Radar complementary polyphase coding frequency modulation signal joint transmit-receive optimization method and device

Abstract

The invention relates to a radar complementary multi-phase coding frequency modulation signal joint transmit-receive optimization method and device, and the method comprises the steps: transmitting a preset complementary multi-phase coding frequency modulation signal to a target region through each channel of a transmitting end, and carrying out the receiving of a received target echo signal at a receiving end, and after the target echo signal is filtered by using a preset receiving filter bank, a waveform after sending-receiving joint optimization is obtained, and accurate detection of the target is realized according to the waveform.

Description

Technical Field

[0001] The present application relates to the technical field of radar waveform generation, and in particular to a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization method and device. Background Art

[0002] In MIMO radar, in order to avoid mutual interference between different channels, the transmit waveform set is generally required to have good orthogonality. In order to make the radar system have better moving target detection performance and clutter suppression capability, the transmit waveform is also required to have good autocorrelation performance and Doppler tolerance. Most of the existing MIMO radar transmit waveform design work is based on phase-coded waveforms. Although the phase-coded waveform has a high degree of freedom in waveform design, due to the drastic phase jumps between different sub-pulses, it has high requirements on the transmitter in practical applications and is usually difficult to achieve theoretical performance. In addition, the research scope of existing MIMO radar transmit waveform design work is usually concentrated within a pulse repetition period, ignoring the superiority of multi-pulse combination within the coherent processing interval. Summary of the invention

[0003] Based on this, it is necessary to provide a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization method and device that can effectively improve target detection in response to the above technical problems.

[0004] A radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method, the method is implemented at the transmitting end and the receiving end of the radar system, comprising:

[0005] Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area;

[0006] After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal;

[0007] The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

[0008] In one embodiment, when constructing the transmit-receive joint optimization model:

[0009] The complementary polyphase coded frequency modulation signal of each channel and the parameters of the receiving filter are used as variables to be optimized;

[0010] The optimization objective function is to minimize the side lobes of the complementary self-ambiguity function and the mutual ambiguity function in the range-Doppler interval of interest, and at the same time, the total energy of the receiving filter bank is constant as a constraint;

[0011] The transmit-receive joint optimization model is constructed according to the variables to be optimized, the optimization objective function and the constraint conditions.

[0012] In one embodiment, the transmit-receive joint optimization model is expressed as:

[0013]

[0014] in,

[0015] In the above formula, f(s,w) represents the sidelobe sum of the self-ambiguity function and the mutual ambiguity function of the baseband complementary transmit waveform and the receive filter group in the range-Doppler interval of interest, x represents the baseband transmit waveform, w represents the receive filter, represents the receive filter parameters corresponding to the i-th pulse in channel q, and the superscript H represents the conjugate transpose. represents the i-th pulse transmission signal of the q-th channel of the radar system, represents the ith pulse baseband transmission signal of the qth channel, G represents the shaping matrix from the baseband signal to the transmission signal, represents the weight factor, h represents the Doppler unit, is the Doppler interval of interest, d is the distance unit, is the distance interval of interest, p is a positive integer, represents the correlation function of the ith pulse of the qth and q'th channels when the Doppler shift is h, (·) * represents conjugation, ||·|| p represents the p-norm, F represents the Fourier transform matrix, I represents the number of pulses in each channel, and Q represents the number of channels of the radar system.

[0016] In one embodiment, when solving the transmit-receive joint optimization model:

[0017] The parameters of the receiving filter group in the transmitting-receiving joint optimization model are fixed, the baseband transmitting waveform of each pulse of each channel is updated respectively by using the L-BFGS algorithm, and the corresponding complementary polyphase coded frequency modulation signal is obtained according to the baseband transmitting waveform;

[0018] Bringing the complementary polyphase coded frequency modulation signal into the transmit-receive joint optimization model, and solving the parameters of the receive filter bank using the MM algorithm;

[0019] The baseband transmission waveform and the parameters of the receiving filter group in the transmitting-receiving joint optimization model are solved by alternate iteration until convergence, so as to obtain the optimized complementary polyphase coded frequency modulation signal and the receiving filter group parameters.

[0020] In one embodiment, when the baseband transmission waveform of each pulse of each channel is updated respectively by using the L-BFGS algorithm, the following formula is used to solve the derivative information of the objective function with respect to the variable to be optimized:

[0021]

[0022] In the above formula,

[0023] represents the weighted correlation function of the ith pulse of the qth and q'th channels when the Doppler shift is h, F represents the Fourier transform matrix, It represents the acceptance filter parameters after zero padding for the ith pulse of the qth channel when the Doppler shift is h.

