Communication and perception integrated multi-target detection method and device, terminal and medium

Abstract

The invention discloses a communication perception integrated multi-target detection method and device, a terminal and a medium, and relates to a communication perception integrated technology, and the method comprises the steps: obtaining a radio frequency analog signal through a receiving end, carrying out the frequency mixing conversion of the radio frequency analog signal, and determining a digital baseband signal; carrying out demodulation and inverse mapping on the digital baseband signal, and determining a sensing residual signal; and performing feature extraction on the sensing residual signal through a pre-trained time-frequency transformation network, and determining a target distance Doppler map. According to the invention, the radio frequency analog signal acquired by the receiving end is converted into the sensing residual signal, and the pre-trained time-frequency transformation network is used for carrying out feature extraction on the sensing residual signal to obtain the super-resolution distance Doppler graph, so that signal model parameter estimation is not needed, the calculation efficiency is high, and the anti-noise performance is stable; therefore, the problems of high calculation complexity and unstable performance due to the fact that the signals are assumed to obey the known generation model and the model parameters are estimated in the prior art can be effectively solved.

Description

Technical Field

[0001] This invention relates to the field of integrated communication and sensing technology, and in particular to a method, device, terminal and medium for integrated communication and sensing multi-target detection. Background Technology

[0002] Integrated Communication-Sensing (ISAC) is one of many strategies for the coexistence of radar and communications. This strategy has emerged in recent years to address the increasingly congested spectrum and the high bandwidth requirements of radar and communication systems. In an ISAC system, radar and communication share the same platform and use a common transmit waveform. Existing ISAC schemes primarily employ Orthogonal Frequency Division Multiplexing (OFDM) waveforms or extended OFDM waveforms. OFDM is a multi-carrier signal composed of a set of orthogonal subcarriers. The complex amplitude of each subcarrier can be used to carry communication data, thereby achieving high data rates. Furthermore, OFDM waveforms exhibit Doppler tolerance and range-Doppler-free coupling. These characteristics are attractive for radar applications.

[0003] The resolution capability of existing ISAC systems for dense multi-target targets is related to the resolution capability of the two-dimensional spectral estimation method. In order to improve the resolution capability for dense multi-target targets, existing two-dimensional spectral estimators assume that the signal follows a known generative model and then estimate the model parameters, which has the problems of high computational complexity and unstable performance.

[0004] Therefore, existing technologies still need improvement and development. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a communication-sensing integrated multi-target detection method, device, terminal and medium to address the above-mentioned defects of the prior art. The aim is to solve the problems of high computational complexity and unstable performance in the prior art, which assumes that the signal follows a known generation model and estimates the model parameters.

[0006] The technical solution adopted by this invention to solve the problem is as follows: In a first aspect, embodiments of the present invention provide a communication-sensing integrated multi-target detection method, wherein the method includes: The receiver acquires the radio frequency analog signal, performs frequency mixing and transformation on the radio frequency analog signal, and determines the digital baseband signal. The digital baseband signal is demodulated and inversely mapped to determine the residual sensing signal; The target distance Doppler map is determined by extracting features from the perceived residual signal using a pre-trained time-frequency transformation network.

[0007] In one implementation, the radio frequency analog signal is mixed and transformed to determine a digital baseband signal, including: The radio frequency analog signal is preprocessed and carrier synchronized to determine the carrier synchronization signal; The carrier synchronization signal is mixed and converted from analog to digital to determine the digital baseband signal.

[0008] In one implementation, the carrier synchronization signal is subjected to frequency mixing and analog-to-digital conversion to determine a digital baseband signal, including: The carrier synchronization signal is orthogonally mixed to determine the analog baseband signal; The analog baseband signal is subjected to low-pass filtering and quadrature imbalance compensation to determine the analog compensation signal; The analog compensation signal is converted from analog to digital and sampled to determine the digital baseband signal.

[0009] In one implementation, demodulating and inverse mapping the digital baseband signal to determine the sensing residual signal includes: Remove the cyclic prefix of the digital baseband signal to determine the processed digital baseband signal; The processed digital baseband signal is converted into frequency domain symbols by orthogonal frequency division multiplexing to determine the initial demodulation signal; The sub-baseband signal is reconstructed based on the quadrature amplitude modulation symbols and the initial demodulated signal; The sensing residual signal is determined based on the digital baseband signal and the sub-baseband signal.

[0010] In one implementation, reconstructing the subbaseband signal based on the quadrature amplitude modulation symbol and the initial demodulated signal includes: The initial demodulated signal is subjected to inverse quadrature amplitude modulation mapping and modulation to determine the quadrature amplitude modulation symbol stream; The subbaseband signal is reconstructed based on the orthogonal amplitude modulation symbol stream.

[0011] In one implementation, reconstructing the subbaseband signal based on the quadrature amplitude modulation symbol and the initial demodulated signal includes: The initial demodulated signal is subjected to inverse quadrature amplitude modulation mapping and modulation to determine the quadrature amplitude modulation symbol stream; The subbaseband signal is reconstructed based on the orthogonal amplitude modulation symbol stream.

[0012] In one implementation method, feature extraction is performed on the perceived residual signal using a pre-trained time-frequency transform network to determine the target distance Doppler map, including: The perceived residual signal is upsampled by a two-dimensional transposed convolution to determine the first upsampled signal; The super-resolution module extracts features from the first upsampled signal to determine the super-resolution features. The super-resolution features are upsampled by a two-dimensional transposed convolution to determine a second upsampled signal, and the target distance Doppler map is determined based on the second upsampled signal.

[0013] In one implementation, the super-resolution module is constructed by stacking multiple residual modules.

[0014] In one implementation, the method for generating the radio frequency analog signal includes: The data stream to be transmitted is generated at the transmitting end through an integrated communication and sensing device; The data stream to be transmitted is subjected to quadrature amplitude modulation to determine the initial modulation signal; The initial modulation signal is orthogonally frequency-division multiplexed to determine the radio frequency analog signal.

[0015] In one implementation, quadrature amplitude modulation is performed on the data stream to be transmitted to determine an initial modulation signal, including: The data stream to be transmitted is mapped to discrete coordinate points in a complex plane to determine the orthogonal amplitude modulation symbol; The orthogonal amplitude modulation symbols are orthogonally modulated to determine the initial modulation signal.

[0016] In one implementation, orthogonal frequency division multiplexing is performed on the initial modulation signal to determine the radio frequency analog signal, including: Subcarrier mapping is performed on the initial modulation signal to determine the subcarrier signal; Perform an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal; A cyclic prefix and digital-to-analog conversion are added to the initial time-domain signal to determine the radio frequency analog signal.

