Ground penetrating radar control method, device, equipment and storage medium

Abstract

The application belongs to the technical field of ground penetrating radar, and provides a ground penetrating radar control method, device, equipment and storage medium, wherein the method comprises: generating a frequency sequence group matrix meeting preset requirements of a ground penetrating radar by using a chaotic mapping, optimizing the frequency sequence group matrix according to a preset genetic algorithm, obtaining an orthogonal discrete frequency coding transmission waveform set, based on the orthogonal discrete frequency coding transmission waveform set, calling a double-channel narrowband, wideband transceiver and a heterogeneous system-level chip of the ground penetrating radar to transmit a waveform to the ground and receive a reflected waveform, analyzing and processing the reflected waveform, obtaining a ground penetrating result, so as to improve work efficiency, meet high-speed operation detection requirements, improve detection accuracy of the radar, have a unique advantage for spectrum analysis and interference suppression, realize a balance between detection depth and resolution, and do not need complex signal processing technology.

Description

Ground penetrating radar control methods, devices, equipment and storage media Technical Field

[0001] This application relates to the field of ground penetrating radar technology, and more specifically, to a ground penetrating radar control method, apparatus, device, and storage medium. Background Technology

[0002] Ground penetrating radar (GPR) is a non-destructive geophysical exploration technique used to detect subsurface structures. It detects subsurface objects and interfaces by emitting high-frequency electromagnetic waves and receiving reflected waves. Arrayed antennas play a crucial role in GPR systems, responsible for transmitting and receiving electromagnetic signals. Current GPR systems include impulse pulse, linear frequency modulated (LFM) continuous wave, and stepped-frequency (PMC) continuous wave radars. Impulse pulse radars require advanced signal processing techniques to improve detection accuracy. LFM continuous wave radars can perform multiple measurements during signal transmission, improving measurement efficiency, but their hardware complexity is high, and signal processing is equally complex. PMC radars are easy to operate and do not require advanced signal processing techniques or numerous electronic components, but they typically perform single measurements. Summary of the Invention

[0003] The main objective of this application is to provide a ground-penetrating radar control method, device, equipment, and storage medium to simplify the hardware and signal processing complexity of ground-penetrating radar, and to enable multiple measurements by ground-penetrating radar, thereby improving detection accuracy and measurement efficiency.

[0004] To achieve the above-mentioned objectives, this application provides a ground-penetrating radar control method, comprising:

[0005] A frequency sequence matrix that meets the preset requirements of ground penetrating radar is generated using chaotic mapping.

[0006] The frequency sequence group matrix is ​​optimized according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set;

[0007] Based on the orthogonal discrete frequency encoded transmitted waveform set, the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar are invoked to transmit waveforms to the ground and receive reflected waveforms.

[0008] The reflected waveform is analyzed and processed to obtain the ground exploration results.

[0009] Preferably, the step of generating a frequency sequence group matrix that meets the preset requirements of ground-penetrating radar using chaotic mapping includes:

[0010] Generating chaotic sequences using chaotic mapping;

[0011] Based on the chaotic sequence, a frequency sequence group matrix that meets the preset requirements of ground penetrating radar is generated according to the mapping relationship.

[0012] Preferably, the method of generating chaotic sequences using chaotic mapping includes:

[0013] Obtain the detection mission requirements of the ground penetrating radar, determine the antenna frequency and set the initial value based on the detection mission requirements;

[0014] Multiple chaotic sequences are generated based on the antenna frequency and initial value through chaotic mapping.

[0015] Preferably, the step of generating a frequency sequence group matrix that meets the preset requirements of ground-penetrating radar based on the chaotic sequence and the mapping relationship includes:

[0016] From the plurality of chaotic sequences, select M chaotic sequences of the target length to obtain a chaotic sequence submatrix; wherein M is a positive integer;

[0017] Frequency mapping is performed on the chaotic sequence submatrix to obtain the frequency matrix;

[0018] The frequency matrix is ​​subjected to Fourier transform using a pre-constructed orthogonal discrete frequency coded signal model to obtain an initial frequency sequence group matrix;

[0019] Calculate the peak-to-sidelobe ratio of the initial frequency sequence group matrix, and select Ψ groups of initial frequency sequence group matrices of preset dimensions according to the peak-to-sidelobe ratio to form a frequency sequence group matrix; wherein, Ψ is a positive integer.

[0020] Preferably, the step of optimizing the frequency sequence group matrix according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set includes:

[0021] The fitness of the frequency sequence group matrix is ​​calculated based on a pre-constructed cost function;

[0022] Determine whether the fitness of the frequency sequence group matrix is ​​greater than a preset fitness.

[0023] If so, determine whether the frequency sequence group matrix conforms to the preset optimization rules;

[0024] If the conditions are met, the frequency sequence group matrix is ​​taken as the optimal frequency sequence group matrix to obtain the orthogonal discrete frequency coded transmission waveform set.

[0025] Furthermore, after determining whether the frequency sequence group matrix conforms to the preset optimization rules, the method further includes:

[0026] If the conditions are not met, the frequency sequence matrix with the highest fitness (ranked in the top W positions) is selected as the parent of the next generation population, and the remaining frequency sequence matrices are eliminated; where W is a positive integer.

[0027] The crossover and mutation probabilities of the parent generation are determined according to the adaptive genetic algorithm and the optimization rules.

[0028] Based on the crossover and mutation probabilities, a new frequency sequence group matrix is ​​generated through crossover and mutation operations, and the step of calculating the fitness of the frequency sequence group matrix according to the pre-constructed cost function is returned until the optimal frequency sequence group matrix is ​​output or the maximum number of iterations is reached.

[0029] Preferably, the ground-penetrating radar includes eleven transceiver antennas, which comprise two four-antenna array units and one three-antenna array unit. Each antenna array unit operates in a time-division multiplexing manner.

[0030] The four antenna array elements simultaneously trigger two transmitting elements and one receiving element, and transmit in two separate steps;

[0031] The three-antenna array unit first triggers two transmitting elements and the receiving element simultaneously, and then triggers the last transmitting element.

[0032] This application also provides a ground-penetrating radar control device, the device comprising:

[0033] The chaotic mapping module is used to generate a frequency sequence group matrix that meets the preset requirements of ground penetrating radar using chaotic mapping.

[0034] The optimization module is used to optimize the frequency sequence group matrix according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set;

[0035] The transmission module is used to transmit waveforms to the ground based on the orthogonal discrete frequency encoded waveform set, and to call the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar, and to receive reflected waveforms.

[0036] The analysis module is used to analyze and process the reflected waveform to obtain the ground exploration results.