[0024] In one embodiment, when the baseband transmission waveform and the parameters of the receiving filter bank in the transmitting-receiving joint optimization model are alternately iterated and solved, the iteration termination condition is:

[0025]

[0026] Or, the number of iterations is greater than a preset number threshold;

[0027] In the above formula, the superscript z represents the number of iterative solutions, and ε0 represents the preset convergence threshold value.

[0028] The present application also provides a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization device, the device comprising:

[0029] A transmitting module, used for each channel of the transmitting end to transmit a preset complementary multi-phase coded frequency modulation signal to a target area;

[0030] A receiving module, which is used for filtering the target echo signal by using a preset receiving filter group after the receiving end receives the target echo signal to obtain a filtered echo signal, and performing target detection according to the filtered echo signal;

[0031] The complementary optimization module is used for solving the transmission-reception joint optimization model to obtain the parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group.

[0032] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0033] Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area;

[0034] After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal;

[0035] The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

[0036] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0037] Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area;

[0038] After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal;

[0039] The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

[0040] The above-mentioned radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method and device transmits a preset complementary polyphase coded frequency modulation signal to the target area through each channel of the transmitting end, and filters the received target echo signal at the receiving end using a preset receiving filter group to obtain a waveform after the transmission-reception joint optimization, and realizes accurate detection of the target based on the waveform. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a diagram of the application environment of a radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method in one embodiment;

[0042] Figure 2 This is a schematic diagram of the convergence curve of the objective function with the number of iterations under different values ​​of p in a simulation experiment;

[0043] Figure 3 A schematic diagram of the self-ambiguity function of transmitting channel 1 and receiving channel 1 in a simulation experiment;

[0044] Figure 4 A schematic diagram of the mutual ambiguity function of the transmitting channel 1 and the receiving channel 2 in a simulation experiment;

[0045] Figure 5 A schematic diagram of the mutual ambiguity function of the transmitting channel 2 and the receiving channel 1 in a simulation experiment;

[0046] Figure 6 A schematic diagram of the self-ambiguity function of transmitting channel 2 and receiving channel 2 in a simulation experiment;

[0047] Figure 7 It is a structural block diagram of a radar complementary multi-phase coded frequency modulation signal joint receiving and transmitting optimization device in one embodiment;

[0048] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] In the existing radar transmission waveform design, the design based on phase-coded waveform has a high degree of design freedom, but due to the drastic phase jump between different sub-pulses, it has high requirements on the transmitter and is difficult to achieve theoretical performance. At the same time, the scope of waveform design is often concentrated within a pulse repetition period, ignoring the advantages of multiple pulses combined within the coherent processing interval, such as Figure 1 As shown, a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization method is provided, which is implemented in the transmitting end and the receiving end of the radar system, and specifically includes the following steps:

[0051] Step S100: Each channel of the transmitting end transmits a preset complementary polyphase coded frequency modulation signal to a target area.

[0052] Step S110, after receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection based on the filtered echo signal.

[0053] Step S120, the preset parameters of the complementary polyphase coded frequency modulation signal and the receiving filter bank are obtained by solving the transmitting-receiving joint optimization model.

[0054] In the present application, a complementary joint optimization method is adopted at the receiving end and the transmitting end in the radar system to achieve accurate detection of the target. Specifically, the baseband complementary transmission waveform of multi-phase coded frequency modulation is adopted at the transmitting end, which can make the transmission signal have better autocorrelation and cross-correlation characteristics, reduce channel interference, and the receiving filter group at the receiving end can further filter out noise and interference. The combination of the two can effectively improve the quality of the received target echo signal. The parameters of the pre-set baseband complementary transmission waveform and the receiving filter group are obtained by solving the transmission-reception joint optimization model, which means that the design of the transmission waveform is coordinated with the filtering processing at the receiving end, which can make the target echo signal more prominent during detection, improve the detection probability of the target, identify the target more accurately, and improve the detection performance and clutter suppression capability of the moving target, and optimize the detection effect. In addition, the joint optimization enables the transmitting end and the receiving end to work together, so that the resource utilization of the entire MIMO radar system is more efficient, reducing unnecessary waste of resources, and improving the overall performance and work efficiency of the system.

