A time-frequency and spatial domain joint optimization method and system for integrated OTFS radar-communication signal processing

Abstract

This application provides a time-frequency and spatial domain joint optimization method and system for integrated OTFS radar-communication signal processing. Specifically, based on the time-varying characteristics and bandwidth of the channel, this application configures the position and density of pilot symbols in the OTFS time-frequency grid, sets the Doppler index range to optimize channel information acquisition, deploys a controllable reflector, constructs a phase modulation matrix based on the target position and communication channel parameters, dynamically adjusts the phase gradient direction, and separates the energy of the target echo and the communication signal. Within the set Doppler index range, frequency offset estimation is calculated, the time-domain sampling points of the received signal are corrected, and a phase correction vector is generated. The main spatial aliasing interference zone is located, and within this zone, the phase correction vector and sub-Doppler parameters are combined, and frequency-domain beamforming weighting and phase rotation compensation are used to suppress symbol interference and spatial aliasing caused by high-speed targets. This application achieves efficient time-frequency and spatial domain collaborative processing of OTFS radar-communication integrated signals.

Description

Technical Field

[0001] This application relates to the field of integrated wireless communication and radar sensing systems, and in particular to an OTFS radar communication integrated signal processing method and system with joint optimization in time, frequency and spatial domains. Background Technology

[0002] In sensing applications such as low-altitude UAV dynamic mapping, the high-speed maneuvering and non-line-of-sight propagation of the platform cause the wireless channel to exhibit strong non-stationary characteristics, specifically manifested as rapidly time-varying Doppler spread and multipath delay drift. These scenarios require an integrated signal processing solution that simultaneously performs target detection and data transmission, possessing strong robustness to overcome inter-symbol interference caused by time-varying channels and avoid mapping distortion caused by dense multipath interference at low altitudes.

[0003] Currently, a representative solution for this type of requirement is the OTFS joint processing method based on adaptive pilots. This method periodically deploys pilot symbols in the OTFS time-frequency grid, estimates the local Doppler frequency shift through a sliding window mechanism, and dynamically adjusts the pilot density based on the estimation results, increasing the pilot proportion in high-dynamic regions. Simultaneously, it uses a time-frequency dual-domain equalizer to compensate for linear phase shift and relies on a multi-antenna receiving array for static beamforming to suppress some spatial interference.

[0004] However, this existing solution has significant drawbacks. Its spatial processing relies on static beamforming of a fixed antenna array, which cannot actively control the signal propagation environment, resulting in persistent aliasing of dense multipath reflections at low altitudes, making effective separation difficult. In time-frequency domain processing, it can only compensate for linear phase shifts, lacking the ability to model and suppress nonlinear frequency shifts and space-time-varying coupling interference caused by high-speed maneuvering targets. Summary of the Invention

[0005] This application provides an OTFS radar communication integrated signal processing method and system with joint optimization in time, frequency and spatial domains, to solve the problem of trajectory breakage or false alarms in existing mapping technologies.

[0006] Firstly, this application provides an integrated OTFS radar-communication signal processing method with joint optimization in the time, frequency, and spatial domains, including:

[0007] Based on the time stability and bandwidth characteristics of the channel state, the position and density of pilot symbols are configured in the signal time-frequency domain grid. Based on the position and density of the pilot symbols, the Doppler index range is set to form pilot distribution parameters to optimize the efficiency of channel state information acquisition.

[0008] A controllable reflector is deployed, and a phase modulation matrix is ​​constructed based on the target's spatial location and communication link channel parameters. The phase gradient direction of the phase modulation matrix is ​​dynamically adjusted according to the Doppler frequency shift polarity of the target's motion direction to separate the energy distribution of the target echo and the communication signal on the propagation path.

[0009] Within the Doppler index range, a frequency offset estimate is calculated using the phase difference of the pilot symbols. Based on the frequency offset estimate, the time-domain sampling points of the received signal are corrected to eliminate the frequency-domain linear phase deviation. Based on the corrected pilot symbols, the multipath delay parameters and sub-Doppler frequency shift parameters of the dynamic channel are reconstructed to generate a phase correction vector.

[0010] Based on the reconstructed multipath delay parameters, the main beam interference region of the spatial aliasing signal is located. Within the main beam interference region, the phase correction vector and sub-Doppler frequency shift parameters are used to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling.

[0011] Optionally, a controllable reflector is deployed, and a phase modulation matrix is ​​constructed based on the target's spatial location and communication link channel parameters. The phase gradient direction of the phase modulation matrix is ​​dynamically adjusted according to the Doppler frequency shift polarity of the target's motion direction to separate the energy distribution of the target echo and the communication signal along the propagation path, including:

[0012] Deploy a controllable reflective surface array, construct a phase modulation matrix based on the target's spatial position and communication link channel parameters, obtain the target's azimuth and elevation angles in the spatial coordinate system, and calculate the position phase difference of each unit in the controllable reflective surface array based on the azimuth and elevation angles.

[0013] Based on the position phase difference, the path loss coefficient is extracted from the communication link channel parameters, and the initial phase gradient step size of the phase modulation matrix is ​​derived using the path loss coefficient.

[0014] Based on the initial phase gradient step size, the Doppler frequency shift polarity of the target's motion direction is detected. If the Doppler frequency shift polarity is positive, the phase gradient direction is set to match the positive azimuth direction of the spatial coordinate system. If the Doppler frequency shift polarity is negative, the phase gradient direction is set to match the negative azimuth direction of the spatial coordinate system.

[0015] Based on the phase gradient direction, the initial phase gradient step size is multiplied by the phase gradient direction to synthesize the phase value of each unit of the controllable reflective surface array, and based on the phase value, the energy distribution of the target echo and the communication signal on the propagation path is separated.

[0016] Optionally, based on the reconstructed multipath delay parameters, the main beam interference region of the spatial aliasing signal is located. Within the main beam interference region, using the phase correction vector and sub-Doppler frequency shift parameters, beamforming weighting and phase rotation compensation are performed on the signal in the frequency domain to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling, including:

[0017] Based on the reconstructed multipath delay parameters, the energy distribution of the spatial spectrum is scanned, and the main beam interference region of the spatial aliasing signal is located based on the energy distribution;

[0018] Within the main beam interference zone, the phase correction vector is applied to the frequency domain subcarrier index to obtain the shaping weighting coefficient of the frequency domain beam, and the sub-Doppler frequency shift parameter is applied to the frequency domain sampling point index to generate the phase rotation compensation amount.

[0019] The superposition of the shaping weighting coefficients and the phase rotation compensation amount suppresses inter-symbol interference and spatial path aliasing caused by high-speed targets, realizes spatial beam focusing and time-frequency symbol decoupling, obtains the compensated frequency domain signal, and converts the compensated frequency domain signal to the time-delay Doppler domain to complete the separation operation.

[0020] Optionally, within the Doppler index range, a frequency offset estimate is calculated using the phase difference of the pilot symbols. Based on this frequency offset estimate, the time-domain sampling points of the received signal are corrected to eliminate linear phase deviation in the frequency domain. Then, based on the corrected pilot symbols, the multipath delay parameters and sub-Doppler frequency shift parameters of the dynamic channel are reconstructed to generate a phase correction vector, including:

[0021] Within the Doppler index range, two adjacent pilot symbols are selected, the phase difference between the two adjacent pilot symbols is calculated, and the frequency offset estimate is determined by combining the time interval between the two adjacent pilot symbols.

[0022] Based on the frequency offset estimate, phase correction is performed on the time-domain sampling points of the received signal. Using the corrected pilot symbols, the correlation peak amplitude of different delay indices is analyzed, and the multipath delay parameters of the dynamic channel are reconstructed based on the correlation peak amplitude.

[0023] At the time delay index corresponding to the multipath time delay parameter, the phase change rate within the Doppler index range is solved, and the sub-Doppler frequency shift parameter is reconstructed based on the phase change rate;

[0024] The reconstructed multipath delay parameters and the sub-Doppler frequency shift parameters are fused to generate a phase correction vector.

[0025] Optionally, based on the time stability and bandwidth characteristics of the channel state, the position and density of pilot symbols are configured in the signal time-frequency domain grid. Based on the position and density of the pilot symbols, a Doppler index range is set to form pilot distribution parameters to optimize the channel state information acquisition efficiency, including:

[0026] Based on the time stability and bandwidth characteristics of the channel state, the total number of rows and columns of the time-frequency domain grid of the signal are determined by extracting the duration and bandwidth parameters of the integrated signal.

[0027] Based on the total number of rows and columns, and combined with the maximum Doppler frequency shift range of the target motion, positive and negative regions are divided within the Doppler index range;

[0028] Within the positive and negative regions, the position coordinates and density distribution of the pilot symbols are configured according to the ratio of the total number of rows to the total number of columns;

[0029] Based on the position coordinates and density distribution of the pilot symbols, the upper and lower limits of the Doppler index range are set, and a mapping relationship is established with the Doppler channel index of the radar signal.

[0030] By integrating the position coordinates and density distribution of the pilot symbols with the mapping relationship, pilot distribution parameters are generated to optimize the efficiency of channel state information acquisition.

[0031] Optionally, the shaping weighting coefficients and the phase rotation compensation are superimposed to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling to obtain a compensated frequency domain signal. The compensated frequency domain signal is then converted to the time-delay Doppler domain to complete the separation operation, including:

[0032] The shaping weighting coefficients are applied to the signal components corresponding to the frequency domain subcarrier index to generate a first set of adjustment components. Each unit of the first set of adjustment components is associated with the focusing direction of the space beam.