[0037] This application also provides a ground-penetrating radar, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the methods described above.

[0038] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the methods described above.

[0039] This application provides a ground-penetrating radar (GPR) control method, apparatus, device, and storage medium. It utilizes chaotic mapping to generate a frequency sequence matrix that meets the preset requirements of the GPR. The frequency sequence matrix is ​​then optimized using a preset genetic algorithm to obtain an orthogonal discrete frequency-coded transmitted waveform set. Based on this set, the GPR's dual-channel narrowband / wideband transceiver and heterogeneous system-on-a-chip transmit waveforms to the ground and receive reflected waveforms. The reflected waveforms are analyzed and processed to obtain ground-penetrating results, thereby improving work efficiency, meeting the requirements of high-speed operation, and enhancing radar detection accuracy. Furthermore, it offers unique advantages in spectrum analysis and interference suppression, achieving a balance between detection depth and resolution without requiring complex signal processing techniques. The signal optimization design method involved in this invention uses a chaotic mapping frequency sequence matrix as the initial population for the optimization algorithm and employs an adaptive genetic algorithm for optimization, significantly improving the convergence speed of the genetic algorithm, enhancing its global search capability, and obtaining transmitted waveforms with low sidelobes and good orthogonality. Attached Figure Description

[0040] Figure 1 is a schematic flowchart of a ground-penetrating radar control method according to an embodiment of this application;

[0041] Figure 2 is a system block diagram of a ground-penetrating radar according to an embodiment of this application;

[0042] Figure 3 is a structural diagram of an antenna array unit according to an embodiment of this application;

[0043] Figure 4 is an autocorrelation function diagram of signal S1 after optimization design using an adaptive genetic algorithm according to an embodiment of this application;

[0044] Figure 5 is an autocorrelation function diagram of signal S2 after optimization design using an adaptive genetic algorithm according to an embodiment of this application;

[0045] Figure 6 is a graph of the signal cross-correlation function after optimization design using an adaptive genetic algorithm according to an embodiment of this application;

[0046] Figure 7 is a self-fuzzy two-dimensional fuzzy diagram of a signal optimized using an adaptive genetic algorithm according to an embodiment of this application;

[0047] Figure 8 is a graph showing the change in fitness of the algorithm iteration for optimizing signals using an adaptive genetic algorithm according to an embodiment of this application;

[0048] Figure 9 is a schematic block diagram of a ground-penetrating radar control device according to an embodiment of this application;

[0049] Figure 10 is a schematic block diagram of the structure of a ground-penetrating radar according to an embodiment of this application.

[0050] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0052] This application proposes a ground-penetrating radar control method, in which the ground-penetrating radar is the executing entity. This ground-penetrating radar control method is used to solve the technical problems of the high complexity of current ground-penetrating radar hardware and signal processing or the inability to perform single measurements.

[0053] Referring to Figure 1, in one embodiment, this application provides a ground-penetrating radar control method, the method comprising:

[0054] S11. Use chaotic mapping to generate a frequency sequence group matrix that meets the preset requirements of ground penetrating radar;

[0055] S12. Optimize the frequency sequence group matrix according to the preset genetic algorithm to obtain the orthogonal discrete frequency encoded transmission waveform set;

[0056] S13. Based on the orthogonal discrete frequency encoded transmitted waveform set, the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar are invoked to transmit waveforms to the ground and receive reflected waveforms.

[0057] S14. Analyze and process the reflected waveform to obtain the ground exploration results.

[0058] In this embodiment, the ground-penetrating radar includes an array-type MIMO ground-penetrating radar, which is a type of ground-penetrating radar utilizing multiple-input multiple-output (MIMO) technology. It achieves high-precision imaging and localization of underground targets by arranging multiple transceiver antenna elements on the radar antenna to form an array. This radar system can simultaneously transmit and receive signals in multiple directions, effectively improving the sensitivity and resolution of the radar system, enabling it to detect deeper and smaller underground targets. Furthermore, array-type MIMO ground-penetrating radar also has advantages such as strong anti-interference performance and high reliability, and has wide applications in geological exploration, groundwater resource investigation, and environmental monitoring.

[0059] MIMO technology can fully utilize spatial diversity, waveform diversity, and spatial multiplexing techniques to achieve narrowband and high spectral efficiency. This concept can precisely compensate for the shortcomings of conventional stepped-frequency ground-penetrating radar systems, enabling ultra-wideband signals and solving the technical challenges of dynamic range and high transmit power.

[0060] In one embodiment, the ground-penetrating radar includes eleven transceiver antennas, which comprise two four-antenna array elements and one three-antenna array element. Each antenna array element operates in a time-division multiplexing manner.

[0061] The four antenna array elements simultaneously trigger two transmitting elements and one receiving element, and transmit in two separate steps;

[0062] The three-antenna array unit first triggers two transmitting elements and the receiving element simultaneously, and then triggers the last transmitting element.

[0063] A MIMO array ground-penetrating radar mainly consists of an antenna array, a main control unit, a host computer unit, and a ranging unit. The structure of a MIMO array ground-penetrating radar can be divided into two parts: hardware and software. The hardware part includes equipment such as the array antenna, transmitter, receiver, and data acquisition unit. The software part includes data processing and analysis software, which can process, analyze, and display the acquired radar signals.

[0064] The ground-penetrating radar of this invention mainly consists of a four-channel acquisition board, a three-channel acquisition board, and an array antenna. The acquisition board uses the Xilinx Zynq series 7020 chip. The acquisition board of this invention comprises two four-channel acquisition boards and one three-channel acquisition board. Each acquisition board has multiple trigger channels, with one trigger channel corresponding to one transmitting antenna. The main control board sends trigger signals to the acquisition boards through these channels to trigger the transmitting antennas to transmit signals and send radar signals to the target.

[0065] The antenna consists of two four-antenna array units and one three-antenna array unit. Each antenna unit operates in a time-division multiplexing manner, while the four-channel antenna units operate simultaneously with dual transmit and receive, and the three-antenna unit operates simultaneously with three transmit and receive. The three antenna units together form twenty-one channels of echo data. This invention, through the combination of time-division and simultaneous operation, can greatly improve the acquisition speed and achieve high-speed, high-resolution acquisition.

[0066] In one embodiment, to meet the requirements of highway operations, the configuration of the MIMO array is reconfigurable. Referring to Figures 2 and 3, the transceiver antennas are combined into a linear array with a measurement point spacing of 7.5 cm to meet the requirements of multiple transverse measurement lines.