[0055] In this embodiment, when constructing a transmit-receive joint optimization model: the baseband complementary transmit waveforms of the multi-phase coded frequency modulation of each channel and the parameters of the receive filter are taken as variables to be optimized, and minimizing the side lobes of the complementary self-ambiguity function and the mutual ambiguity function in the range-Doppler interval of interest is taken as the optimization objective function. At the same time, the constant total energy of the receive filter group is taken as a constraint condition, and finally the transmit-receive joint optimization model is constructed according to the variables to be optimized, the optimization objective function and the constraint conditions.

[0056] In this embodiment, it is assumed that the PCFM-MIMO radar system transmits a signal Where M is the length of the single pulse transmission waveform of each channel, I is the number of pulses contained in the pulse repetition period, and Q is the number of channels. Assume that the baseband transmission waveform is Among them, N is the length of the single pulse baseband transmission waveform of each channel. The relationship between the two, namely the transmission signal of the radar system and the baseband transmission waveform, that is, the transmission signal after PCFM modulation, is expressed as:

[0057]

[0058] In formula (1), They represent the transmission signal of the ith pulse in the qth channel and the baseband transmission waveform M=KN, where K is the oversampling multiple. j is the imaginary unit, and G represents the shaping matrix from the baseband signal to the transmission signal. Specifically, G=[g1,g2,…,g N ].

[0059] Furthermore,

[0060] g n =[g n (1),gn (2),…,g n (M)],n=1,2,…M (2)

[0061] Furthermore,

[0062] The sidelobes and f(s,w) of the self-ambiguity function and mutual ambiguity function of the complementary transmit waveform and the receive filter bank in the range-Doppler interval of interest can be expressed as:

[0063]

[0064] In formula (4), h represents the Doppler unit, represents the Doppler interval of interest, d represents the range unit, represents the distance interval of interest, and p represents a positive integer. and is the weight factor.

[0065] Specifically, for When q = q', that is, in the summation process, if the two summation channels are equal, and hour, In other cases, It is used to extract the distance unit of interest in the correlation function. When the index is within the distance unit interval of interest, the element under the index takes the value of 1, otherwise it takes the value of 0.

[0066] Furthermore, in formula (4), (·) * represents conjugation, ||·|| p represents the p-norm. The correlation function of the i-th pulse of the q-th and q'-th channels when the Doppler shift is h can be expressed as:

[0067]

[0068] In formula (5), F is the Fourier transform matrix, and:

[0069]

[0070] Substituting formula (5) into formula (4), we can obtain:

[0071]

[0072] Therefore, the optimization model of the PCFM transmit waveform and receive filter bank with high Doppler tolerance can be jointly designed, which can be expressed as a transmit-receive joint optimization model, which can be expressed as:

[0073]

[0074] The energy constraint imposed on the receiving filter is to reduce the mismatch signal-to-interference-noise ratio loss caused by the mismatch between the transmitting waveform and the receiving filter.

[0075] In this embodiment, when solving the transmit-receive joint optimization model: first, the parameters of the receive filter group in the transmit-receive joint optimization model are fixed, and the baseband transmit waveform of each pulse of each channel is updated by the L-BFGS algorithm, that is, According to the baseband transmission waveform, the corresponding pulse code frequency modulation waveform is obtained, that is, Then, the pulse code frequency modulation waveform is introduced into the transmit-receive joint optimization model, and the parameters of the receive filter group are solved using the MM algorithm. The baseband transmit waveform and the parameters of the receive filter group in the transmit-receive joint optimization model are alternately iterated and solved until convergence, thereby obtaining the optimized baseband complementary transmit waveform and receive filter group parameters.

[0076] Next, the solutions for the baseband transmit waveform and receive filter bank parameters are described respectively.

[0077] In this embodiment, when solving the baseband transmit waveform based on the transmit-receive joint optimization model, the parameters of the receive filter group in the transmit-receive joint optimization model are first fixed, that is, the baseband transmit waveform is solved as an unknown number. At this time, the transmit-receive joint optimization model will be converted into a problem model for solving the baseband transmit waveform, which is expressed as:

[0078]

[0079] Since the problem model has a complex high-order objective function and is a strongly non-convex optimization problem, the Limited Memory Broyden Flecher Goldfarb and Shanno (L-BFGS) algorithm is used to solve the above optimization problem. In the L-BFGS algorithm, it is necessary to solve the derivative information of the objective function with respect to the optimization variable.