[0017] In one implementation, performing an inverse fast Fourier transform on the subcarrier signal to determine an initial time-domain signal includes: The subcarrier signal is subjected to pilot symbol insertion, empty carrier filling and symbol normalization to determine the preprocessed subcarrier signal; The inverse fast Fourier transform is performed on the preprocessed subcarrier signal to determine the initial time-domain signal.

[0018] Secondly, embodiments of the present invention also provide a communication-sensing integrated multi-target detection device, wherein the communication-sensing integrated multi-target detection device includes: The baseband signal determination module is used to acquire radio frequency analog signals through the receiving end, perform frequency mixing and transformation on the radio frequency analog signals, and determine the digital baseband signal. The residual signal detection module is used to demodulate and inversely map the digital baseband signal to determine the residual signal. The distance Doppler map determination module is used to extract features from the perceived residual signal through a pre-trained time-frequency transformation network to determine the target distance Doppler map.

[0019] In one implementation, the baseband signal determination module includes: A carrier synchronization unit is used to preprocess and synchronize the radio frequency analog signal, and determine the carrier synchronization signal; The mixing and analog-to-digital conversion unit is used to perform mixing and analog-to-digital conversion on the carrier synchronization signal to determine the digital baseband signal.

[0020] In one implementation, the mixer and analog-to-digital converter unit includes: The quadrature mixing unit is used to perform quadrature mixing on the carrier synchronization signal to determine the analog baseband signal; The analog compensation unit is used to perform low-pass filtering and quadrature imbalance compensation on the analog baseband signal to determine the analog compensation signal; An analog-to-digital conversion unit is used to perform analog-to-digital conversion and sampling on the analog compensation signal to determine the digital baseband signal.

[0021] In one implementation, the residual signal determination module includes: The cyclic prefix deletion unit is used to delete the cyclic prefix of the digital baseband signal and determine the processed digital baseband signal; The initial demodulation unit is used to convert the processed digital baseband signal into frequency domain symbols through orthogonal frequency division multiplexing to determine the initial demodulation signal; The sub-baseband signal reconstruction unit is used to reconstruct the sub-baseband signal based on the quadrature amplitude modulation symbols and the initial demodulated signal; A residual sensing signal determination unit is used to determine the residual sensing signal based on the digital baseband signal and the sub-baseband signal.

[0022] In one implementation, the sub-baseband signal reconstruction unit includes: The quadrature amplitude modulation unit is used to perform quadrature amplitude modulation inverse mapping and modulation on the initial demodulated signal to determine the quadrature amplitude modulation symbol stream; The subbaseband signal sub-reconstruction unit is used to reconstruct the subbaseband signal based on the orthogonal amplitude modulation symbol stream.

[0023] In one implementation, the residual signal determination unit includes: The signal difference calculation unit is used to determine the initial sensing residual signal by subtracting the sub-baseband signal from the digital baseband signal; The filtering and coherent accumulation unit is used to filter and coherently accumulate the initial sensing residual signal to determine the sensing residual signal.

[0024] In one implementation, the distance Doppler image determination module includes: The first upsampling unit is used to upsample the perceived residual signal through a two-dimensional transposed convolution to determine the first upsampled signal; The feature extraction unit is used to extract features from the first upsampled signal through the super-resolution module to determine the super-resolution features. The super-resolution module is composed of multiple residual modules stacked together. The second upsampling unit is used to upsample the super-resolution features through a two-dimensional transposed convolution to determine a second upsampled signal, and to determine the target distance Doppler map based on the second upsampled signal.

[0025] In one embodiment, the apparatus further includes a radio frequency analog signal generation module, the radio frequency analog signal generation module comprising: A binary data generation unit is used to generate a data stream to be transmitted at the transmitting end through an integrated communication and sensing device; An initial modulation signal determination unit is used to perform quadrature amplitude modulation on the data stream to be transmitted to determine the initial modulation signal; The radio frequency analog signal determination unit is used to perform orthogonal frequency division multiplexing on the initial modulation signal to determine the radio frequency analog signal.

[0026] In one implementation, the initial modulation signal determination unit includes: The complex plane mapping unit is used to map the data stream to be transmitted into discrete coordinate points in the complex plane and determine the orthogonal amplitude modulation symbol; The quadrature amplitude modulation symbol modulation unit is used to perform quadrature modulation on the quadrature amplitude modulation symbol to determine the initial modulation signal.

[0027] In one implementation, the radio frequency analog signal determination unit includes: A subcarrier mapping unit is used to perform subcarrier mapping on the initial modulation signal to determine the subcarrier signal; The inverse fast Fourier transform unit is used to perform an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal. A prefix addition and digital-to-analog conversion unit is used to add a cyclic prefix and perform digital-to-analog conversion on the initial time-domain signal to determine the radio frequency analog signal.

[0028] In one implementation, the inverse fast Fourier transform unit includes: The subcarrier signal preprocessing unit is used to perform pilot symbol insertion, empty carrier filling and symbol normalization on the subcarrier signal to determine the preprocessed subcarrier signal. An initial time-domain signal determination unit is used to perform an inverse fast Fourier transform on the preprocessed subcarrier signal to determine the initial time-domain signal.

[0029] Thirdly, embodiments of the present invention also provide a terminal, the terminal including a memory and one or more processors; the memory stores one or more programs; the programs include instructions for executing the communication-sensing integrated multi-target detection method as described above; the processor is used to execute the programs.

[0030] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to implement any of the above-described communication-sensing integrated multi-target detection methods.

[0031] The beneficial effects of this invention are as follows: In this embodiment, the radio frequency (RF) analog signal is acquired at the receiving end, and the RF analog signal is mixed and transformed to determine the digital baseband signal; the digital baseband signal is demodulated and inversely mapped to determine the sensing residual signal; and features of the sensing residual signal are extracted using a pre-trained time-frequency transformation network to determine the target range Doppler map. Because this invention converts the RF analog signal acquired at the receiving end into a sensing residual signal, and extracts features from the sensing residual signal using a pre-trained time-frequency transformation network to obtain a super-resolution range Doppler map, there is no need for signal model parameter estimation. This results in high computational efficiency and stable noise resistance. Therefore, it effectively solves the problems of high computational complexity and unstable performance associated with existing technologies that assume the signal follows a known generation model and require parameter estimation. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart illustrating the integrated communication and sensing multi-target detection method provided in this embodiment of the invention.

[0034] Figure 2 This is a schematic diagram of the mixing conversion process provided in an embodiment of the present invention.