[0067] This embodiment employs a dual-transmit dual-receive mode and a triple-transmit triple-receive mode. To avoid mutual interference between transmitted signals, the transmitting antenna array is divided into two groups. Within each transmission cycle, only one transmitting antenna in each group is triggered by the acquisition board. Simultaneously, two adjacent receiving antennas receive the reflected echo signals, and the acquisition board receives both echo data streams. This ensures that the two TX transmitting antennas at a distance transmit signals simultaneously, with frequency steps performed in opposite directions, guaranteeing that the two transmitted signals do not interfere with each other. Furthermore, each transmitting antenna (TX) corresponds to two receiving antennas (RX). The entire control logic is generated by an FPGA to control the RF switching of the antenna array.

[0068] The waveforms of this invention are specifically generated using an ADRV9002 dual-channel narrowband and wideband RF transceiver and a Zynq-7020 heterogeneous SOC platform. After obtaining the optimized waveform file, the AD9002 and Zynq-7020 are first connected, and the SPI interface is selected for communication. Then, the Zynq reads the signal file generated by MATLAB, converts it to COE format, and loads it into the Zynq's ROM. The sampling rate and resolution of the ADRV9002 chip are configured, and synchronization between the chip and the Zynq-7020 is ensured. The signal in the ROM is transmitted to the ADRV900 for analog-to-digital conversion, connected to an external power amplifier, and then connected to the MIMO array antenna transmitter for transmission.

[0069] As described in step S11 above, chaotic mapping is a nonlinear dynamic system that exhibits unpredictable, random, and complex behavior in time and space. Chaotic mapping can be used to describe some natural phenomena, such as climate change, fluid dynamics, and biological evolution. It is also widely used in cryptography, communication, image processing, and other fields. A key characteristic of chaotic mapping is its extreme sensitivity to initial conditions and parameters; minute changes can lead to completely different results. This behavior is known as the "butterfly effect," meaning that small initial changes in a system can be amplified during its evolution, ultimately leading to entirely different outcomes.

[0070] Ground-penetrating radar (GPR) preset requirements can include high resolution, depth detection, high signal-to-noise ratio (SNR), fast data acquisition speed, and low power consumption, which can be set according to actual needs. High resolution means the GPR needs high-precision and high-resolution imaging capabilities to accurately detect and locate underground objects. Depth detection means the GPR needs to be able to penetrate deep underground to detect objects at greater depths. High SNR means the GPR needs a high signal-to-noise ratio to effectively distinguish target signals from background noise. Fast data acquisition speed means the GPR needs to be able to acquire and process data in real time for real-time monitoring and analysis of underground objects. Low power consumption means the GPR needs to have low power consumption to extend battery life or reduce energy consumption.

[0071] A frequency sequence group matrix is ​​a matrix composed of multiple frequency sequences, each representing a carrier signal in the system. These sequences are orthogonal to each other, avoiding inter-frequency interference. In multi-carrier communication systems, the frequency sequence group matrix typically consists of multiple sine waves, each corresponding to a carrier signal. These sine waves have a fixed frequency difference to achieve orthogonality between different carrier signals. By adjusting the frequency and phase of the sine waves, different frequency sequence groups can be generated, thereby achieving efficient utilization and allocation of frequency resources.

[0072] As described in step S12 above, this application provides a MIMO stepped-frequency ground-penetrating radar array antenna, which achieves rapid multi-channel data acquisition through a combination of time-division and simultaneous methods. Then, based on the transceiver characteristics of the array antenna, an orthogonal MIMO radar waveform design method for detecting road defects is proposed. Specifically, the stepped-frequency ground-penetrating radar array antenna employs a special frequency scanning method to detect underground objects. It transmits a series of continuous short pulse signals, gradually increasing the frequency between each pulse signal to form a frequency scanning sequence. Each signal in this sequence interacts with the underground object, generating an echo signal. These echo signals can be received and recorded, and then information about the underground object can be obtained through data analysis and processing.

[0073] MIMO radar waveforms mainly include: orthogonal phase-coded waveforms, orthogonal discrete frequency-coded waveforms, and frequency and phase joint-coded waveforms. Among them, orthogonal discrete frequency-coded signals can realize signals with random frequency jumps within an ultra-widebandwidth range. By properly designing the frequency coding, orthogonality between signals can be achieved, and high range resolution can be achieved through low sidelobe signal optimization methods. Therefore, orthogonal discrete frequency coding is suitable for the transmission signal of the MIMO step-frequency ground-penetrating radar of this invention.

[0074] Orthogonal frequency division multiplexing (OFDM) is a multi-carrier modulation technique that divides a high-speed data stream into multiple low-speed data streams, each modulated onto an independent subcarrier. These subcarriers are orthogonal, meaning that within one period of one subcarrier, the integral over integer periods of the other subcarriers is zero. This orthogonality prevents interference between subcarriers. OFDM offers many advantages in wireless communication, such as high spectral efficiency, resistance to multipath fading, resistance to frequency-selective fading, and ease of implementation. Orthogonal discrete frequency coding waveform (ODFCW) is essentially an extension of OFDM. OFCW incorporates time coding; its principle is to transmit each signal in N sub-bands sequentially as sub-pulses.

[0075] Optimization design methods for ODCFCW mainly include methods based on random or chaotic sequences, heuristic algorithms, and statistical algorithms such as exact algorithms. Sequence-based methods can quickly generate a large number of frequency-coded sequences, but the resulting signals often have high sidelobes. Statistical design methods, on the other hand, are essentially NP-hard problems, leading to high computational complexity and long iteration times. Therefore, this invention proposes an optimization algorithm combining chaos and genetic algorithms to achieve fast and robust design of large-scale signals.

[0076] Genetic Algorithm (GA) is a heuristic search algorithm inspired by natural selection and genetic mechanisms in biology. GA possesses strong global search capabilities, enabling it to find optimal solutions in a large solution space. For the optimization problem of orthogonal discrete frequency coded waveforms, where the solution space can be very large, GA can help find coded waveforms with good orthogonality and other performance indicators. Furthermore, GA employs random selection, crossover, and mutation operations, which helps the algorithm escape local optima and find better global optima. This is particularly important for optimizing orthogonal discrete frequency coded waveforms because the objective function may have multiple local optima. GA has certain advantages in optimizing orthogonal discrete frequency coded waveforms, effectively finding coded waveforms with good orthogonality and other performance indicators. Therefore, GA is chosen to optimize frequency coding, ultimately obtaining a set of orthogonal discrete frequency coded transmission waveforms.