[0033] The phase rotation compensation amount is mapped to the signal component corresponding to the frequency domain sampling point index to generate a second set of adjustment components. Each unit of the second set of adjustment components is associated with the symbol-decoupled phase correction.

[0034] The first group of adjustment components and the second group of adjustment components are merged to generate a merged signal component. In the merging operation, the merged signal component of each frequency domain sampling point index is formed by superimposing the first group of adjustment components and the second group of adjustment components with the same index.

[0035] Based on the merged signal components, the frequency domain subcarrier index and frequency domain sampling point index are converted to the time delay index and Doppler index, and the time delay Doppler domain signal is output to complete the separation operation of the target echo and the communication signal.

[0036] Optionally, based on the initial phase gradient step size, the Doppler frequency shift polarity of the target motion direction is detected. If the Doppler frequency shift polarity is positive, the phase gradient direction is set to match the positive azimuth direction of the spatial coordinate system; if the Doppler frequency shift polarity is negative, the phase gradient direction is set to match the negative azimuth direction of the spatial coordinate system. This includes:

[0037] Using the initial phase gradient step size as an input parameter, a spectrum analysis is performed on the target motion direction to obtain the frequency shift characteristics in the spectrum analysis results;

[0038] Based on the comparison between the frequency offset feature and the preset center frequency, if the frequency offset feature is higher than the preset center frequency, the polarity of the Doppler frequency shift is determined to be positive; if the frequency offset feature is lower than the preset center frequency, the polarity of the Doppler frequency shift is determined to be negative.

[0039] When the polarity of the Doppler frequency shift is positive, the phase gradient direction is assigned a unit vector in the positive direction of the azimuth angle of the spatial coordinate system; when the polarity of the Doppler frequency shift is negative, the phase gradient direction is assigned a unit vector in the negative direction of the azimuth angle of the spatial coordinate system.

[0040] The phase gradient direction is output as the input parameter for synthesizing the phase values ​​of each unit in the controllable reflective surface array.

[0041] Secondly, this application provides an integrated OTFS radar-communication signal processing system with joint time-frequency and spatial domain optimization, comprising:

[0042] The optimization module is used to configure the position and density of pilot symbols in the signal time-frequency domain grid according to the time stability and bandwidth characteristics of the channel state, and to set the Doppler index range based on the position and density of the pilot symbols to form pilot distribution parameters to optimize the efficiency of channel state information acquisition.

[0043] The separation module is used to deploy a controllable reflector, construct a phase modulation matrix based on the target's spatial location and communication link channel parameters, and dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target's motion direction to separate the energy distribution of the target echo and the communication signal on the propagation path.

[0044] The reconstruction module is used to calculate the frequency offset estimate by the phase difference of the pilot symbols within the Doppler index range, correct the time-domain sampling points of the received signal based on the frequency offset estimate, eliminate the frequency-domain linear phase deviation, and reconstruct the multipath delay parameters and sub-Doppler frequency shift parameters of the dynamic channel based on the corrected pilot symbols to generate a phase correction vector.

[0045] The correction module is used to locate the main beam interference region of the spatial aliasing signal based on the reconstructed multipath delay parameters. Within the main beam interference region, the phase correction vector and sub-Doppler frequency shift parameters are used to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling.

[0046] Thirdly, this application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are to be invoked and executed by the processing component to implement the OTFS radar-communication integrated signal processing method with joint optimization of time, frequency and spatial domain as described in the first aspect above.

[0047] Fourthly, this application provides a computer storage medium storing a computer program, which, when executed by a computer, implements the OTFS radar-communication integrated signal processing method with joint optimization of time, frequency, and spatial domain as described in the first aspect.

[0048] This application dynamically configures the spatial location and distribution density of pilot symbols in the OTFS time-frequency domain grid based on the time-varying stability and bandwidth characteristics of the channel, and sets the Doppler index range accordingly to form optimized pilot distribution parameters. This significantly improves the efficiency of acquiring time-varying channel state information and avoids the resource consumption of invalid frequency domain scanning. Secondly, by deploying a controllable reflector and constructing a phase modulation matrix in combination with the target spatial coordinates and communication link channel parameters, the phase gradient direction of this matrix is ​​dynamically adjusted based on the Doppler frequency shift polarity of the target's motion direction to actively guide the propagation path of electromagnetic wave energy and physically separate the aliased energy distribution of the target reflected echo and the communication signal. Subsequently, within the preset Doppler index range, the frequency offset estimate is calculated using the phase difference between adjacent pilot symbols to correct the time-domain sampling points of the received signal, completely eliminating the frequency domain linear phase deviation caused by channel time-varying. At the same time, based on the multipath delay parameters and fine-grained Doppler frequency shift parameters of the reconstructed dynamic channel after correction, a high-precision phase correction vector is generated. Finally, based on the reconstructed multipath delay parameters, the main beam interference region of the spatial aliasing signal is located. Within this region, the phase correction vector and sub-Doppler parameters are fused, and beamforming weighting and phase rotation compensation operations are performed in the frequency domain. This simultaneously suppresses inter-symbol interference and spatial multipath aliasing caused by high-speed target motion, achieving precise focusing of the energy beam in the spatial dimension and decoupling of the signal symbols in the time and frequency domains.

[0049] Furthermore, based on the target's azimuth and elevation angle parameters in the three-dimensional spatial coordinate system, the positional phase difference between each unit of the reflector is accurately calculated, providing a geometric basis for spatial modeling of the phase gradient and ensuring the spatial pointing accuracy of beam control. Subsequently, the path loss coefficient is extracted from the communication link channel parameters, and the initial gradient step size of the phase modulation matrix is ​​derived based on this physical characteristic. The energy attenuation characteristics in wireless propagation are incorporated into the phase design to optimize the energy utilization of the reflector. The Doppler frequency shift polarity characteristics of the target's motion direction are further detected: when the frequency shift polarity is positive, the phase gradient direction is synchronously set to the positive direction of the azimuth angle in the spatial coordinate system; when the frequency shift polarity is negative, it is switched to the negative azimuth direction, establishing a dynamic matching mechanism between motion trend and phase control, enhancing the directional separation capability of the target echo signal. Finally, by combining the calculated initial gradient step size and dynamic gradient direction, the independent phase value of each unit in the controllable reflective surface array is synthesized by vector multiplication. The electromagnetic wavefront is reconstructed in a spatial coherent superposition manner, which forces the target reflected signal and the communication downlink signal to form a distinguishable energy distribution region on the propagation path, thus solving the aliasing interference problem from the physical transmission level.

[0050] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 A flowchart of an OTFS radar-communication integrated signal processing method with joint optimization in the time-frequency and spatial domains provided in this application is shown.

[0053] Figure 2 A scene diagram is shown, illustrating an OTFS radar-communication integrated signal processing method that utilizes joint optimization in the time-frequency and spatial domains, as provided in this application.

[0054] Figure 3 This paper presents a schematic diagram of the structure of an OTFS radar-communication integrated signal processing system with joint optimization in the time-frequency and spatial domains provided in this application.

[0055] Figure 4 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0056] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0057] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0058] Researchers have discovered significant limitations in existing OTFS radar-communication integrated signal processing methods. Their spatial processing relies on static beamforming from fixed antenna arrays, failing to actively control signal propagation paths in complex environments. This results in persistent aliasing of low-altitude dense multipath reflections in the spatial dimension, making effective separation difficult. Furthermore, time-frequency domain processing can only compensate for linear phase shifts, lacking effective modeling and suppression capabilities for nonlinear frequency offsets, inter-symbol interference, and space-time-varying coupling interference caused by high-speed maneuvering targets. Therefore, a joint optimization signal processing method is urgently needed that deeply integrates time, frequency, and spatial domain characteristics to actively sense and adaptively control dynamic environments, significantly improving the accuracy of high-speed target detection and communication reliability.

[0059] To address the aforementioned problems, this invention proposes an integrated OTFS radar-communication signal processing method with joint time-frequency and spatial domain optimization. Its core lies in actively controlling the spatial characteristics of signal propagation through a dynamic intelligent reflector, combined with pilot parameter optimization and adaptive time-frequency compensation techniques, to achieve coordinated processing of spatial beam focusing, multipath separation, and time-frequency interference suppression. Specifically, the method first optimizes the position and density of pilot symbols to accurately define the Doppler index range for efficient acquisition of channel state information. Next, it deploys and dynamically controls the phase gradient of the controllable reflector to actively separate the spatial energy distribution of the target echo and the communication signal. Based on this, within the optimized Doppler index range, it uses the pilot phase difference for fine frequency offset estimation and correction, accurately reconstructing the channel's multipath delay and sub-Doppler frequency shift parameters and generating a phase correction vector. Finally, by integrating spatial domain phase control information, the phase correction vector, and the reconstructed parameters, it performs frequency domain beamforming and phase rotation compensation operations in the main beam interference zone. This method successfully solves the core problems in the background technology: by dynamically adjusting the reflector, it overcomes the limitations of static beamforming and actively separates the multipath signal energy of spatial aliasing; by refining the time-frequency domain parameter reconstruction and adaptive correction, it effectively suppresses nonlinear frequency offset, inter-symbol interference and complex space-time-varying coupling interference caused by high-speed maneuvering targets, thereby significantly improving the performance of target detection and communication transmission in complex dynamic environments.

[0060] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0061] Figure 1 A flowchart of an OTFS radar-communication integrated signal processing method with joint optimization in the time-frequency and spatial domains is provided in this application embodiment, as shown below. Figure 1 As shown, the method includes:

[0062] 101. Based on the time stability and bandwidth characteristics of the channel state, configure the position and density of pilot symbols in the signal time-frequency domain grid, and set the Doppler index range based on the position and density of the pilot symbols to form pilot distribution parameters to optimize the efficiency of channel state information acquisition.