[0080] Furthermore, when solving the derivative information of the objective function with respect to the optimization variable, the problem model The objective function in can be rewritten as:

[0081]

[0082] Each summation pair The partial derivative of can be written as:

[0083]

[0084] At the same time, it can be deduced that:

[0085]

[0086] Combining formula (5) and formula (13) we can get:

[0087]

[0088] Furthermore, by combining formula (12) and formula (14), we can obtain:

[0089]

[0090] in,

[0091] Specifically, formula (15) is the partial derivative of the objective function for a code in the baseband transmission signal, and its partial derivative for a single-channel single-pulse baseband transmission waveform can be written as a column-connected arrangement of partial derivative results of different codes, expressed as:

[0092]

[0093] Therefore, by combining formula (11) and formula (17), the partial derivative of the objective function for the single-channel single-pulse baseband transmission signal waveform can be expressed as:

[0094]

[0095] In formula (18),

[0096] represents the weighted correlation function of the ith pulse of the qth and q'th channels when the Doppler shift is h, F represents the Fourier transform matrix, It represents the acceptance filter parameters after zero padding for the ith pulse of the qth channel when the Doppler shift is h.

[0097] Formula (18) is used to solve the partial derivative of f(s) with respect to the baseband signal of each pulse of each transmission channel, and the derivative information is substituted into the L-BFGS algorithm to update the baseband transmission signal of each pulse of each transmission channel. Finally, formula (1) is used to update the PCFM transmission waveform.

[0098] In this embodiment, when solving the parameters in the receiving filter group, the PCFM transmission waveform obtained by solving is brought into the transmitting-receiving joint optimization model and fixed, that is, the parameters in the receiving filter group are solved as unknown data. At this time, the transmitting-receiving joint optimization model can be written as:

[0099]

[0100] in,

[0101] In formula (20), is the weight coefficient, which takes the value of 0 when the conditions q = q', d = 0, and h is in the range-Doppler unit of interest, and takes the value of 1 under other conditions. d is a displacement matrix, whose elements in row a and column b are:

[0102]

[0103] Furthermore, in order to transform the problem formula (19) to a form that can be solved by the Majorization-Minimization (MM) algorithm, the upper bound function of the original problem is constructed by introducing auxiliary variables, where the introduced auxiliary variables are expressed as:

[0104]

[0105] In formula (24), M I =I(2M-1), so formula (20) can be transformed into:

[0106]

[0107] Furthermore, the transmit waveform of each channel and the parameters of the receive filter bank are combined into a variable by column, which are:

[0108]

[0109] Its relationship with the single-channel transmit waveform and receive filter is:

[0110]

[0111] In formula (28) and formula (29), T is the block selection matrix, which is defined as:

[0112]

[0113] Then formula (25) can be further transformed into:

[0114]

[0115] According to the properties of the matrix trace, formula (31) can be derived as follows:

[0116]

[0117] In formula (32),

[0118] After finding the upper bound function of formula (32), the problem model formula (19) can be transformed into:

[0119]

[0120] Specifically, when optimizing the parameters of the qth channel receiving filter separately, the corresponding sub-problem model can be written as:

[0121]

[0122] In formula (34), By defining the matrix K, Can be used Expressed as K is an M I ×MI-dimensional matrix, which is defined as:

[0123]

[0124] Therefore, the problem model formula (34) can be finally transformed into:

[0125]

[0126] in,

[0127]

[0128] Since, in formula (37) is a Hermitian matrix, and the problem model is a quadratic equality constrained linear optimization problem, whose closed-form optimization solution can be written as:

[0129]

[0130] in,

[0131]

[0132] In this embodiment, based on the transmit-receive joint optimization model, the above method is used to continuously and alternately iterate and solve the transmit-receive joint optimization model until an iteration termination condition is met.

[0133] In this embodiment, the iteration termination condition is:

[0134]

[0135] Or, the number of iterations is greater than a preset number threshold, that is, z>z0;

[0136] In the above formula, the superscript z represents the number of iterative solutions, z0 represents the preset number threshold, and ε0 represents the preset convergence threshold.

[0137] In this paper, the effectiveness of this method is also demonstrated through simulation experimental results.