[0077] This embodiment utilizes chaotic mapping to generate chaotic sequences, and then generates a frequency sequence matrix based on the mapping relationship, serving as the initial population. Using the frequency sequence set as the chromosome significantly saves computational resources and improves the algorithm's iteration speed. An adaptive genetic algorithm is used to adaptively adjust the search parameters during each optimization, achieving better waveform design and signal processing results in the scenario of detecting heterogeneous regions along highways.

[0078] As described in steps S13-S14 above, this embodiment uses the orthogonal discrete frequency encoded transmitted waveform set to call the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar to transmit waveforms to the ground and receive reflected waveforms. Then, the reflected waveforms are analyzed and processed to obtain the ground penetrating results.

[0079] This application provides a ground-penetrating radar (GPR) control method. It utilizes chaotic mapping to generate a frequency sequence matrix that meets the preset requirements of the GPR. The frequency sequence matrix is ​​then optimized using a preset genetic algorithm to obtain an orthogonal discrete frequency-coded transmitted waveform set. Based on this set, the GPR's dual-channel narrowband / wideband transceiver and heterogeneous system-on-a-chip transmit waveforms to the ground and receive reflected waveforms. The reflected waveforms are analyzed and processed to obtain the ground-penetrating results, thereby improving work efficiency, meeting the requirements of high-speed operation, and enhancing the radar's detection accuracy. Furthermore, it offers unique advantages in spectrum analysis and interference suppression, achieving a balance between detection depth and resolution without requiring complex signal processing techniques. The signal optimization design method involved in this invention uses a chaotic mapping frequency sequence matrix as the initial population for the optimization algorithm and employs an adaptive genetic algorithm for optimization. This significantly improves the convergence speed of the genetic algorithm, enhances its global search capability, and yields transmitted waveforms with low sidelobes and good orthogonality.

[0080] In one embodiment, generating a frequency sequence group matrix that meets the preset requirements of ground-penetrating radar using chaotic mapping may specifically include:

[0081] Generating chaotic sequences using chaotic mapping;

[0082] Based on the chaotic sequence, a frequency sequence group matrix that meets the preset requirements of ground penetrating radar is generated according to the mapping relationship.

[0083] This embodiment utilizes chaotic mapping to generate chaotic sequences, and based on these chaotic sequences, generates a frequency sequence matrix that meets the preset requirements of ground-penetrating radar according to the mapping relationship. This chaotic sequence is a digital sequence with randomness and unpredictability; it is a signal generated by a chaotic system. A chaotic system is a nonlinear dynamic system whose behavior is extremely sensitive to initial conditions and parameters; small changes can lead to completely different results. Therefore, signals generated by chaotic systems also possess characteristics such as randomness, complexity, and non-repeatability. Chaotic sequences are typically obtained by discretizing continuous chaotic signals. A digital sequence can be obtained by sampling and quantizing the chaotic signal.

[0084] In one embodiment, generating a chaotic sequence using a chaotic mapping may specifically include:

[0085] Obtain the detection mission requirements of the ground penetrating radar, determine the antenna frequency and set the initial value based on the detection mission requirements;

[0086] Multiple chaotic sequences are generated based on the antenna frequency and initial value through chaotic mapping.

[0087] The requirements for ground penetrating radar (GPR) detection missions can involve aspects such as detection depth, resolution, target type, environmental adaptability, signal-to-noise ratio, and data acquisition speed. The antenna frequency can be determined and an initial value set according to the detection mission requirements. Multiple chaotic sequences can be generated by chaotic mapping based on the antenna frequency and the initial value.

[0088] Detection depth: Ground penetrating radar needs to be able to detect underground objects at a certain depth, usually between tens and hundreds of meters.

[0089] Resolution: Ground penetrating radar needs high resolution to accurately detect and locate underground objects. Resolution requirements typically range from several centimeters to tens of centimeters.

[0090] Object type: Ground penetrating radar needs to be able to detect different types of underground objects, such as metals, non-metals, cavities, pipelines, etc.

[0091] Environmental adaptability: Ground penetrating radar needs to adapt to different environmental conditions, such as terrain, soil type, and humidity.

[0092] Signal-to-noise ratio: Ground penetrating radar needs to have a high signal-to-noise ratio in order to effectively distinguish target signals from background noise.

[0093] Data acquisition speed: Ground penetrating radar needs to be able to acquire and process data in real time in order to monitor and analyze underground objects in real time.

[0094] In one embodiment, generating a frequency sequence group matrix that meets the preset requirements of ground-penetrating radar based on the chaotic sequence and the mapping relationship may specifically include:

[0095] From the plurality of chaotic sequences, select M chaotic sequences of the target length to obtain a chaotic sequence submatrix; wherein M is a positive integer;

[0096] Frequency mapping is performed on the chaotic sequence submatrix to obtain the frequency matrix;

[0097] The frequency matrix is ​​subjected to Fourier transform using a pre-constructed orthogonal discrete frequency coded signal model to obtain an initial frequency sequence group matrix;

[0098] Calculate the peak-to-sidelobe ratio of the initial frequency sequence group matrix, and select Ψ groups of initial frequency sequence group matrices of preset dimensions according to the peak-to-sidelobe ratio to form a frequency sequence group matrix; wherein, Ψ is a positive integer.

[0099] This embodiment utilizes chaotic mapping to generate a large number of chaotic sequences, then extracts multiple sets of chaotic sequences with the required code length from them, maps them into frequency sequences according to the frequency mapping relationship, then substitutes them into the orthogonal discrete frequency coding signal model, performs Fourier transform on them, and then calculates the peak side lobe ratio (PSLR) of each set of frequency sequences to obtain the frequency sequence group matrix with the smallest PSLR.

[0100] In one example, the step is as follows:

[0101] Step A: From multiple sets of chaotic sequences C M,N Extract M frequency sequences of length K from (i,j) to obtain the chaotic sequence submatrix P. H,K (l,p);

[0102] For example, choosing the tent chaotic mapping, where tent is a piecewise linear mapping, uses a random function to generate random numbers between 0 and 0.5 as the initial values ​​for the chaotic mapping. The tent mapping formula is:

[0103]

[0104] x(0)∈(-0.5,0.5) Equation (2);

[0105] Where μ is the control parameter, usually taken as μ∈(0,2] to produce chaotic behavior, x(n) represents the current value of the mapping, that is, the state of the system at time n, and x(n+1) is the state of the system at the next moment. x(0) is the initial value of the chaotic mapping, that is, the state of the system at the initial moment. n=1,2,…N,N is the sequence length. Since chaotic sequences are sensitive to initial values, any number of random sequences of any length can be generated by simply choosing different initial values ​​of x(0) and different μ.