[0035] Figure 3 This is a schematic diagram of the mixing and analog-to-digital conversion process provided in the embodiments of the present invention.

[0036] Figure 4This is a schematic diagram of the demodulation and inverse mapping process provided in an embodiment of the present invention.

[0037] Figure 5 This is a schematic diagram of the subbaseband signal reconstruction process provided in an embodiment of the present invention.

[0038] Figure 6 This is a schematic diagram of the process for determining the residual sensing signal provided in an embodiment of the present invention.

[0039] Figure 7 This is a schematic diagram of the feature extraction process based on time-frequency transform network provided in an embodiment of the present invention.

[0040] Figure 8 This is a schematic diagram illustrating the specific implementation process of the communication-sensing integrated multi-target detection method provided in this embodiment of the invention.

[0041] Figure 9 This is a flowchart illustrating the method for generating radio frequency analog signals provided in an embodiment of the present invention.

[0042] Figure 10 This is a schematic diagram of the orthogonal amplitude modulation process provided in an embodiment of the present invention.

[0043] Figure 11 This is a schematic diagram of the orthogonal frequency division multiplexing process provided in an embodiment of the present invention.

[0044] Figure 12 This is a schematic diagram of the inverse fast Fourier transform provided in an embodiment of the present invention.

[0045] Figure 13 This is a performance comparison diagram of the high signal-to-noise ratio scenario provided in the embodiments of the present invention.

[0046] Figure 14 This is a performance comparison diagram for low signal-to-noise ratio scenarios provided in an embodiment of the present invention.

[0047] Figure 15 This is a schematic diagram of the internal modules of the communication and sensing integrated multi-target detection device provided in an embodiment of the present invention.

[0048] Figure 16 This is a schematic diagram of the terminal provided in an embodiment of the present invention. Detailed Implementation

[0049] This invention discloses a method, apparatus, terminal, and medium for integrated communication and sensing multi-target detection. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention.

[0050] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0051] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0052] Integrated Communication-Sensing (ISAC) is one of many strategies for the coexistence of radar and communications. This strategy has emerged in recent years to address the increasingly congested spectrum and the high bandwidth requirements of radar and communication systems. In an ISAC system, radar and communication share the same platform and use a common transmit waveform. Existing ISAC schemes primarily employ Orthogonal Frequency Division Multiplexing (OFDM) waveforms or extended OFDM waveforms. OFDM is a multi-carrier signal composed of a set of orthogonal subcarriers. The complex amplitude of each subcarrier can be used to carry communication data, thereby achieving high data rates. Furthermore, OFDM waveforms exhibit Doppler tolerance and range-Doppler-free coupling. These characteristics are attractive for radar applications.

[0053] The resolution capability of existing ISAC systems for dense multi-target targets is related to the resolution capability of the two-dimensional spectral estimation method. In order to improve the resolution capability for dense multi-target targets, existing two-dimensional spectral estimators assume that the signal follows a known generative model and then estimate the model parameters, which has the problems of high computational complexity and unstable performance.

[0054] To address the aforementioned shortcomings of existing technologies, this invention provides an integrated communication and sensing multi-target detection method. The method acquires a radio frequency (RF) analog signal at a receiving end, performs a frequency mixing transformation on the RF analog signal to determine a digital baseband signal, demodulates and inversely maps the digital baseband signal to determine a sensing residual signal, and extracts features from the sensing residual signal using a pre-trained time-frequency transformation network to determine the target range Doppler map. Because this invention converts the RF analog signal acquired at the receiving end into a sensing residual signal and extracts features from the sensing residual signal using a pre-trained time-frequency transformation network to obtain a super-resolution range Doppler map, it eliminates the need for signal model parameter estimation, resulting in high computational efficiency and stable noise resistance. Therefore, it effectively solves the problems of high computational complexity and unstable performance associated with existing technologies that assume the signal follows a known generative model and require parameter estimation.

[0055] Exemplary method: like Figure 1 As shown, the method includes: Step S100: Obtain the radio frequency analog signal through the receiving end, perform frequency mixing transformation on the radio frequency analog signal, and determine the digital baseband signal.

[0056] After receiving the RF analog signal from the transmitter, the receiver performs a frequency conversion by downgrading the high-frequency RF signal to a low-frequency baseband signal. The frequency conversion of the RF analog signal requires addressing carrier synchronization and image frequency suppression to ensure that the final output baseband signal is distortion-free and can be demodulated subsequently.

[0057] Frequency mixing of radio frequency analog signals mainly involves using nonlinear devices (such as mixers) to multiply the received radio frequency analog signal with the carrier signal generated by the local oscillator, achieving frequency shifting through frequency superposition / cancellation. Depending on the down-mixing objective, it is divided into single down-mixing (directly down-mixing to the baseband frequency) and double down-mixing (first down-mixing to the intermediate frequency, then down-mixing from the intermediate frequency to the baseband frequency), ultimately outputting a baseband signal containing communication / sensing information (usually two quadrature I / Q signals).

[0058] In one implementation, such as Figure 2 As shown, the radio frequency analog signal is mixed and transformed to determine the digital baseband signal, including: Step S101: Preprocess and synchronize the radio frequency analog signal to determine the carrier synchronization signal; Step S102: Perform frequency mixing and analog-to-digital conversion on the carrier synchronization signal to determine the digital baseband signal.

[0059] The received RF analog signal contains noise, adjacent frequency band interference, and subcarrier clutter, requiring preprocessing to ensure signal integrity. RF signal preprocessing yields a preprocessed signal, which includes: performing wideband RF bandpass filtering to determine the bandpass filter signal. Unlike single-carrier signals, orthogonal frequency division multiplexing (OFDM) signals have bandwidths (e.g., tens to hundreds of MHz), requiring a wideband RF bandpass filter whose passband completely covers the frequency range of the OFDM signal. Example: If receiving a 2.6GHz OFDM signal from 5G NR (100MHz bandwidth, 2600MHz center frequency), the wideband RF bandpass filter must allow signals from 2550 to 2650MHz to pass while suppressing out-of-band interference (such as other signals in the 2.5GHz band) and preventing edge subcarriers from being filtered out. After filtering, the bandpass filter signal is amplified with low noise to linearly amplify the wideband signal, thus determining the preprocessed signal. Orthogonal frequency division multiplexing (OFDM) signals have a high peak-to-average power ratio (PAPR) (typically 6-10 dB), requiring low-noise amplification with high linearity to avoid inter-carrier noise caused by nonlinear distortion. The low-noise amplification gain must be adapted to the dynamic range of the OFDM signal (avoiding signal peak over-saturation or excessively weak valleys), usually adjusted in conjunction with baseband automatic gain control to ensure stable amplitude of the mixing input signal. Furthermore, the pre-processed signal can be down-converted to an intermediate frequency (IF) to reduce the operating frequency of subsequent mixers.