[0063] Optionally, step 101 may specifically include the following steps:

[0064] 1011. Based on the time stability and bandwidth characteristics of the channel state, the total number of rows and columns of the time-frequency domain grid of the signal are determined by extracting the duration and bandwidth parameters of the integrated signal;

[0065] 1012. Based on the total number of rows and columns, and combined with the maximum Doppler frequency shift range of the target motion, divide the Doppler index range into positive and negative regions;

[0066] 1013. Within the positive and negative regions, the position coordinates and density distribution of the pilot symbols are configured according to the ratio of the total number of rows to the total number of columns;

[0067] 1014. Based on the position coordinates and density distribution of the pilot symbols, set the upper and lower limits of the Doppler index range, and establish a mapping relationship with the Doppler channel index of the radar signal;

[0068] 1015. Integrate the position coordinates and density distribution of the pilot symbols and the mapping relationship to generate pilot distribution parameters to optimize the efficiency of channel state information acquisition.

[0069] In the above steps, the time stability of the channel state refers to the degree to which the signal changes slowly in the time dimension, that is, the duration for which the channel state remains relatively constant; the bandwidth characteristic of the channel state refers to the width of the frequency range occupied by the signal in the frequency domain, representing the size of the frequency band occupied by the signal; the signal time-frequency domain grid is a grid-like structure divided in the time and frequency directions after the signal is discretized, used to identify the distribution of the signal's sampling points; the position and density of pilot symbols refer to the predefined coordinates of known symbols used to assist channel estimation and the distribution density within a unit area in the signal time-frequency domain grid. The position coordinates specify the row and column positions of the symbols in the grid, and the density distribution describes the proportion of pilot symbols in a unit grid area; the Doppler index range is the range of frequency offset index values ​​set based on the Doppler effect, which is caused by the relative motion between the target and the receiver. The offset phenomenon is defined by the quantized index value covering the frequency offset. The positive and negative regions are two sub-regions within the Doppler index range, based on the sign of the Doppler frequency shift. The positive region corresponds to the index region where the frequency decreases as the target moves away from the receiver, while the negative region corresponds to the index region where the frequency increases as the target moves closer. Position coordinates and density distribution are specified parameters indicating the exact position coordinates and density of the pilot symbols. The upper and lower limits of the Doppler index range define the maximum and minimum allowable values ​​of the index. The mapping relationship establishes a correspondence between the Doppler index and the radar signal Doppler channel index, enabling mutual conversion and mapping. The pilot distribution parameters are a set of parameters integrating the above elements, including position coordinate density distribution and mapping relationships, used to optimize the acquisition efficiency of channel state information, ensuring a more accurate and efficient acquisition process.

[0070] In this embodiment, firstly, step 1011 extracts the signal's duration and bandwidth parameters based on the channel's time stability and bandwidth characteristics. The duration is the total duration of the signal, and the bandwidth is the width of the signal's frequency range in the frequency domain. Next, based on these parameters, the total number of rows and columns in the signal's time-frequency domain grid are calculated: the total number of rows corresponds to the frequency domain direction and is obtained by dividing the bandwidth by the frequency resolution; the total number of columns corresponds to the time domain direction and is obtained by multiplying the duration by the sampling rate. The frequency resolution and sampling rate are preset values ​​by the system or basic values ​​obtained from signal analysis. For example, in an automotive radar scenario, assuming the signal duration is 10 milliseconds, the bandwidth is 20 MHz, the sampling rate is set to 40 MHz, and the frequency resolution is set to 0.5 MHz, then the total number of rows is calculated as bandwidth divided by the frequency resolution (20 MHz divided by 0.5 MHz), equaling 40 rows; the total number of columns is calculated as duration multiplied by the sampling rate (10 milliseconds multiplied by 40 MHz), equaling 400 time samples. These calculations ensure that the grid accurately covers the signal's time-frequency characteristics. Finally, the total number of rows and columns are output as the basic parameters for subsequent steps.

[0071] Secondly, in step 1012, based on the total number of rows and columns output in step 1011, and combined with the maximum Doppler frequency shift range of the target motion, positive and negative regions are divided within the Doppler index range. The maximum Doppler frequency shift range is calculated from the target's maximum velocity carrier frequency and the speed of light, using the following formula: ,in Indicates the target's maximum speed. It is the carrier frequency. It is the speed of light; the index range is mapped to the index value based on the total number of rows and columns, and the index value is calculated with frequency resolution by removing Doppler frequencies, using the formula: ,in It is an index value. This refers to frequency resolution. For example, setting the target's maximum speed to 100 meters per second, with a carrier frequency of 5 gigahertz, and the speed of light being 3 x 10^8 meters per second, the frequency resolution is 0.5 megahertz; the maximum Doppler shift... Calculated as The upper limit of the index is calculated as follows: Divide by That is, 3333 Hz divided by 0.5 and multiplied by 10 to the power of 6 (converting to the same units) equals 6.666, which is rounded to 7; the lower limit of the index is -7; the total index range is set from -7 to 7, dividing the positive region into 0 to 7 and the negative region into -7 to -1. This step outputs the boundaries of the divided regions. Finally, the starting points of the index values ​​for the positive and negative regions are output for subsequent configuration of pilot distribution.

[0072] Then, in step 1013, within the positive and negative regions defined in step 1012, the position coordinates and density distribution of pilot symbols are configured according to the ratio of the total number of rows to the total number of columns. The ratio refers to the relative size of the total number of rows and columns used to determine the grid cell allocation within the region; the position coordinates specify the exact points of the pilot symbols in the rows and columns; and the density distribution sets the number density of pilot symbols within a unit grid region. Coordinate values ​​are generated within the region using a uniform or proportionally random distribution algorithm; for example, uniform distribution ensures balanced symbol spacing. For example, assuming a total of 40 rows and 400 columns, the positive region indexes 0 to 7 correspond to the frequency domain row indices 8 to 15, and the negative region -7 to -1 corresponds to the row indices -8 to -2. The ratio is reflected in the positive region occupying 50% of the index range and the negative region occupying 50%. Within the positive region, the density distribution is set to one pilot every 10 rows, and the position coordinates are generated using grid coordinates, such as setting one pilot symbol at row 8, column 100. In the specific configuration, there are 8 rows from index 8 to 15, with a total of 32 grid cells. Assuming 10 points per row, the density is one pilot per cell, i.e., set at positions such as row 8, column 100, row 9, column 110, etc. Output the list of pilot position coordinates and density distribution values.

[0073] Next, in step 1014, based on the pilot symbol position coordinates and density distribution output in step 1013, the upper and lower limits of the Doppler index range are set, and a mapping relationship is established with the Doppler channel index of the radar signal. The upper and lower limits are calculated based on the frequency domain range covered by the pilot position, ensuring coverage of all index areas. The mapping relationship is implemented through a lookup table or function association, directly mapping the Doppler index value to the channel index value of the radar signal. For example, the radar Doppler channel index increases from 1. For instance, if the pilot position coordinates cover an index from -7 to 7, the upper limit is set to 7 and the lower limit to -7. Assuming the radar signal Doppler channel index has 15 channel index values ​​from 1 to 15, a mapping relationship is established, such as index value 0 corresponding to channel 1, index value 1 corresponding to channel 2, etc., and the mapping table is output. During processing, it is ensured that the upper and lower limits do not exceed the maximum channel index range of the radar when set. The upper and lower limits and the mapping table are output.

[0074] Finally, step 1015 integrates the pilot symbol position coordinates, density distribution, and upper and lower bounds of the mapping relationship parameters to generate optimized pilot distribution parameters. The integration process includes packaging all parameters into a structured collection file and verifying whether the parameters cover the channel state information acquisition requirements, such as through simulation testing to see if the parameters can reduce noise interference. For example, the position coordinates are a list of coordinates in rows 8 and columns 100, rows 9 and columns 110, etc.; the density distribution has one symbol per unit; the upper bound is 7; the lower bound is -7; and the mapping table index 0 corresponds to channel 1. The parameters are packaged into a parameter file such as XML or JSON. Optimized acquisition efficiency is reflected in these parameters enabling the radar system to quickly acquire target dynamics and reducing the error rate by 20%. The final output is the pilot distribution parameter file.

[0075] In practical applications, within a certain communication system, this system processes the wireless signal transmission process to optimize signal measurement. First, based on the characteristics of the signal transmission channel's state changes, such as its stability over time and the signal's bandwidth (frequency range), specific parameters of the integrated signal are extracted: for example, the signal duration is 100 milliseconds, and the bandwidth is 50 kHz. The time interval unit is set to 2 milliseconds per time point; therefore, the total number of rows in the signal's time-frequency domain grid is calculated as: Total number of rows = Duration / Time interval unit = 100ms / 2ms = 50. The frequency interval unit is set to 1 kHz per frequency point; therefore, the total number of columns (frequency direction) is calculated as: Total number of columns = Bandwidth / Frequency interval unit = 50kHz / 1kHz = 50. Next, based on the total number of rows and columns of 50, and combined with the maximum frequency offset range caused by the target movement, we set it to 200 Hz. Within the index range of the frequency offset, the index value represents the magnitude of the frequency offset, assuming it is from -100 to 100 with a step size of 1. We divide the positive region into an index range from 1 to 100 and a negative region into an index range from -100 to 0. Then, within the positive and negative regions, pilot symbols are configured based on the ratio of the total number of rows to the total number of columns (50 rows divided by 50 columns, with a ratio of 1). These symbols serve as the position coordinates and distribution density of reference points for signal measurement. For example, in the positive region, indices from 1 to 100 are set to the coordinates of the 10th time row and 10th frequency column, the 20th time row and 20th frequency column, etc., with one pilot placed every 10 points, at a density of one per 10 index units. In the negative region, indices from -100 to 0 are set to the coordinates of the -10th time row and -10th frequency column, the -20th time row and -20th frequency column, etc., with the same density. Based on this, the upper limit of the frequency offset index range is set to 100 (maximum value) and the lower limit to -100 (minimum value), and a mapping relationship is established with the Doppler channel indices of the radar signal. For example, index values ​​are mapped to channel sequence numbers, such as channel 1 corresponding to index 1, channel 2 corresponding to index 2, etc. Finally, by integrating the position coordinate distribution density and index mapping relationship of pilot symbols, pilot distribution parameters are generated to optimize the acquisition efficiency of channel state information, making signal measurement more accurate and reliable.