[0106] Since the tent chaotic sequence has the best uniform distribution property, the tent sequence is selected to generate the chaotic sequence encoding group C, which is a matrix composed of M sequences of length N. M is the number of tent sequences selected, and N is the length of each sequence.

[0107]

[0108] i = 1, 2, ..., M, j = 1, 2, ..., N Equation (4);

[0109] Step B: For the submatrix P H,K Frequency mapping is performed on (l,p) to obtain the frequency matrix F. H,K (l,p);

[0110] The main coding scheme is threshold quantization coding, which, while simple, has low uniformity and complexity. Therefore, a new coding scheme is chosen. Considering the need to ensure that the frequency coding group meets the frequency range requirements of the signal, the length of the frequency coding group needs to be adjusted according to the selected bandwidth of the ground penetrating radar.

[0111] First, set the initial value x. m (0)∈(0,1) Iterate according to equation (1) to generate an M*N chaotic sequence matrix C, taking n∈[1,N+999] equation (5). Delete the first 1000 numbers of each row of the matrix to reduce the influence of the initial value. The chaotic sequence matrix C is obtained. M,N (i,j).

[0112] Discretized Chaotic Sequence: The chaotic sequence matrix is ​​discretized into an integer sequence. The chaotic sequence matrix obtained by equation (1) is a floating-point number between [0,3], so it needs to be discretized.

[0113] First, we need to start from matrix C. M,N H sequences of length K are iteratively extracted from (i,j) to form a new chaotic sequence submatrix P. H,K (l,p), where H is the number of rows in the submatrix and K is the number of columns in the submatrix. H∈(1,M),K∈(1,N),l=1,2,...,H,p=1,2,...,K (6).

[0114] Where K corresponds to the number of sub-pulses in the orthogonal discrete frequency encoding, K = B / Δf, and H corresponds to the initial population size in the genetic algorithm. Secondly, for P... H,K Sort each row of (l,p) in ascending order to obtain the sorted chaotic sequence matrix P. H ' ,K (l,p) and in the unsorted matrix P H,K The index matrix Q of (l,p)H,K (l,p).

[0115] index matrix Q H,K Each element in (l,p) is arranged according to Mapped to frequency coding matrix F H,K (l,p), The frequency encoding of the p-th sub-pulse of the l-th waveform, n * f0 is the number of transition intervals between sub-pulses.

[0116]

[0117] At this time, the frequency coding matrix F H,K (l,p) represents M sequences of length K. Since the antenna array elements operate by simultaneously transmitting L signals, the actual signal frequency coding group is an L*K dimensional matrix. L corresponds to the number of antenna elements.

[0118]

[0119] Equation (9) represents a uniformly discrete randomized frequency coding sequence. The final result is a discrete frequency coding group matrix with a number of H / L and a length of K. F H / L,K (l,p) is a three-dimensional matrix of L*K*(H / L), which is the chaotic frequency coding group matrix.

[0120] Step C: For the frequency matrix, establish an orthogonal discrete frequency coded signal model, then perform a Fourier transform on it and calculate its peak-to-side-lobe ratio (PSLR). Select Ψ groups of L*K dimensional frequency sequence matrices to form the initial chaotic discrete frequency coded matrix. This step consists of the following steps:

[0121] (1) Establish the transmitted signal model of the chaotic frequency coding group matrix, and construct each frequency coding group T based on the model. L,K Discrete frequency encoded signal sig l (t), l=1,2,...L.

[0122] (2) Perform Fourier transform on the transmitted signals of all frequency-coded sequence groups to obtain the spectrum signal matrix of each frequency-coded sequence group.

[0123] (3) Calculate the peak side lobe ratio (PSLR) in the spectrum signal matrix, and select the discrete frequency coding sequences with the smallest PSLR as the final selected frequency coding sequence group, which is the initial population of the genetic algorithm.

[0124] For example, for the frequency-coded sequence T L,K Constructing an orthogonal discrete frequency coded signal model:

[0125] Let L be the number of elements in the MIMO radar transmitter array and U be the number of sub-pulses, then T L,K The corresponding set of discrete frequency coded waveforms consisting of L frequency hopping sequences is:

[0126]

[0127] in,

[0128] T is the sub-pulse width, U is the number of sub-pulses, L is the number of transmit array elements, and f l.p =f0+(u-1)Δf is the frequency code of the u-th sub-pulse in the l-th waveform, and Δf=1 / T is the frequency step interval, u=1,2,...U.

[0129] Performing a Fourier transform on the signal yields the frequency domain signal:

[0130]

[0131] f r It's frequency. yes Fourier transform.

[0132] Finally, calculate SIG(f) r PSLR.

[0133]

[0134] |y0| is the maximum amplitude of the main lobe, |y k The amplitude of each signal outside the main lobe.

[0135] Finally, the PSLR-minimum frequency-coded sequence was selected as the initial population.

[0136] In one embodiment, optimizing the frequency sequence group matrix according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set may specifically include:

[0137] The fitness of the frequency sequence group matrix is ​​calculated based on a pre-constructed cost function;

[0138] Determine whether the fitness of the frequency sequence group matrix is ​​greater than a preset fitness.

[0139] If so, determine whether the frequency sequence group matrix conforms to the preset optimization rules;

[0140] If the conditions are met, the frequency sequence group matrix is ​​taken as the optimal frequency sequence group matrix to obtain the orthogonal discrete frequency coded transmission waveform set.

[0141] This invention utilizes an adaptive genetic algorithm to optimize the frequency sequence group matrix, thereby obtaining a set of orthogonal discrete frequency-coded transmission signals with good orthogonality.

[0142] For example, the step includes:

[0143] First, a suitable cost function is established. Since the ground-penetrating radar antenna array needs to transmit two or three signals simultaneously, it is necessary to ensure good orthogonality between the signals. The cost function is established using the peak sidelobe minimization criterion. The cost function mainly includes the autocorrelation sidelobe energy and cross-correlation energy, and the sidelobe peak value of the autocorrelation function and the peak value of the cross-correlation function should also be considered.

[0144] Then, an adaptive genetic algorithm is used to optimize the frequency coding. The optimized individuals are frequency coding sequence groups of a single transmitted waveform set, and the optimized population consists of multiple frequency coding sequences with low PSLR. The adaptive genetic algorithm increases its ability to search for the global optimum by adaptively adjusting the number of mutation points, thereby improving the algorithm's search efficiency and global search capability. The main optimization steps are as follows:

[0145] Based on the established cost function, the cost function is formulated by the criterion of minimizing peak sidelobes;

[0146] Calculate the fitness of the frequency coding group and determine whether it meets the optimization criteria. If it does, output the best frequency coding group; otherwise, continue the optimization process.

