion model, to obtain a model after parameter update; The model after parameter update is used as the signal fusion model, and the above steps of solving the signal fusion model are repeated until the target fusion range image is obtained.

4. The method according to claim 2, characterized in that: The iterative solution is performed according to the signal fusion model to obtain the target fusion range image, including: Based on the signal fusion model, one of the range image solution and the phase difference solution is performed, and one of the initial fused range image and the initial phase difference is updated accordingly, so as to obtain a first intermediate model accordingly; Based on the first intermediate model, another operation of solving the range image and solving the phase difference is performed, and the other of the initial fused range image and the initial phase difference is updated accordingly, so as to obtain a second intermediate model accordingly; The second intermediate model is used as a signal fusion model, and the above-mentioned alternating solution steps for the signal fusion model are repeated until the target fusion range image is obtained.

5. The method according to claim 2, characterized in that: The determining an initial phase difference between the first echo signal and the second echo signal comprises: performing a differential operation on the first echo signal and the second echo signal to obtain a phase difference signal; The phase difference signal is coupled and analyzed to obtain the initial phase difference including the residual misalignment phase error term and the linear phase error term; wherein the residual misalignment phase error term refers to the error term related to the scattering center position; the linear phase error term refers to the error caused by the overall misalignment of the time-frequency trajectory between signals due to the overall translation of the signal time-frequency trajectory.

6. The method according to claim 2, characterized in that The determining a splicing frequency band of the first echo signal and the second echo signal includes: Performing de-linear frequency modulation processing on the first echo signal and the second echo signal to obtain a first intermediate echo signal and a second intermediate echo signal; Performing time-frequency conversion and simplification processing on the first intermediate echo signal and the second intermediate echo signal to obtain a first frequency domain echo signal and a second frequency domain echo signal; The spliced ​​frequency band is obtained by performing sampling and fusion processing based on the first frequency domain echo signal and the second frequency domain echo signal.

7. The method according to claim 1, characterized in that The initial fused range image of the first range image and the second range image is obtained by: performing de-linear frequency modulation processing on the first echo signal and the second echo signal to obtain a first intermediate echo signal and a second intermediate echo signal; Performing time-frequency conversion and simplification processing on the first intermediate echo signal and the second intermediate echo signal to obtain a first frequency domain echo signal and a second frequency domain echo signal; Applying inverse Fourier transform to the first frequency domain echo signal to obtain the first range image, and applying inverse Fourier transform to the second frequency domain echo signal to obtain the second range image; The first range image and the second range image are sampled and fused to obtain the initial fused range image.

8. A radar system, characterized in that: include: A signal transmitting module, used for transmitting radar signals of different frequency bands; A signal receiving module, used for receiving an echo signal reflected from a scattering center; A signal processing module, used to execute the radar target detection and recognition method according to any one of claims 1 to 7; The display module is used to display the target fusion range image.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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