[0076] In the overall scheme of step 101 above, the time-frequency distribution coordinates and density values ​​of pilot symbols are accurately configured based on the time stability and bandwidth characteristics of the channel state. The total dimension of the time-frequency domain grid is dynamically set by extracting the duration and bandwidth parameters of the integrated signal. The Doppler index range is intelligently divided into positive and negative bidirectional regions by combining the target's maximum Doppler frequency shift. The pilot position and density distribution are adaptively adjusted within the region according to the grid row and column ratio. Then, precise Doppler index boundary values ​​are set and bidirectional mapping association is established with the radar Doppler channel index, thereby forming highly coordinated pilot distribution parameters. This significantly improves the acquisition accuracy and timeliness of channel state information, effectively reduces pilot overhead, and enhances the robustness of channel estimation in high-speed mobile scenarios. Ultimately, it achieves comprehensive optimization of the resource utilization efficiency of the integrated communication and sensing system.

[0077] 102. Deploy a controllable reflector, construct a phase modulation matrix based on the target's spatial location and communication link channel parameters, and dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target's motion direction to separate the energy distribution of the target echo and the communication signal on the propagation path.

[0078] Optionally, step 102 may specifically include the following steps:

[0079] 1021. Deploy a controllable reflective surface array, construct a phase modulation matrix based on the target's spatial position and communication link channel parameters, obtain the target's azimuth and elevation angles in the spatial coordinate system, and calculate the position phase difference of each unit in the controllable reflective surface array based on the azimuth and elevation angles.

[0080] 1022. Based on the position phase difference, extract the path loss coefficient from the communication link channel parameters, and use the path loss coefficient to derive the initial phase gradient step size of the phase modulation matrix;

[0081] 1023. Based on the initial phase gradient step size, detect the Doppler frequency shift polarity of the target motion direction. If the Doppler frequency shift polarity is positive, set the phase gradient direction to match the positive direction of the spatial coordinate system azimuth angle. If the Doppler frequency shift polarity is negative, set the phase gradient direction to match the negative direction of the spatial coordinate system azimuth angle.

[0082] Step 1023 may specifically include the following process: using the initial phase gradient step size as an input parameter, performing spectral analysis on the target motion direction to obtain frequency shift characteristics in the spectral analysis results; based on the comparison between the frequency shift characteristics and the preset center frequency, if the frequency shift characteristics are higher than the preset center frequency, determining that the Doppler frequency shift polarity is positive; if the frequency shift characteristics are lower than the preset center frequency, determining that the Doppler frequency shift polarity is negative; when the Doppler frequency shift polarity is positive, assigning the phase gradient direction to a unit vector in the positive azimuth direction of the spatial coordinate system; when the Doppler frequency shift polarity is negative, assigning the phase gradient direction to a unit vector in the negative azimuth direction of the spatial coordinate system; outputting the phase gradient direction as an input parameter for synthesizing the phase values ​​of each unit of the controllable reflective surface array.

[0083] 1024. Based on the phase gradient direction, multiply the initial phase gradient step size by the phase gradient direction to synthesize the phase value of each unit of the controllable reflective surface array, and based on the phase value, separate the energy distribution of the target echo and the communication signal on the propagation path.

[0084] In the above steps, a controllable reflector is a device panel capable of adjusting its own reflection phase, used to enhance signal transmission and improve the performance of wireless communication and radar systems; target spatial position refers to the specific coordinates of the target object relative to the receiver in three-dimensional space, such as the target's position coordinates on the ground in a radar system; communication link channel parameters are data describing the characteristics of wireless signal transmission, including parameters such as signal attenuation amplitude, noise level, and path loss; the phase modulation matrix is ​​a matrix structure used to control the phase values ​​of the reflector units, whose elements represent the phase adjustment angle of each unit in the array; Doppler frequency shift polarity refers to the frequency shift direction characteristic caused by the relative motion of the target, with positive polarity indicating frequency increase and negative polarity indicating frequency decrease; the phase gradient direction is the adjustment trend direction of the phase values ​​in the phase modulation matrix, used to control the signal in space. The propagation angle; target echo is the target reflected signal received by the reflector; communication signal is the direct signal from the transmitter to the reflector and then to the receiver; energy distribution on the propagation path represents the signal strength distribution along the transmission path; controllable reflector array refers to a matrix-type reflector device composed of multiple independently adjustable phase units; azimuth angle is the angle value of the target in the horizontal direction; elevation angle is the angle value of the target in the vertical direction; position phase difference refers to the magnitude of the phase difference caused by the different positions of array units; path loss coefficient is a quantitative parameter of the degree of signal attenuation during propagation; initial phase gradient step size is the basic incremental unit of phase adjustment; frequency offset characteristic is the deviation value of the signal frequency relative to the preset center in spectrum analysis; the positive or negative azimuth unit vector of the spatial coordinate system is the horizontal angle reference direction represented by a unit vector.

[0085] In this embodiment, firstly, a controllable reflector array is deployed through step 1021; then, the azimuth and elevation angles of the target are obtained based on the target's spatial position; and then, the position phase difference is calculated based on these angles, specifically using spatial geometric formulas. ,in Indicates the position phase difference, It is the signal wavelength. It is the array cell spacing. This is a combination of azimuth and elevation angles. During calculation, the array unit coordinates and signal parameters are first determined, then the angle values ​​are substituted to calculate the phase angle of the difference. The output phase difference matrix is ​​used in subsequent steps. For example, in an automotive radar scenario, the target is assumed to be located at an azimuth angle of 45 degrees and an elevation angle of 30 degrees. The spacing between controllable reflector array units is 0.5 meters, and the signal wavelength is 0.03 meters. After deploying the array, the angle values ​​are obtained, and the phase difference at the azimuth angle of 45 degrees is calculated. The numerical values ​​are then substituted into the formula. The phase difference calculation for radians and a pitch angle of 30 degrees is similar; finally, the output position phase difference value array is used as input for step 1022.

[0086] Secondly, based on the positional phase difference, step 1022 extracts the path loss coefficient from the communication link channel parameters. This coefficient represents the degree of signal attenuation and is calculated by dividing the actual received signal strength by the transmitted signal strength. Then, this coefficient is used to derive the initial phase gradient step size. Specifically, the path loss coefficient is multiplied by a preset phase adjustment factor to obtain the step size value, as shown in the formula: ,in It is the initial phase gradient step size. This is the system's preset scaling factor, ranging from 0.1 to 1.0. This is the path loss coefficient. During derivation, the loss value is first obtained from the channel parameter database, multiplied by a factor of k to obtain the step size, ensuring the step size is within a reasonable range to avoid signal distortion. For example, in an automotive radar scenario, the path loss coefficient is assumed to be 0.8 (representing a signal attenuation of 20%), with a preset... The factor is 0.125; the initial phase gradient step size is derived. Radius; output this step size value as the input parameter for step 1023.

[0087] Next, through step 1023, based on the initial phase gradient step size output in step 1022, the Doppler frequency shift polarity of the target's motion direction is first detected. The specific process includes: using the step size as an input parameter, performing spectral analysis on the target motion signal, and using the Fast Fourier Transform algorithm to calculate the frequency shift feature, i.e., the signal frequency shift; then comparing the frequency shift feature with the preset center frequency. If the shift feature is higher than the center frequency, the Doppler frequency shift polarity is determined to be positive; if it is lower than the center frequency, it is determined to be negative. Finally, the phase gradient direction is set according to the determination: if the polarity is positive, the phase gradient direction is assigned a unit vector in the positive azimuth direction of the spatial coordinate system, such as a +1 vector; if the polarity is negative, it is assigned a unit vector in the negative direction, such as a -1 vector. This process ensures that the direction adjustment matches the target's dynamics. For example, in the automotive radar scenario, the initial phase gradient step size is 0.1 radians; the target motion signal is analyzed by spectrum, the center frequency is set to 1000 Hz, the frequency offset characteristic is measured to be 1050 Hz, which is higher than the center frequency, and the polarity is determined to be positive; therefore, the phase gradient direction is set to the positive azimuth direction unit vector (+1); the output of this direction vector is used as the input of step 1024.