[0147] The fitness of each individual is calculated based on the cost function, and individuals with higher fitness are selected as the parents of the next generation. These individuals have a higher probability of being selected, while individuals with lower fitness are eliminated.

[0148] The crossover and mutation probabilities are determined using adaptive genetic algorithm criteria, and new individuals are generated through crossover and mutation.

[0149] Reassess whether the new population fitness meets the optimization criteria. If it does, stop iterating and output the best frequency encoding group; otherwise, continue optimization.

[0150] For example, first, let's establish the cost function:

[0151] For ground-penetrating radar, the autocorrelation function of the discrete frequency coded signal should have the lowest possible sidelobes, while the cross-correlation function should be as small as possible; that is, it should have the following characteristics:

[0152]

[0153] p≠q, p, q=1, 2, ...L Equation (15);

[0154] In practical applications, the cross-correlation of signals cannot be zero. Therefore, in engineering, the following criteria are often used to measure whether signals are close to orthogonal.

[0155] Minimize peak sidelobe criterion:

[0156] (1) Minimize the autocorrelation peak sidelobe level

[0157]

[0158] (2) Minimize the peak level of cross-correlation

[0159]

[0160] According to the minimum peak sidelobe criterion, the cost function should consider not only the autocorrelation sidelobe energy and cross-correlation energy, but also the sidelobe peak of the autocorrelation function and the peak of the cross-correlation function. That is, the cost function can be expressed as:

[0161]

[0162] Therefore, the cost function of the adaptive genetic algorithm is:

[0163]

[0164] Next, we establish the initial population:

[0165] From the frequency-encoded sequence group in step A, select Ψ groups of frequency sequences as the initial population of the genetic algorithm. Each individual is a matrix composed of L frequency sequences of length K. Then the initial population of the genetic algorithm is:

[0166]

[0167] The chromosomes are:

[0168] In the above formula, L is the number of transmitting array elements, K is the number of sub-pulses, and Ψ is the population size.

[0169] Then, the fitness of the individual is calculated based on the cost function, and it is determined whether it meets the optimization criterion. If it does, the best individual and its optimal solution are output; otherwise, the best individual and the optimal solution it represents are output, and the calculation ends.

[0170] In one embodiment, after determining whether the frequency sequence group matrix conforms to a preset optimization rule, the method may further include:

[0171] If the conditions are not met, the frequency sequence matrix with the highest fitness (ranked in the top W positions) is selected as the parent of the next generation population, and the remaining frequency sequence matrices are eliminated; where W is a positive integer.

[0172] The crossover and mutation probabilities of the parent generation are determined according to the adaptive genetic algorithm and the optimization rules.

[0173] Based on the crossover and mutation probabilities, a new frequency sequence group matrix is ​​generated through crossover and mutation operations, and the step of calculating the fitness of the frequency sequence group matrix according to the pre-constructed cost function is returned until the optimal frequency sequence group matrix is ​​output or the maximum number of iterations is reached.

[0174] Adaptive genetic algorithms differ from traditional algorithms in that they use fixed search parameters. They employ adaptive adjustment of these parameters during crossover and mutation, making them more suitable for large-scale frequency coding waveform optimization. Furthermore, adaptive genetic algorithms offer greater controllability, stronger global optimization capabilities, and are better suited for frequency coding optimization in high-bandwidth scenarios. Therefore, adaptive genetic algorithms were chosen for optimization.

[0175] The Adaptive Genetic Algorithm (AGA) is an algorithm that can adaptively adjust the parameters in a genetic algorithm. Compared with traditional genetic algorithms, it has the following advantages:

[0176] Fast convergence speed: Traditional genetic algorithms require manual parameter adjustment, while AGA can automatically adjust parameters, enabling the algorithm to find a better solution in a shorter time, thus achieving faster convergence speed.

[0177] Higher search efficiency: In traditional genetic algorithms, parameter settings may be inappropriate, leading to low search efficiency. AGA, however, can adaptively adjust parameters, resulting in higher search efficiency.

[0178] More adaptable to different problems: In traditional genetic algorithms, the setting of algorithm parameters may depend on the characteristics of different problems, requiring constant manual adjustment of parameters. AGA, on the other hand, can adaptively adjust parameters, making it more adaptable to different problems and reducing the workload of algorithm designers.

[0179] Better global search capability: Traditional genetic algorithms may get stuck in local optima, while AGA can adaptively adjust algorithm parameters to increase the algorithm's ability to search for global optima, thus making it easier to find the global optimum.

[0180] High adaptability: Traditional genetic algorithms may suffer from slow convergence and failure to find the optimal solution due to unreasonable parameter settings. However, AGA can adaptively adjust parameters and has stronger adaptability. Therefore, the adaptive genetic algorithm is chosen as the optimization algorithm.

[0181] In this embodiment, if the frequency sequence group matrix does not conform to the preset optimization rules, optimization will continue.

[0182] Next, calculate the fitness function values ​​for all individuals:

[0183] T L,K (i) Substitute into the signal model

[0184]

[0185] Then, the sidelobe peaks of the autocorrelation function and the cross-correlation function, as well as the autocorrelation sidelobe energies and cross-correlation energies, are calculated. The values ​​of weights w1, w2, w3, and w4 are determined through multiple experiments. Finally, the appropriate values ​​are calculated based on the cost function.

[0186] Individuals are selected for regeneration based on fitness; those with lower fitness values ​​are more likely to be selected, while those with higher fitness values ​​may be eliminated.

[0187] The crossover and mutation probabilities of the adaptive genetic algorithm are determined according to the following formula:

[0188]

[0189] P c Let P be the crossover probability. m f is the mutation probability. max It is the maximum fitness value within the population; f avg is the average fitness value within the population; f is the larger fitness value of the two individuals to be crossovered; f' is the fitness value of the individual to be mutated. k1, k2, k3 are arbitrary constants.

[0190] Then, based on the calculated crossover and mutation probabilities, crossover and mutation are performed to generate new individuals. Finally, the fitness value of each individual is checked to see if it meets the requirements; if so, the iteration stops.

[0191] In this embodiment, to obtain a waveform set with good orthogonality, a cost function is designed using the minimization of peak sidelobes. An optimization criterion is set, and the fitness of each individual in the frequency sequence group matrix is ​​calculated. If all individuals meet the optimization criterion, the frequency sequence group is output; otherwise, optimization continues. Then, search parameters are determined according to the adaptive genetic algorithm formula. Crossover and mutation are continuously performed to generate a new population. The fitness of individuals is then evaluated again until the optimization condition is met or the number of iterations is reached, resulting in a frequency sequence group with good orthogonality.