[0060] Carrier synchronization is performed on the preprocessed signal to obtain the corresponding carrier synchronization signal, avoiding the introduction of carrier frequency and phase offsets, which would lead to baseband signal distortion and inter-subcarrier interference. Carrier synchronization includes frequency synchronization and phase synchronization. Frequency synchronization estimates the carrier frequency offset and adjusts the LO frequency using the preamble or pilot subcarrier in the received signal; phase synchronization estimates and compensates for the carrier phase offset using the phase information of the pilot subcarrier or data subcarrier to obtain the carrier synchronization signal.

[0061] Once the carrier synchronization signal is obtained, it can be mixed and converted from analog to digital to obtain a digital baseband signal, thus preserving the orthogonal subcarrier structure and data information of the orthogonal frequency division multiplexing signal.

[0062] In one implementation, such as Figure 3 As shown, the carrier synchronization signal is subjected to frequency mixing and analog-to-digital conversion to determine the digital baseband signal, including: Step S1021: Perform quadrature mixing on the carrier synchronization signal to determine the analog baseband signal; Step S1022: Perform low-pass filtering and quadrature imbalance compensation on the analog baseband signal to determine the analog compensation signal; Step S1023: Perform analog-to-digital conversion and sampling on the analog compensation signal to determine the digital baseband signal.

[0063] The mixing process must avoid signal nonlinear distortion and filter out unwanted components to output an analog baseband signal adapted for communication demodulation and sensing processing. In this embodiment, the analog baseband signal is obtained by multiplying the preprocessed RF signal by the I / Q channel LO (local oscillator).

[0064] For the analog baseband signal, a linear-phase finite-length unit impulse response (FIR) filter (to avoid phase distortion) is used for low-pass filtering. The cutoff frequency is equal to the bandwidth of the orthogonal frequency division multiplexing (OFDM) baseband (e.g., if the baseband bandwidth is 50MHz, the cutoff frequency is set to 50MHz). This filters out the second harmonic component (high-frequency interference) generated by mixing, resulting in a low-pass filtered signal. Compared to an infinite-length unit impulse response (IR) filter, the linear-phase characteristic of the finite-length IR filter ensures that the time delay information of the sensed echo is distortion-free (time delay error ≤10ns, corresponding to a ranging error ≤3m). DC offset and orthogonal imbalance compensation are then applied to the low-pass filtered signal. First, the DC component caused by LO leakage is eliminated by digital domain mean subtraction (averaging and canceling 1024 sampling points), resulting in a DC offset compensation signal. This prevents the DC component from affecting the baseline of the sensed signal, thus avoiding ranging deviation. Orthogonal imbalance compensation is then applied to the DC offset compensation signal. Based on the communication pilot and sensing reference signal, the imbalance parameters (amplitude deviation) and phase deviation in the DC offset compensation signal are estimated to obtain the simulated compensation signal, ensuring that the I / Q orthogonality error is ≤0.5° and guaranteeing the accuracy of sensing phase estimation.

[0065] The analog compensation signal is sampled by an analog-to-digital converter (ADC) to achieve sampling rate coordination between communication and sensing. The sampling meets the requirements of low sampling rate and low power consumption for communication baseband processing and high sampling rate and high resolution for sensing signal processing. In this embodiment, a variable sampling rate ADC is used to sample the analog compensation signal to obtain a digital baseband signal.

[0066] like Figure 1 As shown, the method further includes the following steps: Step S200: Demodulate and inversely map the digital baseband signal to determine the residual sensing signal; After demodulation and inverse mapping of the digital baseband signal, communication data can be recovered. From the recovered communication data, residual components containing target information (such as amplitude / phase distortion caused by target reflection, multipath delay differences, etc.) are separated to obtain the sensing residual signal, thus achieving physical separation between communication data recovery and sensing signal extraction.

[0067] In one implementation, such as Figure 4As shown, the digital baseband signal is demodulated and inversely mapped to determine the sensing residual signal, including: Step S201: Delete the cyclic prefix of the digital baseband signal and determine the processed digital baseband signal; Step S202: Convert the processed digital baseband signal into frequency domain symbols using orthogonal frequency division multiplexing to determine the initial demodulation signal; Step S203: Reconstruct the sub-baseband signal based on the quadrature amplitude modulation symbol and the initial demodulated signal; Step S204: Determine the sensing residual signal based on the digital baseband signal and the sub-baseband signal.

[0068] The digital baseband signal retains a cyclic prefix before the orthogonal frequency division multiplexing (OFDM) symbol to combat multipath delay and simplify time-domain synchronization. At the receiver, to extract valid data from the digital baseband signal, the cyclic prefix needs to be removed. Cyclic prefix removal requires first locating the boundary between the cyclic prefix and valid data through symbol synchronization, then cutting the cyclic prefix. It is also crucial to ensure timing alignment between communication demodulation and sensing processing to avoid communication errors or sensing ranging deviations caused by cyclic prefix removal errors. This embodiment employs a two-dimensional synchronization algorithm for symbol synchronization. The steps are as follows: Utilizing the repetition of the cyclic prefix and the tail of the valid data, an autocorrelation value is calculated. Based on the autocorrelation value, the starting position of the initial locator is determined, with the error controlled within ±2 sampling points. Combining the delay characteristics of the received RF analog signal (there is a delay difference between the boundary of the cyclic prefix of the sensing RF analog signal and the direct signal), the boundary position of the cyclic prefix of the RF analog signal (i.e., the start and end positions of the cyclic prefix) is calibrated through the cross-correlation between the direct signal and the RF analog signal. This avoids cyclic prefix removal errors caused by echo delay, which could affect sensing ranging accuracy. Based on the start and end positions of the cyclic prefix obtained through symbol synchronization, the cyclic prefix portion is removed from the initial digital baseband signal, retaining the valid data to obtain the digital baseband signal. This embodiment, through a two-dimensional synchronization algorithm, can ensure the resolution of sensing and ranging while preserving the weak signal characteristics of the radio frequency analog signal.

[0069] The residual sensing signal refers to the difference between the demodulated, inverse-mapped, and reconstructed communication signal and the original baseband signal (digital baseband signal). The residual sensing signal mainly includes the reflected signal from the target (the distorted component of the communication signal after reflection from the target) and the unrelated portion of the channel noise. It is the core processing object for the sensing side (ranging, velocity measurement, target identification). To extract the residual sensing signal, this embodiment first performs orthogonal frequency division multiplexing (OFDM) on the digital baseband signal after mixing and cyclic prefix deletion to obtain the initial demodulated signal; then, based on known orthogonal amplitude modulation symbols, it performs inverse mapping and reconstruction on the initial demodulated signal to obtain the sub-baseband signal; the residual sensing signal can be obtained by calculating the digital baseband signal and the sub-baseband signal.