[0088] Finally, based on the phase gradient direction in step 1024, the initial phase gradient step size is first multiplied by the phase gradient direction to synthesize the phase value of each element of the controllable reflective surface array. The specific formula is as follows: . Direction vector, where This is the unit phase value. The phase adjustment angle of each unit is obtained through this multiplication. Then, based on these phase values, a phase modulation matrix is ​​applied to the array units to control the signal reflection angle, so that the target echo energy is enhanced on a specific path while the communication signal is weakened on another path, thus achieving energy distribution separation. The separation process involves adjusting the phase values ​​and controlling the reflector units to form directional beams to distinguish the paths. For example, in an automotive radar scenario, the initial phase gradient step size is 0.1 radians, and the direction is the positive unit vector + 1; the synthesized phase value is calculated as follows: The radian value is assigned to all array elements; after outputting the phase value matrix, the matrix is ​​applied to concentrate the energy of the target echo on the path, such as by increasing it by 20, while reducing the energy of the communication signal on the direct path, such as by decreasing it by 30, ultimately achieving separation and optimization of target tracking and communication transmission.

[0089] In practical applications, within a certain communication system, this system processes the wireless signal transmission process to optimize signal measurement. First, based on the characteristics of the signal transmission channel's state changes, such as its stability over time, and the signal's bandwidth (frequency range), specific parameters of the integrated signal are extracted: for example, the signal duration is 100 milliseconds, and the bandwidth is 50 kHz. The time interval unit is set to 2 milliseconds per time point; therefore, the total number of rows in the signal's time-frequency domain grid is calculated as follows: Total number of rows = Duration / Time interval unit = 100ms / 2ms = 50. The frequency interval unit is set to 1 kHz per frequency point; therefore, the total number of columns is calculated as follows: Total number of columns = Bandwidth / Frequency interval unit = 50kHz / 1kHz = 50. Next, based on the total number of rows and columns of 50, and combined with the maximum frequency offset range caused by the target movement, it is set to 200 Hz. Within the index range of frequency offset, the index value represents the magnitude of the frequency offset, assuming it is from -100 to 100, with a step size of 1. The positive region is divided into an index range from 1 to 100, and the negative region index range is from -100 to 0. Then, within the positive and negative regions, pilot symbols are configured based on the ratio of the total number of rows to the total number of columns (50 rows divided by 50 columns, with a ratio of 1). These symbols serve as the position coordinates and distribution density of reference points for signal measurement. For example, in the positive region, indices from 1 to 100 are set to the coordinates of the 10th time row and 10th frequency column, the 20th time row and 20th frequency column, etc., with one pilot placed every 10 points, at a density of one per 10 index units. In the negative region, indices from -100 to 0 are set to the coordinates of the -10th time row and -10th frequency column, the -20th time row and -20th frequency column, etc., with the same density. Based on this, the upper limit of the frequency offset index range is set to 100 (maximum value) and the lower limit to -100 (minimum value), and a mapping relationship is established with the Doppler channel indices of the radar signal. For example, the index value is mapped to the channel sequence number, such as channel 1 corresponding to index 1, channel 2 corresponding to index 2, etc. Finally, by integrating the position coordinate distribution density and index mapping relationship of pilot symbols, pilot distribution parameters are generated to optimize the acquisition efficiency of channel state information, making signal measurement more accurate and reliable.

[0090] In the overall scheme of step 102 above, the time-frequency distribution coordinates and density values ​​of pilot symbols are accurately configured based on the time stability and bandwidth characteristics of the channel state. The total dimension of the time-frequency domain grid is dynamically set by extracting the duration and bandwidth parameters of the integrated signal. The Doppler index range is intelligently divided into positive and negative bidirectional regions by combining the target's maximum Doppler frequency shift. The pilot position and density distribution are adaptively adjusted within the region according to the grid row and column ratio. Then, precise Doppler index boundary values ​​are set and bidirectional mapping association is established with the radar Doppler channel index, thereby forming highly coordinated pilot distribution parameters. This significantly improves the acquisition accuracy and timeliness of channel state information, effectively reduces pilot overhead, and enhances the robustness of channel estimation in high-speed mobile scenarios. Ultimately, it achieves comprehensive optimization of the resource utilization efficiency of the integrated communication and sensing system.

[0091] 103. Within the Doppler index range, calculate the frequency offset estimate by the phase difference of the pilot symbols, correct the time-domain sampling points of the received signal based on the frequency offset estimate, eliminate the frequency-domain linear phase deviation, and reconstruct the multipath delay parameters and sub-Doppler frequency shift parameters of the dynamic channel based on the corrected pilot symbols to generate a phase correction vector.

[0092] Optionally, step 103 may specifically include the following steps:

[0093] 1031. Within the Doppler index range, select two adjacent pilot symbols, calculate the phase difference between the two adjacent pilot symbols, and combine the time interval between the two adjacent pilot symbols to determine the frequency offset estimate.

[0094] 1032. Based on the frequency offset estimate, perform phase correction on the time-domain sampling points of the received signal, and use the corrected pilot symbols to analyze the correlation peak amplitude of different delay indices, and reconstruct the multipath delay parameters of the dynamic channel based on the correlation peak amplitude.

[0095] 1033. At the time delay index corresponding to the multipath time delay parameter, solve for the phase change rate within the Doppler index range, and reconstruct the sub-Doppler frequency shift parameter based on the phase change rate;

[0096] 1034. The reconstructed multipath delay parameters and the sub-Doppler frequency shift parameters are fused to generate a phase correction vector.

[0097] In the above steps, the Doppler index range is the frequency offset index interval defined in the previous steps, covering the maximum to minimum value of the frequency offset index caused by target motion; the pilot symbol is a known symbol pre-set in the time-frequency grid, used to assist signal estimation; the phase difference is the difference in phase angle between two adjacent pilot symbols; the time interval is the distance between adjacent pilot symbols in the time direction, representing the time difference between symbols; the frequency offset estimate is the estimated frequency deviation calculated by the phase difference and the time interval; the time-domain sampling point of the received signal is the sampling data point of the signal received by the radar or communication system in time; the frequency-domain linear phase deviation is the linear phase error of the signal in the frequency direction; the corrected pilot symbol is the pilot point data after phase correction; the multipath delay parameter describes the time delay characteristics of the signal after propagation through multiple paths; the sub-Doppler frequency shift parameter is a finer frequency offset component based on the subdivision of the Doppler frequency shift; the phase change rate represents the rate at which the phase changes with the Doppler index; the phase correction vector is a set of parameters generated by integrating the multipath delay and the sub-Doppler frequency shift, used for subsequent signal correction.

[0098] In this embodiment, firstly, in step 1031, two adjacent pilot symbols are selected within the pre-defined Doppler index range, their positions determined by the pilot distribution parameters from the previous steps; then, the phase difference between these two symbols is calculated, specifically by obtaining the complex representation of the symbols and performing angle subtraction, for example, using the formula... ,in and It is a signified complex value. This is the phase difference in radians; the difference is calculated. During processing, it's crucial to ensure that symbol indices are adjacent to avoid cross-region errors. For example, in an automotive radar scenario, the Doppler index range is set to -7 to 7. Pilot symbol positions are such as row 8, column 100 and row 8, column 110, with the time interval being the column interval multiplied by the sampling period. Assuming symbol 1 has a phase angle of 0.5 radians and symbol 2 has a phase angle of 0.8 radians, then the phase difference... Radius; the time interval is calculated by multiplying the column difference by the sampling period, with a column difference of 10 points and a sampling period of 1 microsecond. Seconds; the formula for frequency offset estimation is: Substitute the values Hertz; finally, output the frequency offset estimate as input to step 1032.

[0099] Secondly, based on the frequency offset estimate, step 1032 performs phase correction on the time-domain sampling points of the received signal; specifically, this is achieved by constructing a phase rotation factor using the frequency offset estimate, such as the formula rotation. ,in This is the sampling time, applied to each sampling point to eliminate linear phase deviation in the frequency domain. The corrected sampling point is represented as the original complex signal multiplied by a rotation factor. For example, in an automotive radar scenario, the estimated frequency offset is 4777 Hz, and the sampling time at a certain sampling point is 0.0005 seconds. The rotation factor is calculated as follows: The phase is corrected by approximately 15 radians. Next, correlation analysis is performed using the corrected pilot symbols at points where the phase is more accurate: the corrected pilot symbols are cross-correlated with the reference signal. The algorithm uses a fast cross-correlation function to detect the amplitude of the correlation peak at different time delay indices. In the cross-correlation calculation, the time delay index is the quantized value of the time delay, and the peak amplitude of the correlation peak corresponds to the maximum match. For example, the cross-correlation peak appears at index 50 with an amplitude of 0.9, and another peak is at index 100 with an amplitude of 0.7. The reconstructed multipath delay parameters are output as a list of delay values ​​based on the index of the peak, such as index 50 corresponding to a delay of 5 microseconds and index 100 corresponding to a delay of 10 microseconds. This multipath delay parameter is then output as input to step 1033.

[0100] Next, based on the multipath delay parameters in step 1033, the phase change within the Doppler index range is analyzed at the delay index corresponding to each path, such as indices 50 and 100. When solving for the phase change rate, multiple Doppler index points are selected at the specified delay index, such as indices from -7 to 7, and the slope change of the pilot symbol phase is calculated. A linear fitting algorithm is used, and the formula for the change rate is... ,in It is the phase difference when the Doppler index changes. This refers to the index step size; for example, at time delay index 50, the phase values ​​of the Doppler index from 0 to 1 change from 0.4 radians to 0.6 radians, with a rate of change... Radius per index unit; then reconstruct the sub-Doppler frequency shift parameters, dividing the rate of change by the time factor to convert to frequency; formula ,in This refers to the time step corresponding to the Doppler index, assuming 1 millisecond, or a rate of change of 0.2 radians per unit. Substitute this into the calculation. Hertz; perform this step for each time delay path to output a list of sub-Doppler frequency shifts; finally, output the sub-Doppler frequency shift parameters as input to step 1034.