[0192] The following is a simulation example of the transmission waveform of a MIMO array ground penetrating radar system, and its performance is analyzed.

[0193] Table 1: System Configuration Parameters

[0194]

[0195]

[0196] This invention first utilizes frequency sequence coding groups to improve the iteration speed of optimized individuals, saving computation time. In contrast, standard genetic algorithms require optimization of each frequency code as an individual, and each frequency code needs to be converted to multiple binary codes, resulting in excessively long computation times. Then, an adaptive multi-mutation point genetic algorithm is used for optimization, making it more suitable for the practical application requirements of ground-penetrating radar, significantly improving the system's target detection capability and reducing system operating time.

[0197] The ground-penetrating radar signal design algorithm was simulated 50 times, and the average value was selected as the result. Numerical analysis of using chaotic mapping alone and using the improved genetic algorithm alone is also presented.

[0198] Table 2: Comparison of the effects of using chaotic mapping alone, using genetic algorithm alone, and the adaptive multi-mutation point genetic algorithm based on chaotic mapping in this invention; comparison of autocorrelation peak sidelobes and cross-correlation sidelobes.

[0199]

[0200]

[0201] As shown in Table 2, the autocorrelation sidelobe peak value (ASP) and cross-correlation peak value (CP) of the orthogonal discrete frequency coded signal designed using the method of this invention are both improved. Specifically, the maximum autocorrelation sidelobe peak value is improved by 4.54 dB compared to the traditional algorithm, and the cross-correlation peak value is improved by 14.07 dB. The average autocorrelation sidelobe peak value is improved by 3.19 dB, and the average cross-correlation peak value is improved by 11.85 dB.

[0202] Referring to Figures 4, 5, and 6, it can be seen that using the frequency sequence generated by chaotic mapping as the initial population and optimizing it with an adaptive genetic algorithm still demonstrates good adaptability under large-scale signal conditions. Furthermore, compared to simply generating signals using chaotic sequences, its autocorrelation and cross-correlation performance are superior. Therefore, this signal design method is suitable for use with array-type ground-penetrating radar.

[0203] Referring to Figure 7, it can be seen that the ambiguity function of the signal is thumbtack shaped, thus it has good autocorrelation performance, which is beneficial to improving the target detection capability.

[0204] Referring to Figure 8, it can be seen that the iterative change time curve of the signal design method shows that the algorithm converges to the optimal fitness at approximately the 45th generation. This proves that the optimization algorithm can achieve fast and robust design of large-scale signals, saving computational resources and improving the iteration speed while ensuring good correlation performance.

[0205] This invention provides a method for designing and generating waveforms for orthogonal MIMO ground-penetrating radar (GPR) in heterogeneous regions of highways. Suitable for high-bandwidth GPR applications, it can rapidly and robustly generate waveforms with relatively long code lengths. Compared to traditional statistical optimization algorithms, it uses chaotic mapping to generate the initial population, significantly reducing the search space and saving computational resources. Furthermore, the adaptive genetic algorithm is better suited to the design requirements of different bandwidth transmission waveform sets due to varying detection depths. Compared to existing technologies, this invention also has the following advantages;

[0206] 1. Stepped-frequency MIMO antenna arrays enable high-speed, multi-channel data acquisition. Introducing MIMO arrays into stepped-frequency ground-penetrating radars (GPR) enables rapid acquisition of data from multiple sparse arrays at multiple measurement points. This provides technical support for achieving high-resolution, high-speed acquisition in GPRs on the market and solves the problem of low resolution caused by single-point acquisition in traditional stepped-frequency systems.

[0207] 2. Rapidly generate orthogonal MIMO transmit waveform sets with longer code lengths. Using chaotic mapping to generate initial low PSLR frequency coding sequences and using them as the initial population significantly improves the convergence speed of the genetic algorithm, enhances its global search capability, and yields transmit waveforms with low sidelobe orthogonality.

[0208] 3. Generates higher-quality orthogonal discrete frequency coded waveform sets more stably. By utilizing an adaptive genetic algorithm to adaptively adjust search parameters during the iteration process, local optima are avoided, resulting in better solutions and improved convergence speed.

[0209] Referring to Figure 9, this application embodiment also provides a ground-penetrating radar control device, the device comprising:

[0210] Chaotic mapping module 11 is used to generate a frequency sequence group matrix that meets the preset requirements of ground penetrating radar using chaotic mapping;

[0211] Optimization module 12 is used to optimize the frequency sequence group matrix according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set;

[0212] The transmitting module 13 is used to transmit waveforms to the ground based on the orthogonal discrete frequency encoded waveform set, and to call the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar, and to receive reflected waveforms.

[0213] Analysis module 14 is used to analyze and process the reflected waveform to obtain the ground exploration results.

[0214] As described above, it is understood that each component of the ground-penetrating radar control device proposed in this application can realize the function of any of the ground-penetrating radar control methods described above, and the specific structure will not be described in detail.

[0215] Referring to Figure 10, this embodiment of the application also provides a ground-penetrating radar, the internal structure of which is shown in Figure 10. The ground-penetrating radar includes a processor and a memory connected via a system bus. The processor in this ground-penetrating radar is designed to provide computing and control capabilities. The memory of the ground-penetrating radar includes a storage medium and internal memory. The storage medium stores an operating system, computer programs, and a database. The memory provides an environment for the execution of the computer programs in the storage medium. When the computer program is executed by the processor, it implements a ground-penetrating radar control method.

[0216] The processor described above executes the ground-penetrating radar control method described above, the method comprising:

[0217] A frequency sequence matrix that meets the preset requirements of ground penetrating radar is generated using chaotic mapping.

[0218] The frequency sequence group matrix is ​​optimized according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set;

[0219] Based on the orthogonal discrete frequency encoded transmitted waveform set, the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar are invoked to transmit waveforms to the ground and receive reflected waveforms.

[0220] The reflected waveform is analyzed and processed to obtain the ground exploration results.

[0221] In one embodiment of this application, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it implements a ground-penetrating radar control method, the method comprising:

[0222] A frequency sequence matrix that meets the preset requirements of ground penetrating radar is generated using chaotic mapping.

[0223] The frequency sequence group matrix is ​​optimized according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set;

[0224] Based on the orthogonal discrete frequency encoded transmitted waveform set, the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar are invoked to transmit waveforms to the ground and receive reflected waveforms.

[0225] The reflected waveform is analyzed and processed to obtain the ground exploration results.