[0070] The process of performing orthogonal frequency division multiplexing on the digital baseband signal to obtain the initial demodulated signal includes: performing a fast Fourier transform on the digital baseband signal to obtain a frequency domain baseband signal; performing channel estimation and channel equalization based on the pilot subcarriers at the transmitting end to obtain a channel equalization signal; and extracting subcarrier symbols based on the channel equalization signal to determine the initial demodulated signal.

[0071] In one implementation, such as Figure 5 As shown, the reconstructing of the subbaseband signal based on the quadrature amplitude modulation symbols and the initial demodulated signal includes: Step S2031: Perform orthogonal amplitude modulation inverse mapping and modulation on the initial demodulated signal to determine the orthogonal amplitude modulation symbol stream; Step S2032: Reconstruct the subbaseband signal based on the orthogonal amplitude modulation symbol stream.

[0072] Before inverse mapping, the orthogonal amplitude modulation (OAM) symbols at the transmitting end are defined based on the system protocol. Key parameters include modulation order, constellation diagram format, and constellation point amplitude or phase standards. Based on the minimum Euclidean distance criterion for the OAM symbols, the ideal constellation point to which the initial demodulated signal belongs is determined, resulting in the OAM symbol stream. The specific steps are as follows: Amplitude normalization is performed on the initial demodulated signal. If amplitude attenuation exists at the receiving end, calibration based on the known amplitude of the pilot symbols is required to ensure that the amplitude range of the initial demodulated signal matches the ideal constellation diagram. The OAM symbols are used to traverse all ideal constellation points, calculating the Euclidean distance between each point in the initial demodulated signal and the ideal constellation point. The ideal constellation point with the smallest Euclidean distance is selected as the decision result. The symbol error after the decision is calculated. If the error amplitude exceeds a threshold, the subcarrier is marked as a suspicious symbol, requiring subsequent correction through channel coding and decoding.

[0073] For the orthogonal amplitude modulation (OAM) symbol stream after the decision, it is restored to the binary bit stream of the transmitting end based on the OAM symbols, and the complex baseband signal is reconstructed based on this binary bit stream. The reconstruction steps include: regenerating frequency-domain ideal OAM symbols based on the binary bit stream and synchronizing them with the transmitting end constellation mapping (finding the ideal OAM constellation point corresponding to each group of bits based on the OAM symbols to generate frequency-domain ideal symbols); converting the reconstructed frequency-domain ideal symbols into time-domain valid data through inverse fast Fourier transform to match the multi-carrier time-domain characteristics of OAM; inserting a cyclic prefix before the time-domain valid data to generate complete OAM time-domain symbols; and concatenating the OAM symbols to obtain the reconstructed sub-baseband signal.

[0074] In one implementation, such as Figure 6 As shown, determining the sensing residual signal based on the digital baseband signal and the sub-baseband signal includes: Step S2041: Determine the initial sensing residual signal by subtracting the sub-baseband signal from the digital baseband signal; Step S2042: Filter and coherently accumulate the initial sensing residual signal to determine the sensing residual signal.

[0075] Symbol synchronization of the digital baseband and sub-baseband signals is achieved using a cyclic prefix. Then, a Costas ring is used to correct the phase shift introduced by orthogonal amplitude modulation. Simultaneously, the symbol rates and frame structures of the two signals are precisely matched in the time domain. Symbol-by-symbol subtraction is performed between the synchronized digital baseband signal and the reconstructed sub-baseband signal to obtain the initial sensing residual signal. This initial sensing residual signal contains the target scattering echo component required for sensing, channel noise, and demodulation residual error, with the target scattering echo being the primary source of the sensing residual signal.

[0076] By combining frequency domain bandpass filtering and adaptive filtering optimization, irrelevant noise and communication signal residues in the initial sensing residual signal are filtered out, while retaining the target signal frequency band components related to sensing, thus obtaining the filtered sensing residual signal. The filtered sensing residual signal is then coherently accumulated, and the target energy of multiple frames is superimposed to enhance the signal strength while simultaneously canceling random noise, thus obtaining the sensing residual signal.

[0077] like Figure 1 As shown, the method further includes the following steps: Step S300: Extract features from the perceived residual signal using a pre-trained time-frequency transformation network to determine the target distance Doppler map.

[0078] The residual sensing signal suffers from problems such as noise fluctuations and feature sparsity. In this embodiment, the sensing features (such as target reflection, Doppler frequency shift, distance information, etc.) in the residual sensing signal are automatically extracted by a time-frequency transformation network to obtain the target range Doppler map, which replaces the traditional two-dimensional spectrum estimator for estimation and improves the accuracy and robustness of sensing tasks such as target detection and parameter estimation.

[0079] Before feature extraction from the residual sensing signal using a pre-trained time-frequency transform network, the signal dimension reconstruction and standardization of the residual signal are performed. The residual sensing signal is transformed from a one-dimensional time-domain signal into a two-dimensional feature map through short-time Fourier transform and cyclic stationary feature extraction. The two-dimensional feature map is then normalized to eliminate the influence of magnitude. Commonly used methods are Z-Score normalization or Min-Max normalization.

[0080] In one implementation, such as Figure 7 As shown, feature extraction of the perceived residual signal is performed using a pre-trained time-frequency transform network to determine the target distance Doppler map, including: Step S301: Upsample the perceived residual signal by two-dimensional transposed convolution to determine the first upsampled signal; Step S302: Extract features from the first upsampled signal using the super-resolution module to determine the super-resolution features; Step S303: Upsample the super-resolution features by two-dimensional transposed convolution to determine the second upsampled signal, and determine the target distance Doppler map based on the second upsampled signal.

[0081] Because the residual sensing signal has the problem of signal sparsity, such as Figure 8 As shown, the time-frequency transformation network first upsamples the perceived residual signal through a 2D transposed convolution to improve its resolution and provide more details for subsequent feature extraction, resulting in a first upsampled signal. This first upsampled signal is then input into the super-resolution module for feature extraction, yielding super-resolution features. These super-resolution features are constructed from multiple stacked residual modules, which are the residual modules found in ResNet, connected by skip connections. The super-resolution features are then upsampled again through a 2D transposed convolution to obtain a second upsampled signal that more closely approximates the real-world situation, which is used as the target distance Doppler map.