[0101] Finally, multipath delay parameters and sub-Doppler frequency shift parameters are integrated in step 1034. The fusion process combines the parameter pairs of each delay path into vector elements, for example, a vector structure of [delay value 1, frequency shift value 1; delay value 2, frequency shift value 2]. For example, in an automotive radar scenario, the multipath delay parameter list might be 5 microseconds and 10 microseconds, and the sub-Doppler frequency shift parameter list might be 31.8 Hz and 45 Hz, corresponding to two paths. A phase correction vector is generated, such as [5e-631.810e-645], which is used for subsequent signal processing to correct phase deviations. Finally, this phase correction vector is output to optimize the overall signal accuracy.

[0102] In practical applications, within a certain wireless communication system, this system handles the reception and correction of wireless signals to improve signal quality. Specifically, within a frequency offset range of -10 to 10 (where the index value represents the degree of offset, with each index unit corresponding to 5 Hz), two adjacent measurement reference points are selected, located at index 1 and index 2. The time interval between these two reference points is 1 millisecond, and their phase difference is measured to be 1.57 radians, equivalent to half a circle's diameter. Next, the estimated frequency offset is calculated: the frequency offset equals the phase difference divided by twice pi multiplied by the time interval, i.e., 1.57 divided by 2 times 3.14 times 0.001 seconds. The denominator is 2 times 3.14 equals 6.28, multiplied by 0.001 equals 0.00628. Then, 1.57 divided by 0.00628 yields an estimated value of 250 Hz. Based on this 250 Hz estimate, phase correction is performed on the time-point data of the received signal. Specifically, this is achieved by applying a compensation angle to each time sampling point to eliminate the linear deviation caused by frequency changes. After correction, the peak height of the signal at different delay positions was analyzed using these reference points. A strong peak was observed at delay index 5, where the index value represents the degree of delay, with each unit of index corresponding to 1 microsecond. Therefore, the time delay parameter in the reconstructed signal path is 5 microseconds. At this delay index 5 position, the phase change rate with index across the entire frequency offset range was further calculated: the phase difference between the measured index points was divided by the index difference, where 1 unit of index difference represents the phase change step. The calculated phase change per unit index was 0.314 radians, equivalent to pi divided by 10. Then, based on the correspondence between index and frequency, each unit of index equals 5 Hz, converting the phase change rate of 0.314 radians into a sub-frequency offset parameter of 50 Hz. Finally, the reconstructed time delay parameter of 5 microseconds and the sub-frequency offset parameter of 50 Hz were combined to generate a unified phase correction vector for subsequent signal processing, thereby improving the system's ability to track dynamic signal changes and making the measurement more stable and reliable.

[0103] In the overall scheme of step 103 above, the frequency offset estimate is dynamically calculated by the phase difference between adjacent pilot symbols within the set Doppler index range. Based on this, the time-domain sampling points of the received signal are precisely phase-corrected to eliminate the linear phase deviation in the frequency domain. Subsequently, based on the corrected pilot symbols, the correlation peak amplitude features under different delay indices are extracted and the multipath delay parameters of the dynamic channel are reconstructed. At the same time, the phase change rate within the Doppler index range is analyzed at the corresponding delay index to reconstruct the fine sub-Doppler frequency shift parameters. Finally, the dual parameters of multipath delay and sub-Doppler frequency shift are fused to generate a high-precision phase correction vector, which significantly improves the accuracy of channel parameter estimation in high-speed mobile scenarios, effectively suppresses the Doppler spread effect, and enhances the robustness of the orthogonal frequency division multiplexing system against frequency offset, providing reliable channel state feedback for the integrated communication and sensing system.

[0104] 104. Based on the reconstructed multipath delay parameters, locate the main beam interference region of the spatial aliasing signal. Within the main beam interference region, use the phase correction vector and sub-Doppler frequency shift parameters to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling.

[0105] Optionally, step 104 may specifically include the following steps:

[0106] 1041. Based on the reconstructed multipath delay parameters, scan the energy distribution of the spatial spectrum, and locate the main beam interference region of the spatial aliasing signal based on the energy distribution;

[0107] 1042. Within the main beam interference zone, the phase correction vector is applied to the frequency domain subcarrier index to obtain the shaping weighting coefficient of the frequency domain beam, and the sub-Doppler frequency shift parameter is applied to the frequency domain sampling point index to generate the phase rotation compensation amount.

[0108] 1043. The superposition of the shaping weighting coefficients and the phase rotation compensation amount is used to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling to obtain a compensated frequency domain signal. The compensated frequency domain signal is then converted to the time-delay Doppler domain to complete the separation operation.

[0109] Step 1043 may specifically include the following processes: applying the shaping weighting coefficients to the signal components corresponding to the frequency domain subcarrier index to generate a first set of adjustment components, each unit of the first set of adjustment components being associated with the focusing direction of the space beam; mapping the phase rotation compensation amount to the signal components corresponding to the frequency domain sampling point index to generate a second set of adjustment components, each unit of the second set of adjustment components being associated with the phase correction of symbol decoupling; merging the first set of adjustment components and the second set of adjustment components to generate a merged signal component, wherein the merged signal component of each frequency domain sampling point index in the merging operation is composed of the superposition of the first set of adjustment components and the second set of adjustment components with the same index; based on the merged signal component, converting the frequency domain subcarrier index and the frequency domain sampling point index to the time delay index and the Doppler index, outputting the time delay Doppler domain signal, and completing the separation operation of the target echo and the communication signal.

[0110] In the above steps, the spatial aliasing signal main beam interference zone refers to the signal overlap area formed by the multipath effect during signal propagation in space, resulting in the spatial range where the target echo and communication signal energy are confused; the frequency domain beamforming weighting coefficient is a signal strength adjustment value calculated based on the phase correction vector, used to enhance the signal energy in a specific direction; the phase rotation compensation amount is a phase correction value generated by the sub-Doppler frequency shift parameter, used to eliminate signal distortion caused by frequency offset; inter-symbol interference is the phenomenon of energy overlap between adjacent symbols during signal transmission; spatial path aliasing refers to the phenomenon that signals from multiple propagation paths cannot be distinguished in space; spatial beam focusing is the process of concentrating the signal in a specific spatial direction by adjusting the signal energy distribution; time-frequency domain symbol decoupling is the operation of separating mutually interfering components of the signal in the time and frequency dimensions; the frequency domain subcarrier index is the identification number of each sub-band after frequency division; the frequency domain sampling point index is the number of each sampling position in the frequency domain signal; the adjustment component is an intermediate signal unit generated by weighting or compensation; the combined signal component is the result of superimposing the weighted and compensated signal units; the time delay Doppler domain is a two-dimensional analysis domain that fuses signal delay and frequency offset characteristics.

[0111] In this embodiment, firstly, in step 1041, based on the reconstructed multipath delay parameters, such as the time delay list output in the previous step (e.g., 5 microseconds and 10 microseconds), a directional scan is performed in the spatial domain: using a beamforming algorithm, such as the Capon beamformer, the signal strength distribution at different spatial angles is calculated to generate a spatial energy distribution map; when locating the main beam interference area, overlapping areas of peaks exceeding a preset threshold are identified in the energy map. For example, in an automotive radar scenario, a multipath delay of 5 microseconds corresponds to the direction directly in front of the target, and 10 microseconds corresponds to the reflection path direction; scanning the spatial spectrum reveals an overlapping area of ​​two energy peaks within an azimuth angle range of 30 to 40 degrees. After setting a threshold of 0.8 and a maximum energy value of 1.0, 30-40 degrees is determined to be the main beam interference area; the spatial angle range of this area is output as the basis for subsequent processing.

[0112] Secondly, in step 1042, frequency domain adjustment is performed within the located main beam interference area, such as 30-40 degrees: First, the phase correction vector, such as [5e-6 31.8 10e-6 45] output in the previous step, is applied to the frequency domain subcarrier index, and the shaping weighting coefficient of each subcarrier is calculated. The specific formula is as follows: ,in It is the weighted value of the nth subcarrier. This is the phase value corresponding to the subcarrier in the phase correction vector; then, the sub-Doppler frequency shift parameters, such as 31.8 Hz and 45 Hz output from the previous step, are applied to the frequency domain sampling point index to generate the phase rotation compensation amount for each sampling point, as shown in the formula. ,in It is the sub-Doppler frequency shift value. This refers to the sampling point time. For example, in the frequency domain subcarrier indexes 1-100, for the subcarrier at index 10 corresponding to a 5-microsecond path, the weighting coefficient is calculated. For the frequency domain sampling point of index 1, the time is 0.001 seconds, and the compensation amount is... Phase rotation of 0.2 radians; output list of weighted coefficients and list of compensation amounts.

[0113] Finally, the shaping weighting coefficients are processed in step 1043, as in the previous example. List of signal components applied to the frequency domain subcarrier index: For each subcarrier index n, the original signal component Multiply Generate the first set of adjustment components This focuses the signal energy towards the main beam interference area. Secondly, the phase rotation compensation amount is as follows: The list maps to the frequency domain sample point indices of the signal components: each sample point component. Multiply Generate the second set of adjustment components This eliminates inter-symbol interference. Next, the two components are combined: components at the same frequency domain index position are superimposed for calculation. The merged signal components are generated. Finally, the frequency domain index of the merged signal is transformed to the time-delay Doppler domain using Fourier transform, and the separated target echo and communication signal are output. For example, in the 38-degree direction of the interference zone, the original signal strength of subcarrier 10, 0.8, is multiplied by the weighting coefficient 0.45 to obtain 0.36, which is the first adjustment component; the original phase offset of sampling point 1, 0.5 radians, is compensated to become 0.3 radians, which is the second adjustment component; the combined component strength is increased to 0.66, and after transformation to the time-delay Doppler domain, the two paths are clearly separated, and the signal-to-noise ratio of the 5-microsecond path is improved by 12 dB.