[0138] In the simulation experiment, the optimization problem parameters are first determined: According to the steps of constructing the transmit-receive joint optimization model in this method, it is assumed that the radar system transmits signal channels M = 2, bandwidth B = 100 MHz, phase coding code length N = 64, and carrier frequency f s =14GHz, the normalized distance interval where the target may appear is [-3,3], and the normalized Doppler frequency interval where the target may appear is [-3,3]. The angle where the target may appear in the airspace is [30°, 40°], and the angle where the clutter may appear in the airspace is [-90°, 30°)∪(40°, 90°). The frequency response of the target within the radar working bandwidth is a full 1 vector, and the power spectrum characteristics of the clutter are as follows: Figure 2 shown.

[0139] Next, the optimal energy spectrum of the transmission sequence of each channel is solved: the optimal transmission waveform energy spectrum of each channel is solved according to the water injection method, such as Figure 3 shown.

[0140] Furthermore, a non-convex optimization model is constructed by taking the MIMO radar transmit sequence set as the optimization variable and minimizing the sidelobes of the non-periodic autocorrelation function of each transmit sequence to be optimized in a specific distance-Doppler interval as the objective function. Meanwhile, the angular energy ratio of the target and clutter in the transmit pattern of the sequence set to be optimized, the minimum mean square error between the waveform spectrum of the sequence set to be optimized and the ideal spectrum, and the constant modulus constraint are taken as constraints.

[0141] Finally, the non-convex optimization model is solved, the problem model is transformed into a convex approximation, and the non-convex optimization model is iteratively solved using an accelerated continuous convex approximation algorithm to obtain a MIMO radar transmission sequence set.

[0142] The specific implementation process of the above steps has been described in the previous text and will not be repeated here. The following numerical simulation experiment further illustrates the beneficial effects of the method of the present invention:

[0143] Establish an optimization problem model: determine the number of radar system transmission signal channels Q = 2, the number of pulses in each channel I = 2, the time bandwidth product T = 32, the oversampling multiple K = 2, and the range unit of interest Doppler unit of interest Figure 2 The normalized convergence curve of the objective function f(s,w) under different norm p values. It can be seen that the algorithm has good convergence under different norm values; and as the value of p increases, the convergence speed of the objective function increases. Figure 3 , Figure 4 , Figure 5 , Figure 6These are the results of self-ambiguity function and mutual ambiguity function of different transmitting and receiving channels, respectively. It can be seen that the ambiguity function composed of the designed PCFM transmitting waveform and receiving filter bank has a deep depression in the range-Doppler unit of interest.

[0144] In the above radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method, the polyphase coded frequency modulation baseband complementary transmission waveform of each channel and its receiving filter are used as optimization variables, the side lobes of the complementary self-ambiguity function and the mutual ambiguity function in the range-Doppler interval of interest are minimized as the optimization objective function, and the total energy of the receiving filter is constant as the constraint condition, and a transmission-reception joint optimization model is established. When solving the baseband transmission waveform based on the transmission-reception joint optimization model, the parameters of the receiving filter are fixed, and the baseband transmission waveform of each pulse of each channel is updated respectively by the L-BFGS algorithm, and then the PCFM transmission waveform is updated, and then the updated PCFM transmission waveform is brought into the transmission-reception joint optimization model, and the problem is convexly approximated by Majorization-Minimization (MM algorithm), and the closed-form solution of the receiving filter is solved and updated, and the parameters of the baseband transmission waveform and the receiving filter are alternately iterated until the problem converges, and the optimization result is finally output.

[0145] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0146] In one embodiment, Figure 7 As shown, a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization device is provided, comprising: a transmitting module 200, a receiving module 210 and a complementary optimization module 220, wherein:

[0147] Transmitting module 200, used for each channel of the transmitting end to transmit a preset complementary multi-phase coded frequency modulation signal to a target area;

[0148] The receiving module 210 is used for filtering the target echo signal by using a preset receiving filter group after the receiving end receives the target echo signal to obtain a filtered echo signal, and performing target detection according to the filtered echo signal;

[0149] The complementary optimization module 220 is used to obtain the parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group by solving the transmission-reception joint optimization model.

[0150] For the specific definition of the radar complementary multi-phase coded frequency modulation signal joint transceiver optimization device, please refer to the definition of the radar complementary multi-phase coded frequency modulation signal joint transceiver optimization method mentioned above, which will not be repeated here. Each module in the above-mentioned radar complementary multi-phase coded frequency modulation signal joint transceiver optimization 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-mentioned modules.

[0151] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network 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 network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a radar complementary multi-phase coded frequency modulation signal joint transmission and reception optimization 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 shell, or an external keyboard, touchpad or mouse, etc.

[0152] Those skilled in the art will understand that Figure 8 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.