[0082] In one implementation, such as Figure 9 As shown, the method for generating the radio frequency analog signal includes: Step H100: Generate the data stream to be transmitted at the transmitting end through the integrated communication and sensing device; Step H200: Perform quadrature amplitude modulation on the data stream to be transmitted to determine the initial modulation signal; Step H300: Perform orthogonal frequency division multiplexing on the initial modulation signal to determine the radio frequency analog signal.

[0083] The integrated communication sensing device encodes the communication data to be transmitted at the transmitting end to improve the signal's anti-interference capability. Next, it performs interleaving on the encoded data to avoid consecutive bit errors. Then, it performs serial-to-parallel conversion, splitting the high-speed serial data stream into multiple low-speed parallel data streams. Finally, according to the orthogonal frequency division multiplexing (OFDM) rules, the different parallel data streams are allocated to different orthogonal subcarrier groups to obtain the data stream to be transmitted.

[0084] For each subcarrier data stream allocated according to the orthogonal frequency division multiplexing (OFDM) rules, orthogonal amplitude modulation (OAM) is performed to obtain the initial modulated signal, realizing the mapping from binary data to complex baseband symbols. OAM carries information by jointly adjusting the amplitude and phase of the carrier; for example, 16-bit OAM can map 4 bits of data, and 64-bit OAM can map 6 bits of data. The initial modulated signal output after modulation is a multi-parallel OAM complex baseband symbol stream, with each path corresponding to one OAM subcarrier.

[0085] For multiple parallel initial modulation signals, they are synthesized into a unified orthogonal frequency division multiplexing time-domain baseband signal, i.e., radio frequency analog signal, through orthogonal frequency division multiplexing modulation, while ensuring subcarrier orthogonality and adapting to sensing requirements.

[0086] In one implementation, such as Figure 10 As shown, the data stream to be transmitted is subjected to quadrature amplitude modulation to determine the initial modulation signal, including: Step H201: Map the data stream to be transmitted to discrete coordinate points in the complex plane and determine the orthogonal amplitude modulation symbol; Step H202: Perform quadrature modulation on the quadrature amplitude modulation symbol to determine the initial modulation signal.

[0087] Quadrature amplitude modulation (QAM) maps a binary data stream to be transmitted as discrete constellation points on the complex plane. By simultaneously adjusting the amplitudes of the in-phase (I) and quadrature (Q) carrier waves, high bandwidth utilization is achieved. In this embodiment, the data stream to be transmitted is mapped to discrete coordinate points on the complex plane using a preset constellation diagram rule, resulting in QAM symbols. If the QAM symbols generated by the mapping are transmitted directly, symbol tailing will occur due to channel bandwidth limitations, causing inter-symbol interference. Therefore, baseband shaping filtering is required to convert the discrete symbols into continuous baseband waveforms.

[0088] For the quadrature amplitude modulation symbol converted into a continuous baseband waveform, it is split into an in-phase branch (I(t)) and a quadrature branch (Q(t)). The digital signals are then converted to analog signals by digital-to-analog converters. These analog signals are then mixed with the two orthogonal carriers and superimposed to obtain the final initial modulation signal. Since the initial modulation signal has low power, it can be amplified to the target power by a power amplifier. Simultaneously, a bandpass filter is used to filter out harmonic components generated during modulation, ensuring the signal conforms to the spectral specifications.

[0089] In one implementation, such as Figure 11 As shown, the initial modulation signal is orthogonally frequency-division multiplexed to determine the radio frequency analog signal, including: Step H301: Perform subcarrier mapping on the initial modulation signal to determine the subcarrier signal; Step H302: Perform inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal; Step H303: Add a cyclic prefix and perform digital-to-analog conversion to the initial time-domain signal to determine the radio frequency analog signal.

[0090] Orthogonal Frequency Division Multiplexing (OFDM) modulation distributes multiple orthogonal amplitude modulation (AEM) complex baseband symbols onto mutually orthogonal subcarriers, and synthesizes a single-channel time-domain OFDM signal using inverse fast Fourier transform (IFFT). This achieves the dual goals of efficient frequency domain resource utilization and resistance to multipath interference. For the initial modulated signal of AEM, it is split from the serial sub-baseband symbol into multiple parallel symbols, which are then assigned to different subcarriers to obtain subcarrier signals. An inverse fast Fourier transform is performed on each subcarrier signal to convert the multiple subcarrier symbols in the frequency domain into a single-channel OFDM symbol in the time domain, obtaining the initial time-domain signal and ensuring no interference between different subcarriers in the time domain. The OFDM symbol (i.e., the initial time-domain signal) exhibits a trailing waveform at the end; direct transmission of this waveform can lead to overlap between adjacent OFDM symbols. Simultaneously, multipath propagation in the wireless channel can cause the received signal to contain delayed reflection components, further exacerbating interference. Therefore, a cyclic prefix is ​​added to the initial time-domain signal to address this issue. At the same time, the initial time-domain signal with the added cyclic prefix is ​​converted from digital to analog to generate an analog signal, namely a radio frequency analog signal.

[0091] In one implementation, such as Figure 12 As shown, performing an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal includes: Step H3021: Perform pilot symbol insertion, empty carrier filling, and symbol normalization on the subcarrier signal to determine the preprocessed subcarrier signal; Step H3022: Perform an inverse fast Fourier transform on the preprocessed subcarrier signal to determine the initial time-domain signal.

[0092] To ensure the orthogonality of the subsequent inverse fast Fourier transform (IFT), the demodulation accuracy at the receiver, and the effectiveness of the sensed signal, this embodiment performs preprocessing operations on the subcarrier signal before performing the IFT, including pilot symbol insertion, empty carrier filling, and symbol normalization. First, empty carrier filling is performed on the subcarrier signal to clarify the functional boundaries of the subcarriers and avoid interference from non-data subcarrier signals on the orthogonality of the IFT. Then, pilot symbols are inserted into the filled subcarrier signal to achieve channel estimation and sensed synchronization at the receiver. Since the amplitudes of the data symbols and pilot symbols in orthogonal amplitude modulation (OAM) differ, directly inputting them into the IFT would lead to an increased peak-to-average power ratio (PAPR) in the time domain and uneven power distribution among different subcarriers. Symbol normalization is used to process the signal after pilot symbol insertion, unifying the amplitude scale to obtain a preprocessed subcarrier signal. This preprocessed subcarrier signal is then subjected to the IFT to obtain the initial time-domain signal.