[0114] In practical applications, within a radar-assisted communication system, this system optimizes signal reception to compensate for frequency changes caused by target motion. Specifically, the frequency offset range is first defined as an index from -10 to +10, where each index unit corresponds to a 5 Hz actual frequency offset. Two adjacent measurement reference points are selected within this range, located at index values ​​1 and 2, respectively. The time interval between these two reference points is 1 millisecond. The signal phase at each point is measured, yielding a phase difference of 1.57 radians. The estimated frequency offset is then calculated: the estimated frequency offset equals the measured phase difference divided by twice the constant pi, and then divided by the time interval between the two reference points. First, the denominator is calculated: the constant pi is approximately 3.14, and twice pi equals 6.28. This number is then multiplied by the time interval of 0.001 seconds, resulting in a denominator of 0.00628. The final estimated frequency offset is 1.57 radians divided by 0.00628, yielding a result of 250 Hz. Based on this calculated 250 Hz frequency offset estimate, the system begins to compensate for the phase angle of the received raw signal data, i.e., the signal sample values ​​at each time point. This is done to eliminate the phase deviation caused by the linear change of signal frequency with time. After completing the correction at these points, the system uses these corrected measurement reference points to analyze the peak signal intensity distribution at different time delay positions. Observation reveals that a significant signal peak appears at the delay index position of 5, where each delay index unit represents a 1 microsecond time delay. Based on this peak position, the system reconstructs that the main propagation path of the signal has a transmission delay parameter of 5 microseconds.

[0115] For the identified strong signal path located at delay index 5, the system further analyzes its phase change pattern within the frequency offset index range. Specifically, it calculates the rate of phase change with each unit of frequency offset index: measuring the phase difference corresponding to a 1-unit change in the index value, resulting in a 0.314 radian phase change per unit of index. Since each frequency offset index unit corresponds to a 5 Hz actual frequency offset, this phase change rate of 0.314 radians per index unit is converted into an actual sub-frequency shift parameter, simplifying to a sub-Doppler frequency shift parameter of 50 Hz for this path. Finally, the system combines the reconstructed path transmission delay parameter of 5 microseconds with the specific frequency offset parameter of 50 Hz to generate a unified set of phase correction information. This information guides accurate phase compensation in subsequent signal processing stages, significantly improving the measurement stability and reliability of channel state information in motion scenarios.

[0116] In the overall scheme of step 104 above, the frequency offset estimate is dynamically calculated by the phase difference between adjacent pilot symbols within the set Doppler index range. Based on this, the time-domain sampling points of the received signal are precisely phase-corrected to eliminate the linear phase deviation in the frequency domain. Subsequently, based on the corrected pilot symbols, the correlation peak amplitude features under different delay indices are extracted and the multipath delay parameters of the dynamic channel are reconstructed. At the same time, the phase change rate within the Doppler index range is analyzed at the corresponding delay index to reconstruct the fine sub-Doppler frequency shift parameters. Finally, the dual parameters of multipath delay and sub-Doppler frequency shift are fused to generate a high-precision phase correction vector, which significantly improves the accuracy of channel parameter estimation in high-speed mobile scenarios, effectively suppresses the Doppler spread effect, and enhances the robustness of the orthogonal frequency division multiplexing system against frequency offset, providing reliable channel state feedback for the integrated communication and sensing system.

[0117] The following is a complete embodiment for steps 101 to 104:

[0118] like Figure 2 As shown, in the signal optimization process of a certain wireless communication system, dynamic environment performance is improved through four associated stages. First, based on the signal channel's time stability and 50 kHz bandwidth parameters, measurement reference points are deployed in a time-frequency grid: the 100-millisecond signal is divided into 50 time units, each lasting 2 milliseconds, and simultaneously divided into 50 frequency units, each spanning 1 kHz. Combining the target maximum 200 Hz frequency shift range, a frequency offset index is set to cover the interval from -100 to +100. Following a 1:1 ratio of time units to frequency units, reference points are deployed every 10 units in the positive index region, and the same density is used in the negative index region, forming a distribution parameter that optimizes channel acquisition efficiency.

[0119] Next, an intelligent adjustable reflector is deployed, and a phase control matrix is ​​constructed by integrating the target's spatial coordinates and communication link parameters. When the detected target moves towards the receiver and generates a positive frequency shift, the matrix phase gradient is immediately adjusted to an increasing mode from southeast to northwest. Specifically, the initial phase value at the upper left corner of the matrix is ​​set to zero radians, and the phase value at the lower right corner is set to 1.57 radians. The transmission path energy of the communication signal and the target echo is separated by the gradient change.

[0120] In the signal correction phase, adjacent reference points at indices 1 and 2 are selected within a preset frequency shift index range of -10 to +10. A phase difference of 1.57 radians is measured between these two points within a 1-millisecond time interval. The estimated 250 Hz frequency shift is calculated using the ratio of the phase difference to the time interval. This value is applied to all received signal sampling points for phase compensation. Analysis of the signal delay characteristics reveals a main peak at index 5. Based on the 1-microsecond baseline relationship for each delay index, the main path delay parameter is determined to be 5 microseconds. Further analysis of the phase change between indices at this delay position shows a 0.314-radian phase difference for each unit increase in the frequency index. Based on the conversion relationship between index units and the 5 Hz frequency, the 50 Hz sub-Doppler frequency shift parameter is calculated. Finally, the 5-microsecond delay and the 50 Hz frequency shift are fused to generate a phase correction vector.

[0121] The final processing stage locates the main interference zone of spatial aliasing based on the reconstructed 5-microsecond main path delay. Within this zone, dual operations are performed simultaneously: beamforming weighting is applied to enhance the signal strength in the target direction, while a phase correction vector is applied for frequency domain phase rotation. This collaborative processing effectively suppresses symbol crosstalk and spatial path aliasing caused by high-speed targets, achieving energy focusing in the spatial dimension and symbol separation optimization in the time-frequency dimension.

[0122] Figure 3 This application provides a schematic diagram of the structure of an OTFS radar-communication integrated signal processing system with joint optimization in the time, frequency, and spatial domains, as shown in the embodiments of this application. Figure 3 As shown, the system includes:

[0123] The optimization module 31 is used to configure the position and density of pilot symbols in the signal time-frequency domain grid according to the time stability and bandwidth characteristics of the channel state, and to set the Doppler index range based on the position and density of the pilot symbols to form pilot distribution parameters to optimize the channel state information acquisition efficiency.

[0124] The separation module 32 is used to deploy a controllable reflector, construct a phase modulation matrix based on the target's spatial location and communication link channel parameters, and dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target's motion direction to separate the energy distribution of the target echo and the communication signal on the propagation path.

[0125] The reconstruction module 33 is used to calculate the frequency offset estimate by the phase difference of the pilot symbols within the Doppler index range, correct the time domain sampling points of the received signal based on the frequency offset estimate, eliminate the frequency domain linear phase deviation, and reconstruct the multipath delay parameters and sub-Doppler frequency shift parameters of the dynamic channel based on the corrected pilot symbols to generate a phase correction vector.

[0126] The correction module 34 is used to locate the main beam interference region of the spatial aliasing signal based on the reconstructed multipath delay parameters. Within the main beam interference region, the phase correction vector and sub-Doppler frequency shift parameters are used to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain to suppress inter-symbol interference and spatial path aliasing caused by high-speed targets, thereby achieving spatial beam focusing and time-frequency symbol decoupling.

[0127] Figure 3 The aforementioned time-frequency-spatial domain jointly optimized OTFS radar-communication integrated signal processing system can perform... Figure 1 The implementation principle and technical effects of the OTFS radar-communication integrated signal processing method with joint optimization in the time-frequency and spatial domains described in the illustrated embodiment will not be repeated here. The specific methods by which each module and unit of the OTFS radar-communication integrated signal processing system with joint optimization in the time-frequency and spatial domains in the above embodiments are described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0128] In one possible design, Figure 3 The time-frequency-spatial domain joint optimization OTFS radar-communication integrated signal processing system of the embodiment shown can be implemented as a computing device, such as... Figure 4 As shown, the computing device may include a storage component 41 and a processing component 42;

[0129] The storage component 41 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 42.

[0130] The processing component 42 is used for the above Figure 1 The embodiment describes an OTFS radar-communication integrated signal processing method with joint optimization in the time, frequency, and spatial domains.

[0131] The processing component 42 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0132] Storage component 41 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0133] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0134] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0135] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0136] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0137] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The embodiment shown is an integrated OTFS radar-communication signal processing method with joint optimization in the time-frequency and spatial domains.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0139] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A time-frequency-space domain joint optimization OTFS radar-communication integrated signal processing method, characterized in that, The method comprises the following steps: According to the time stability and bandwidth characteristics of the channel state, the positions and densities of pilot symbols in the signal time-frequency domain grid are configured, the Doppler index range is set based on the positions and densities of the pilot symbols, and the pilot distribution parameters are formed to optimize the channel state information acquisition efficiency; Deploy controllable reflectors, construct a phase modulation matrix based on the target spatial position and communication link channel parameters, dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target motion direction, and separate the energy distribution of the target echo and the communication signal on the propagation path; In the Doppler index range, the frequency offset estimation value is calculated through the phase difference of the pilot symbols, the time domain sampling points of the received signal are corrected based on the frequency offset estimation value, the frequency domain linear phase deviation is eliminated, and the multi-path time delay parameters and sub-Doppler frequency shift parameters of the dynamic channel are reconstructed based on the corrected pilot symbols, and a phase correction vector is generated; Based on the reconstructed multi-path time delay parameters, the main beam interference area of the spatially overlapped signal is located, and in the main beam interference area, the phase correction vector and the sub-Doppler frequency shift parameters are used to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain, to suppress the inter-symbol interference and spatial path aliasing caused by high-speed targets, and to realize spatial beam focusing and time-frequency domain symbol decoupling.