[0153] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0154] Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area;

[0155] After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal;

[0156] The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

[0157] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0158] Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area;

[0159] After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal;

[0160] The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

[0161] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0162] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0163] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method, characterized in that: The method is implemented at the transmitting end and the receiving end of the radar system, and includes: Each channel of the transmitting end transmits a preset complementary multi-phase coded frequency modulation signal to the target area; After receiving the target echo signal, the receiving end filters the target echo signal using a preset receiving filter group to obtain a filtered echo signal, and performs target detection according to the filtered echo signal; The parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group are obtained by solving a transmitting-receiving joint optimization model.

2. The radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method according to claim 1, characterized in that: When constructing the transmit-receive joint optimization model: The complementary polyphase coded frequency modulation signal of each channel and the parameters of the receiving filter are used as variables to be optimized; The optimization objective function is to minimize the side lobes of the complementary self-ambiguity function and the mutual ambiguity function in the range-Doppler interval of interest, and at the same time, the total energy of the receiving filter bank is constant as a constraint; The transmit-receive joint optimization model is constructed according to the variables to be optimized, the optimization objective function and the constraint conditions.

3. The radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method according to claim 2, characterized in that: The transmit-receive joint optimization model is expressed as: in, In the above formula, f(s,w) represents the sidelobe sum of the self-ambiguity function and the mutual ambiguity function of the baseband complementary transmit waveform and the receive filter group in the range-Doppler interval of interest, x represents the baseband transmit waveform, w represents the receive filter, represents the receive filter parameters corresponding to the i-th pulse in channel q, and the superscript H represents the conjugate transpose. represents the i-th pulse transmission signal of the q-th channel of the radar system, represents the ith pulse baseband transmission signal of the qth channel, G represents the shaping matrix from the baseband signal to the transmission signal, represents the weight factor, h represents the Doppler unit, is the Doppler interval of interest, d is the distance unit, is the distance interval of interest, p represents a positive integer, represents the correlation function of the ith pulse of the qth and q'th channels when the Doppler shift is h, (·) * represents conjugation, ||·|| p represents the p-norm, F represents the Fourier transform matrix, I represents the number of pulses in each channel, and Q represents the number of channels of the radar system.

4. The radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method according to claim 2 or 3, characterized in that: When solving the transmit-receive joint optimization model: The parameters of the receiving filter group in the transmitting-receiving joint optimization model are fixed, the baseband transmitting waveform of each pulse of each channel is updated respectively by using the L-BFGS algorithm, and the corresponding complementary polyphase coded frequency modulation signal is obtained according to the baseband transmitting waveform; Bringing the complementary polyphase coded frequency modulation signal into the transmit-receive joint optimization model, and solving the parameters of the receive filter bank using the MM algorithm; The baseband transmission waveform and the parameters of the receiving filter group in the transmitting-receiving joint optimization model are solved by alternate iteration until convergence, so as to obtain the optimized complementary polyphase coded frequency modulation signal and the receiving filter group parameters.

5. The radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method according to claim 4, characterized in that: When the L-BFGS algorithm is used to update the baseband transmission waveform of each pulse of each channel, the following formula is used to solve the derivative information of the objective function with respect to the variable to be optimized: In the above formula, represents the weighted correlation function of the ith pulse of the qth and q'th channels when the Doppler shift is h, F represents the Fourier transform matrix, It represents the acceptance filter parameters after zero padding for the ith pulse of the qth channel when the Doppler shift is h.

6. The radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization method according to claim 5, characterized in that: When the baseband transmission waveform and the parameters of the receiving filter bank in the transmitting-receiving joint optimization model are alternately iterated and solved, the iteration termination condition is: Or, the number of iterations is greater than a preset number threshold; In the above formula, the superscript z represents the number of iterative solutions, and ε0 represents the preset convergence threshold value.

7. A radar complementary polyphase coded frequency modulation signal joint transmission and reception optimization device, characterized in that: The device comprises: A transmitting module, used for each channel of the transmitting end to transmit a preset complementary multi-phase coded frequency modulation signal to a target area; A receiving module, which is used for filtering the target echo signal by using a preset receiving filter group after the receiving end receives the target echo signal to obtain a filtered echo signal, and performing target detection according to the filtered echo signal; The complementary optimization module is used for solving the transmission-reception joint optimization model to obtain the parameters of the preset complementary polyphase coded frequency modulation signal and the receiving filter group.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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