[0226] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media provided in this application and used in the embodiments 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. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0227] In summary, the greatest benefit of this application is that:

[0228] This application provides a ground-penetrating radar (GPR) control method, apparatus, device, and storage medium. It utilizes chaotic mapping to generate a frequency sequence matrix that meets the preset requirements of the GPR. The frequency sequence matrix is ​​then optimized using a preset genetic algorithm to obtain an orthogonal discrete frequency-coded transmitted waveform set. Based on this set, the GPR's dual-channel narrowband / wideband transceiver and heterogeneous system-on-a-chip transmit waveforms to the ground and receive reflected waveforms. The reflected waveforms are analyzed and processed to obtain ground-penetrating results, thereby improving work efficiency, meeting the requirements of high-speed operation, and enhancing radar detection accuracy. Furthermore, it offers unique advantages in spectrum analysis and interference suppression, achieving a balance between detection depth and resolution without requiring complex signal processing techniques. The signal optimization design method involved in this invention uses a chaotic mapping frequency sequence matrix as the initial population for the optimization algorithm and employs an adaptive genetic algorithm for optimization, significantly improving the convergence speed of the genetic algorithm, enhancing its global search capability, and obtaining transmitted waveforms with low sidelobes and good orthogonality.

[0229] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0230] The above description is only a preferred embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural changes made based on the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A ground-penetrating radar control method, characterized in that, include: A frequency sequence group matrix that meets the preset requirements of ground penetrating radar is generated by using chaotic mapping. The ground penetrating radar includes an array-type MIMO ground penetrating radar. The frequency sequence group matrix is ​​optimized according to a preset genetic algorithm to obtain an orthogonal discrete frequency coded transmission waveform set. Based on the orthogonal discrete frequency coded transmission waveform set, the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar are invoked to transmit waveforms to the ground and receive reflected waveforms. The reflected waveforms are analyzed and processed to obtain ground penetrating results. The step of optimizing the frequency sequence group matrix according to the preset genetic algorithm to obtain the orthogonal discrete frequency coded transmission waveform set includes: calculating the fitness of the frequency sequence group matrix according to a pre-constructed cost function, wherein the cost function is established using the peak sidelobe minimization criterion; determining whether the fitness of the frequency sequence group matrix is ​​greater than a preset fitness; if so, determining whether the frequency sequence group matrix conforms to a preset optimization rule; if it conforms, the frequency sequence group matrix is ​​taken as the optimal frequency sequence group matrix to obtain the orthogonal discrete frequency coded transmission waveform set.

2. The method according to claim 1, characterized in that, The step of generating a frequency sequence group matrix that meets the preset requirements of ground penetrating radar using chaotic mapping includes: generating a chaotic sequence using chaotic mapping; and generating a frequency sequence group matrix that meets the preset requirements of ground penetrating radar based on the chaotic sequence and according to the mapping relationship.

3. The method according to claim 2, characterized in that, The method of generating chaotic sequences using chaotic mapping includes: obtaining the detection mission requirements of ground penetrating radar; determining the antenna frequency and setting an initial value based on the detection mission requirements; and generating multiple sets of chaotic sequences using chaotic mapping based on the antenna frequency and the initial value.

4. The method according to claim 3, characterized in that, The step of generating a frequency sequence group matrix that meets the preset requirements of ground-penetrating radar based on the chaotic sequence and the mapping relationship includes: selecting M chaotic sequences with a length equal to the target length from the multiple chaotic sequences to obtain a chaotic sequence sub-matrix; wherein M is a positive integer; performing frequency mapping on the chaotic sequence sub-matrix to obtain a frequency matrix; performing a Fourier transform on the frequency matrix using a pre-constructed orthogonal discrete frequency coded signal model to obtain an initial frequency sequence group matrix; calculating the peak-to-sidelobe ratio of the initial frequency sequence group matrix, and selecting Ψ initial frequency sequence group matrices of preset dimensions to form a frequency sequence group matrix based on the peak-to-sidelobe ratio; wherein Ψ is a positive integer.

5. The method according to claim 1, characterized in that, After determining whether the frequency sequence group matrix conforms to the preset optimization rules, the process further includes: if it does not conform, selecting the frequency sequence group matrix with the highest fitness (ranked in the top W positions) as the parent of the next generation population, and eliminating the remaining frequency sequence group matrices; wherein, W is a positive integer; determining the crossover and mutation probabilities of the parent generation according to the adaptive genetic algorithm and the optimization rules; generating a new frequency sequence group matrix through crossover and mutation operations based on the crossover and mutation probabilities, and returning to execute the step of calculating the fitness of the frequency sequence group matrix according to the pre-constructed cost function, until the optimal frequency sequence group matrix is ​​output or the maximum number of iterations is reached.

6. The method according to claim 1, characterized in that, The ground-penetrating radar includes eleven transceiver antennas, which include two four-antenna array units and one three-antenna array unit. Each antenna array unit operates in a time-division manner. Specifically, the four-antenna array unit simultaneously triggers two transmitting and receiving elements and transmits in two separate transactions. The three-antenna array unit first simultaneously triggers two transmitting and receiving elements, and then triggers the last transmitting element.

7. A ground-penetrating radar control device, characterized in that, include: A chaotic mapping module is used to generate a frequency sequence group matrix that meets the preset requirements of a ground penetrating radar, including an array-type MIMO ground penetrating radar. An optimization module is used to optimize the frequency sequence group matrix according to a preset genetic algorithm to obtain an orthogonal discrete frequency-coded transmission waveform set. Specifically, it includes: calculating the fitness of the frequency sequence group matrix according to a pre-constructed cost function, wherein the cost function is established using the minimum peak sidelobe criterion; determining whether the fitness of the frequency sequence group matrix is ​​greater than a preset fitness; if so, determining whether the frequency sequence group matrix conforms to a preset optimization rule; if it does, taking the frequency sequence group matrix as the optimal frequency sequence group matrix to obtain an orthogonal discrete frequency-coded transmission waveform set; a transmission module is used to transmit waveforms to the ground by calling the dual-channel narrowband and broadband transceivers and heterogeneous system-on-a-chip of the ground penetrating radar based on the orthogonal discrete frequency-coded transmission waveform set, and receiving the reflected waveforms; and an analysis module is used to analyze and process the reflected waveforms to obtain ground penetrating results.

8. A ground-penetrating radar, characterized in that, include: processor; A memory; wherein the memory stores a computer program, and the processor executes the computer program to implement the ground-penetrating radar control method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the ground-penetrating radar control method according to any one of claims 1-6.

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