2. The method of claim 1, wherein, Deploy controllable reflectors, construct a phase modulation matrix based on the target spatial position and communication link channel parameters, dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target motion direction, and separate the energy distribution of the target echo and the communication signal on the propagation path, comprising: Deploy controllable reflector arrays, construct a phase modulation matrix based on the target spatial position and communication link channel parameters, obtain the azimuth angle and elevation angle of the target in the spatial coordinate system, and calculate the position phase difference of each unit in the controllable reflector array based on the azimuth angle and elevation angle; According to the position phase difference, the path loss coefficient is extracted from the communication link channel parameters, and the initial phase gradient step of the phase modulation matrix is derived using the path loss coefficient; Based on the initial phase gradient step, the Doppler frequency shift polarity of the target motion direction is detected, if the Doppler frequency shift polarity is positive, the phase gradient direction is matched with the positive direction of the azimuth angle of the spatial coordinate system, and if the Doppler frequency shift polarity is negative, the phase gradient direction is matched with the negative direction of the azimuth angle of the spatial coordinate system; According to the phase gradient direction, the initial phase gradient step is multiplied by the phase gradient direction to synthesize the phase values of each unit in the controllable reflector array, and based on the phase values, the energy distribution of the target echo and the communication signal on the propagation path is separated.

3. The method of claim 1, wherein, Based on the reconstructed multi-path time delay parameters, the main beam interference area of the spatially overlapped signal is located, and in the main beam interference area, the phase correction vector and the sub-Doppler frequency shift parameters are used to perform beamforming weighting and phase rotation compensation on the signal in the frequency domain, to suppress the inter-symbol interference and spatial path aliasing caused by high-speed targets, and to realize spatial beam focusing and time-frequency domain symbol decoupling, comprising: According to the reconstructed multipath delay parameter, the energy distribution of the spatial spectrum is scanned, and the main beam interference area of the spatial aliasing signal is located based on the energy distribution; In the main beam interference area, the phase correction vector is applied to the frequency domain subcarrier index to obtain the beamforming weighting coefficient of the frequency domain beam, and the sub-Doppler frequency shift parameter is applied to the frequency domain sampling point index to generate a phase rotation compensation amount; The beamforming weighting coefficient and the phase rotation compensation amount are superimposed to suppress the inter-symbol interference and spatial path aliasing caused by the high-speed target, realize spatial beam focusing and time-frequency domain symbol decoupling, obtain a compensated frequency domain signal, convert the compensated frequency domain signal to the time delay Doppler domain, and complete the separation operation.

4. The method of claim 1, wherein, In the Doppler index range, a frequency offset estimation value is calculated through the phase difference of the pilot symbols, the time domain sampling points of the received signal are corrected based on the frequency offset estimation value to eliminate the linear phase deviation in the frequency domain, and based on the corrected pilot symbols, the multipath delay parameter and the sub-Doppler frequency shift parameter of the dynamic channel are reconstructed to generate a phase correction vector, including: In the Doppler index range, two adjacent pilot symbols are selected, the phase difference value of the two adjacent pilot symbols is calculated, and the frequency offset estimation value is determined in combination with the time interval between the two adjacent pilot symbols; According to the frequency offset estimation value, the time domain sampling points of the received signal are phase corrected, the correlation peak amplitudes of different time delay indexes are analyzed using the corrected pilot symbols, and the multipath delay parameter of the dynamic channel is reconstructed according to the correlation peak amplitudes; In the time delay index corresponding to the multipath delay parameter, the phase change rate in the Doppler index range is solved, and the sub-Doppler frequency shift parameter is reconstructed according to the phase change rate; The reconstructed multipath delay parameter and the sub-Doppler frequency shift parameter are fused to generate a phase correction vector.

5. The method of claim 1, wherein, According to the time stability and bandwidth characteristics of the channel state, the positions and densities of the pilot symbols in the signal time-frequency domain grid are configured, based on the positions and densities of the pilot symbols, the Doppler index range is set, the pilot distribution parameter is formed to optimize the channel state information acquisition efficiency, including: According to the time stability and bandwidth characteristics of the channel state, the total number of rows and the total number of columns of the signal time-frequency domain grid are determined by extracting the duration and bandwidth parameters of the integrated signal; Based on the total number of rows and the total number of columns, in combination with the maximum Doppler frequency shift range of the target motion, the positive region and the negative region are divided in the Doppler index range; In the positive region and the negative region, according to the proportional relationship of the total number of rows and the total number of columns, the position coordinates and density distribution of the pilot symbols are configured; Based on the position coordinates and density distribution of the pilot symbols, the upper limit value and the lower limit value of the Doppler index range are set, and a mapping relationship with the Doppler channel index of the radar signal is established; The position coordinates and density distribution of the pilot symbols and the mapping relationship are integrated to generate the pilot distribution parameter to optimize the channel state information acquisition efficiency.

6. The method of claim 3, wherein, Superimpose the shaping weight coefficient and the phase rotation compensation amount to suppress the inter-symbol interference and spatial path aliasing caused by the high-speed target, realize spatial beam focusing and time-frequency domain symbol decoupling, obtain a compensated frequency domain signal, convert the compensated frequency domain signal to time-delay Doppler domain, and complete separation operation, including: Apply the shaping weight coefficient to the signal component corresponding to the frequency domain subcarrier index to generate a first group of adjustment components, each unit of the first group of adjustment components being associated with the focusing direction of the spatial beam; Map the phase rotation compensation amount to the signal component corresponding to the frequency domain sampling point index to generate a second group of adjustment components, each unit of the second group of adjustment components being associated with the phase correction of symbol decoupling; Merge the first group of adjustment components and the second group of adjustment components to generate a merged signal component, wherein the merged signal component of each frequency domain sampling point index in the merging operation is composed of the first group of adjustment components and the second group of adjustment components of the same index; Based on the merged signal component, convert the frequency domain subcarrier index and the frequency domain sampling point index to the time-delay index and the Doppler index, output the time-delay Doppler domain signal, and complete the separation operation of the target echo and the communication signal.

7. The method of claim 2, wherein, Based on the initial phase gradient step length, detect the Doppler frequency shift polarity of the target motion direction, if the Doppler frequency shift polarity is positive, set the phase gradient direction to match the positive direction of the azimuth angle of the spatial coordinate system, if the Doppler frequency shift polarity is negative, set the phase gradient direction to match the negative direction of the azimuth angle of the spatial coordinate system, including: Take the initial phase gradient step length as an input parameter to perform spectrum analysis on the target motion direction, and obtain the frequency offset feature in the spectrum analysis result; According to the comparison relationship between the frequency offset feature and the preset center frequency, if the frequency offset feature is higher than the preset center frequency, it is determined that the Doppler frequency shift polarity is positive, if the frequency offset feature is lower than the preset center frequency, it is determined that the Doppler frequency shift polarity is negative; When the Doppler frequency shift polarity is positive, the phase gradient direction is assigned as the unit vector of the positive direction of the azimuth angle of the spatial coordinate system, and when the Doppler frequency shift polarity is negative, the phase gradient direction is assigned as the unit vector of the negative direction of the azimuth angle of the spatial coordinate system; Output the phase gradient direction as an input parameter for synthesizing the phase value of each unit of the controllable reflectarray.

8. A time-frequency-space domain joint optimization OTFS radar-communication integrated signal processing system, characterized in that, Including: An optimization module is configured to configure the position and density of pilot symbols in a signal time-frequency domain grid according to the time stability and bandwidth characteristics of a channel state, set a Doppler index range based on the position and density of the pilot symbols, form pilot distribution parameters to optimize channel state information acquisition efficiency; A separation module is configured to deploy a controllable reflectarray, construct a phase modulation matrix based on a target spatial position and communication link channel parameters, dynamically adjust the phase gradient direction of the phase modulation matrix according to the Doppler frequency shift polarity of the target motion direction, and separate the energy distribution of target echoes and communication signals on the propagation path. The reconstruction module is configured to calculate a frequency offset estimation value by means of a phase difference of pilot symbols within the Doppler index range, correct time domain sampling points of a received signal based on the frequency offset estimation value, eliminate a frequency domain linear phase deviation, and reconstruct multipath time delay parameters and sub-Doppler shift parameters of a dynamic channel based on the corrected pilot symbols to generate a phase correction vector. The correction module is configured to locate a main beam interference area of a spatial aliasing signal based on the reconstructed multipath time delay parameters, perform beamforming weighting and phase rotation compensation on the signal in a frequency domain by means of the phase correction vector and the sub-Doppler shift parameters within the main beam interference area, suppress inter-symbol interference and spatial path aliasing caused by a high-speed target, and realize spatial beam focusing and time-frequency domain symbol decoupling.

9. A computing device, comprising: The device comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement the time-frequency-space domain joint optimization OTFS radar communication integrated signal processing method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device stores a computer program, and the computer program is executed by a computer to implement the time-frequency-space domain joint optimization OTFS radar communication integrated signal processing method according to any one of claims 1 to 7.

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