[0093] Figure 13 and Figure 14 This study demonstrates a performance comparison between the integrated communication and sensing multi-target detection method and other two-dimensional algorithms. Among them, Figure 13 For cases with high signal-to-noise ratio (20dB). Figure 13 (a) is the truth graph. Figure 13 (b) is the periodogram method. Figure 13 (c) represents the Capon method. Figure 13 (d) represents the MUSIC method. Figure 14 (e) represents the method proposed in this invention. Figure 14 For cases with low signal-to-noise ratio (0dB). Figure 14 (a) is the truth graph. Figure 14 (b) is the periodogram method. Figure 14 (c) represents the Capon method. Figure 14 (d) represents the MUSIC method. Figure 15 (e) illustrates the method proposed in this invention. The communication-sensing integrated multi-target detection method proposed in this invention exhibits better resolution and detection capability for weak frequencies, and can clearly distinguish closely spaced frequency components even at a signal-to-noise ratio of 0 dB. The periodogram method suffers from high sidelobes and low resolution. At a signal-to-noise ratio of 20 dB, neither the MUSIC method nor the Capon method can detect two weak frequencies, namely (-0.3, -0.277) and (-0.16, -0.26), and their resolution performance drops significantly when the signal-to-noise ratio decreases to 0 dB.

[0094] Based on the above embodiments, the present invention also provides a communication-sensing integrated multi-target detection device, such as... Figure 16 As shown, the device includes: The baseband signal determination module 01 is used to acquire the radio frequency analog signal through the receiving end, perform frequency mixing transformation on the radio frequency analog signal, and determine the digital baseband signal. The residual signal determination module 02 is used to demodulate and inversely map the digital baseband signal to determine the residual signal. The distance Doppler map determination module 03 is used to extract features from the perceived residual signal through a pre-trained time-frequency transformation network to determine the target distance Doppler map.

[0095] In one implementation, the baseband signal determination module 01 includes: A carrier synchronization unit is used to preprocess and synchronize the radio frequency analog signal, and determine the carrier synchronization signal; The mixing and analog-to-digital conversion unit is used to perform mixing and analog-to-digital conversion on the carrier synchronization signal to determine the digital baseband signal.

[0096] In one implementation, the mixing and analog-to-digital conversion unit includes: The quadrature mixing unit is used to perform quadrature mixing on the carrier synchronization signal to determine the analog baseband signal; The analog compensation unit is used to perform low-pass filtering and quadrature imbalance compensation on the analog baseband signal to determine the analog compensation signal; An analog-to-digital conversion unit is used to perform analog-to-digital conversion and sampling on the analog compensation signal to determine the digital baseband signal.

[0097] In one implementation, the residual signal determination module 02 includes: The cyclic prefix deletion unit is used to delete the cyclic prefix of the digital baseband signal and determine the processed digital baseband signal; The initial demodulation unit is used to convert the processed digital baseband signal into frequency domain symbols through orthogonal frequency division multiplexing to determine the initial demodulation signal; The sub-baseband signal reconstruction unit is used to reconstruct the sub-baseband signal based on the quadrature amplitude modulation symbols and the initial demodulated signal; A residual sensing signal determination unit is used to determine the residual sensing signal based on the digital baseband signal and the sub-baseband signal.

[0098] In one implementation, the sub-baseband signal reconstruction unit includes: The quadrature amplitude modulation unit is used to perform quadrature amplitude modulation inverse mapping and modulation on the initial demodulated signal to determine the quadrature amplitude modulation symbol stream; The subbaseband signal sub-reconstruction unit is used to reconstruct the subbaseband signal based on the orthogonal amplitude modulation symbol stream.

[0099] In one implementation, the residual signal determination unit includes: The signal difference calculation unit is used to determine the initial sensing residual signal by subtracting the sub-baseband signal from the digital baseband signal; The filtering and coherent accumulation unit is used to filter and coherently accumulate the initial sensing residual signal to determine the sensing residual signal.

[0100] In one implementation, the distance Doppler image determination module 03 includes: The first upsampling unit is used to upsample the perceived residual signal through a two-dimensional transposed convolution to determine the first upsampled signal; The feature extraction unit is used to extract features from the first upsampled signal through the super-resolution module to determine the super-resolution features. The super-resolution module is composed of multiple residual modules stacked together. The second upsampling unit is used to upsample the super-resolution features through a two-dimensional transposed convolution to determine a second upsampled signal, and to determine the target distance Doppler map based on the second upsampled signal.

[0101] In one implementation, the apparatus further includes a radio frequency analog signal generation module, the radio frequency analog signal generation module comprising: A binary data generation unit is used to generate a data stream to be transmitted at the transmitting end through an integrated communication and sensing device; An initial modulation signal determination unit is used to perform quadrature amplitude modulation on the data stream to be transmitted to determine the initial modulation signal; The radio frequency analog signal determination unit is used to perform orthogonal frequency division multiplexing on the initial modulation signal to determine the radio frequency analog signal.

[0102] In one implementation, the initial modulation signal determination unit includes: The complex plane mapping unit is used to map the data stream to be transmitted into discrete coordinate points in the complex plane and determine the orthogonal amplitude modulation symbol; The quadrature amplitude modulation symbol modulation unit is used to perform quadrature modulation on the quadrature amplitude modulation symbol to determine the initial modulation signal.

[0103] In one implementation, the radio frequency analog signal determination unit includes: A subcarrier mapping unit is used to perform subcarrier mapping on the initial modulation signal to determine the subcarrier signal; The inverse fast Fourier transform unit is used to perform an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal. A prefix addition and digital-to-analog conversion unit is used to add a cyclic prefix and perform digital-to-analog conversion on the initial time-domain signal to determine the radio frequency analog signal.

[0104] In one implementation, the inverse fast Fourier transform unit includes: The subcarrier signal preprocessing unit is used to perform pilot symbol insertion, empty carrier filling and symbol normalization on the subcarrier signal to determine the preprocessed subcarrier signal. An initial time-domain signal determination unit is used to perform an inverse fast Fourier transform on the preprocessed subcarrier signal to determine the initial time-domain signal.

[0105] Based on the above embodiments, the present invention also provides a terminal, the principle block diagram of which can be as follows: Figure 16 As shown, the terminal includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a communication-sensing integrated multi-target detection method. The display screen can be a liquid crystal display (LCD) or an e-ink display.

[0106] Those skilled in the art will understand that ​ The schematic diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the terminal to which the present invention is applied. A specific terminal may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0107] In one implementation, the terminal's memory stores one or more programs, and these programs are configured to be executed by one or more processors, and the programs contain instructions for performing a communication-sensing integrated multi-target detection method.

[0108] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0109] In summary, this invention discloses an integrated communication and sensing multi-target detection method, device, terminal, and medium. The method acquires a radio frequency analog signal at a receiving end, performs a frequency mixing transformation on the radio frequency analog signal to determine a digital baseband signal, demodulates and inversely maps the digital baseband signal to determine a sensing residual signal, and extracts features from the sensing residual signal using a pre-trained time-frequency transformation network to determine the target range Doppler map. Because this invention converts the radio frequency analog signal acquired at the receiving end into a sensing residual signal and extracts features from the sensing residual signal using a pre-trained time-frequency transformation network to obtain a super-resolution range Doppler map, it eliminates the need for signal model parameter estimation, resulting in high computational efficiency and stable noise resistance. Therefore, it effectively solves the problems of high computational complexity and unstable performance associated with existing technologies that assume the signal follows a known generation model and require parameter estimation.

[0110] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A multi-target detection method integrating communication and sensing, characterized in that, The method includes: The receiver acquires the radio frequency analog signal, performs frequency mixing and transformation on the radio frequency analog signal, and determines the digital baseband signal. The digital baseband signal is demodulated and inversely mapped to determine the residual sensing signal; The target distance Doppler map is determined by extracting features from the perceived residual signal using a pre-trained time-frequency transformation network.

2. The integrated communication and sensing multi-target detection method according to claim 1, characterized in that, The radio frequency analog signal is mixed and transformed to determine the digital baseband signal, including: The radio frequency analog signal is preprocessed and carrier synchronized to determine the carrier synchronization signal; The carrier synchronization signal is mixed and converted from analog to digital to determine the digital baseband signal.

3. The integrated communication and sensing multi-target detection method according to claim 2, characterized in that, The carrier synchronization signal is mixed and converted from analog to digital to determine the digital baseband signal, including: The carrier synchronization signal is orthogonally mixed to determine the analog baseband signal; The analog baseband signal is subjected to low-pass filtering and quadrature imbalance compensation to determine the analog compensation signal; The analog compensation signal is converted from analog to digital and sampled to determine the digital baseband signal.

4. The integrated communication and sensing multi-target detection method according to claim 1, characterized in that, Demodulating and inverse mapping the digital baseband signal to determine the sensing residual signal includes: Remove the cyclic prefix of the digital baseband signal to determine the processed digital baseband signal; The processed digital baseband signal is converted into frequency domain symbols by orthogonal frequency division multiplexing to determine the initial demodulation signal; The sub-baseband signal is reconstructed based on the quadrature amplitude modulation symbols and the initial demodulated signal; The sensing residual signal is determined based on the digital baseband signal and the sub-baseband signal.

5. The integrated communication and sensing multi-target detection method according to claim 4, characterized in that, Reconstructing the subbaseband signal based on the quadrature amplitude modulation symbols and the initial demodulated signal includes: The initial demodulated signal is subjected to inverse quadrature amplitude modulation mapping and modulation to determine the quadrature amplitude modulation symbol stream; The subbaseband signal is reconstructed based on the orthogonal amplitude modulation symbol stream.

6. The integrated communication and sensing multi-target detection method according to claim 4, characterized in that, Determining the sensing residual signal based on the digital baseband signal and the sub-baseband signal includes: The initial sensing residual signal is determined by subtracting the sub-baseband signal from the digital baseband signal. The initial sensing residual signal is filtered and coherently accumulated to determine the sensing residual signal.

7. The integrated communication and sensing multi-target detection method according to claim 1, characterized in that, Feature extraction of the perceived residual signal is performed using a pre-trained time-frequency transform network to determine the target distance Doppler map, including: The perceived residual signal is upsampled by a two-dimensional transposed convolution to determine the first upsampled signal; The super-resolution module extracts features from the first upsampled signal to determine the super-resolution features. The super-resolution features are upsampled by a two-dimensional transposed convolution to determine a second upsampled signal, and the target distance Doppler map is determined based on the second upsampled signal.

8. The integrated communication and sensing multi-target detection method according to claim 7, characterized in that, The super-resolution module is composed of multiple residual modules stacked together.

9. The integrated communication and sensing multi-target detection method according to claim 1, characterized in that, The method for generating the radio frequency analog signal includes: The data stream to be transmitted is generated at the transmitting end through an integrated communication and sensing device; The data stream to be transmitted is subjected to quadrature amplitude modulation to determine the initial modulation signal; The initial modulation signal is orthogonally frequency-division multiplexed to determine the radio frequency analog signal.

10. The integrated communication and sensing multi-target detection method according to claim 9, characterized in that, Performing quadrature amplitude modulation on the data stream to be transmitted to determine the initial modulation signal includes: The data stream to be transmitted is mapped to discrete coordinate points in a complex plane to determine the orthogonal amplitude modulation symbol; The orthogonal amplitude modulation symbols are orthogonally modulated to determine the initial modulation signal.

11. The communication-sensing integrated multi-target detection method according to claim 9, characterized in that, Orthogonal frequency division multiplexing is performed on the initial modulation signal to determine the radio frequency analog signal, including: Subcarrier mapping is performed on the initial modulation signal to determine the subcarrier signal; Perform an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal; A cyclic prefix and digital-to-analog conversion are added to the initial time-domain signal to determine the radio frequency analog signal.

12. The integrated communication and sensing multi-target detection method according to claim 11, characterized in that, Performing an inverse fast Fourier transform on the subcarrier signal to determine the initial time-domain signal includes: The subcarrier signal is subjected to pilot symbol insertion, empty carrier filling and symbol normalization to determine the preprocessed subcarrier signal; The inverse fast Fourier transform is performed on the preprocessed subcarrier signal to determine the initial time-domain signal.

13. A communication-sensing integrated multi-target detection device, characterized in that, The device includes: The baseband signal determination module is used to acquire radio frequency analog signals through the receiving end, perform frequency mixing and transformation on the radio frequency analog signals, and determine the digital baseband signal. The residual signal detection module is used to demodulate and inversely map the digital baseband signal to determine the residual signal. The distance Doppler map determination module is used to extract features from the perceived residual signal through a pre-trained time-frequency transformation network to determine the target distance Doppler map.

14. A terminal, characterized in that, The terminal includes a memory and one or more processors; the memory stores one or more programs; the programs contain instructions for executing the communication-sensing integrated multi-target detection method as described in any one of claims 1-12; the processors are used to execute the programs.

15. A computer-readable storage medium storing a plurality of instructions thereon, characterized in that, The instructions are loaded and executed by the processor to implement the steps of the communication-sensing integrated multi-target detection method according to any one of claims 1-12.

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