Committee-inductance integrated waveform design method based on multiple pulse repetition frequencies

Abstract

The invention provides a waveform design method of integrated sensing and communications (ISAC) based on multiple pulse repetition frequencies (PRF), and aims to solve the problem of distance ambiguity of an ISAC system, improve the accuracy of the waveform design of the ISAC system, improve the accuracy of the waveform design of the ISAC system, improve the accuracy of the waveform design of the ISAC system, and improve the accuracy of the waveform design of the ISAC system, and improve the accuracy of the waveform design of the ISAC system. The method comprises the following steps: firstly, a full duplex ISAC node respectively transmits different PRF waveforms in a plurality of coherent processing intervals (CPIs), and under each PRF, a sensing signal with a fixed length and a communication symbol with a variable length are sequentially transmitted; secondly, the full-duplex ISAC node knows the transmitted sensing waveform and carries out matched filtering on the target echo; thirdly, full-duplex self-interference and noise are reduced through pulse-Doppler processing; and finally, when all CPIs detect the target, obtaining the target apparent time delay in each CPI according to the distance-Doppler matrix, solving the real time delay in combination with the remainder theorem, and estimating the real distance of the target. The waveform method designed by the invention has the capability of resisting range ambiguity, remarkably expands the maximum non-ambiguity range, and improves the detection probability and the distance estimation precision of a long-distance target.

Description

Technical Field

[0001] The invention belongs to a waveform design method, and in particular relates to a synaesthesia integrated waveform design method based on multiple pulse repetition frequencies and anti-distance ambiguity in a synaesthesia integrated system. Background Art

[0002] As the next generation of mobile communication system, 6G is required to have interconnected perception capabilities in addition to communication capabilities. The future 6G system will have higher frequency bands, larger bandwidths, and denser large-scale antenna array distribution to integrate wireless signal perception and communication capabilities, further enhancing the collaboration capabilities between systems. Integrated Sensing and Communications (ISAC) is one of the key scenarios of 6G. The research focus is to design a dual-function waveform that can achieve perception and communication through shared signaling resources.

[0003] Since 6G has more relaxed frequency band, bandwidth, and antenna conditions, the radar system can be absorbed into the ISAC system for ISAC waveform design. Among them, the pulse-Doppler radar system is used to embed communication symbols to form the ISAC system because of its super long-range perception capability. The pulse-Doppler radar performs ranging based on a single pulse repetition interval (Pulse Repetition Interval, PRI) echo delay. At this time, the selection of the pulse repetition frequency (Pulse Repetition Frequency, PRF) is particularly important. It needs to meet the requirements of distance, speed area coverage and resolution, which involves a trade-off between the maximum unambiguous distance and the maximum unambiguous speed.

[0004] PRF is divided into low, medium and high frequency bands. Low PRF corresponds to a larger PRI, and there is no distance ambiguity within the maximum range, but it cannot guarantee that the speed is not ambiguous; medium PRF has good all-round coverage of the target, but there will be ambiguity in both the distance and speed ranges; high PRF can not only obtain a wider clutter-free area in the frequency domain to ensure that the speed is not ambiguous, but also increase the number of accumulated pulses within a coherent processing interval (CPI), thereby improving the detection signal-to-noise ratio, but it cannot avoid distance ambiguity. Since speed is crucial to target tracking and needs to be accurately measured, PD radars usually choose high PRFs, which will cause PD radars to often have distance ambiguity.

[0005] Distance ambiguity is caused by the echo delay of distant targets exceeding the measurable range of the PRI, which is due to the defects of the radar ranging system. The radar measures the distance within a PRI based on the delay between the transmitted signal and the echo. When the target is close, the echo arrives before the next PRI transmits the signal, and accurate distance measurement can be achieved at this time; when the target is far away, the echo returns after passing through multiple PRIs. At this time, the radar misjudges that the target appears in the current PRI, and the real delay is folded into a PRI range, resulting in a serious decrease in ranging accuracy as the number of PRIs delayed by the echo increases, resulting in distance ambiguity. Therefore, when designing the ISAC waveform, it is necessary to ensure both communication performance, such as transmission rate, and perception performance, such as ranging accuracy. This requires effective distance deambiguation of the measured ambiguous distance to achieve more accurate target distance estimation.

[0006] In order to solve the problem of distance ambiguity, the present invention designs a synaesthesia integrated waveform design method based on multiple pulse repetition frequencies. By transmitting different PRFs at multiple CPIs, the folded delay in each PRF is obtained, and the unfolded delay is solved by combining the remainder theorem, and then the real distance of the target is estimated based on the unfolded delay. The proposed waveform design can effectively improve the distance ambiguity problem, expand the maximum unambiguous distance range, improve the detection probability and distance estimation accuracy of long-distance targets, and further improve the performance of the ISAC system. Summary of the invention

[0007] The purpose of the present invention is to provide a synaesthesia integrated waveform design method based on multiple pulse repetition frequencies under the ISAC system, which can improve the distance ambiguity problem caused by long-distance targets, expand the maximum unambiguous distance range, and improve the detection probability and distance estimation accuracy of long-distance targets.

[0008] The invention discloses a synaesthesia integrated waveform design method based on multiple pulse repetition frequencies, which specifically comprises the following steps:

[0009] Step 1: Construct a synaesthesia integrated transmission signal with I pulse repetition frequency. The specific process is as follows:

[0010] The ISAC transmits a waveform of I PRF at I consecutive CPIs, and the PRF vector is F = [F1, F2, ..., F I ], and its corresponding pulse repetition interval (PRI) is In the i-th CPI, i=1,2,…,I, there exists T CPI =K i T i , where T CPI Indicates the duration of CPI, K i Indicates that the PRF in this CPI is Fi The ISAC transmission waveform is designed within each CPI, and the sensing signal is a linear frequency modulation (LFM) wave with a fixed duration of T. p ; The communication signal is a symbol modulated by Phase Shift Keying (PSK), and its length varies with T i Change to T i -T p The transmitted signal x(t) at the full-duplex ISAC node is expressed as:

[0011]

[0012] Among them, x i,k (t) represents the transmission signal of the kth PRI of the i-th CPI, expressed as:

[0013]

[0014] Among them, T c represents the sampling interval, denote the perceived signal power and the communication signal power respectively, c[n]=exp(jπn 2 / N), n=0,1,…,N-1 represents the fast time code corresponding to LFM, and its length is s i,k [j],j=0,1,…,J i -1 represents the i-th CPI, k-th PRI, j-th communication symbol, k = 0, 1, ..., K i -1, length is Then the number of range gates for the i-th PRF is N+J i , ψ(t) represents the bandwidth B = 1 / T c The Nyquist waveform.

[0015] Step 2: The full-duplex ISAC node obtains the echo signal of the range-ambiguous target after several PRIs. The specific process is as follows:

[0016] After the transmitted signal in step 1 is reflected by the target, the received signal y(t) at the full-duplex ISAC node is expressed as:

[0017]

[0018] Where α represents the complex channel coefficient of the target reflection path, β represents the complex channel coefficient of full-duplex self-interference, and f d represents the Doppler shift of the target, Indicates the transmitted signal after several PRIs. Represents the apparent delay, which is different from the real delay τs The relationship between d represents the number of PRIs that the transmitted signal is delayed to return, d = 1, 2, ..., K i , βx(t) represents the self-interference caused by full-duplex, and n(t) represents the channel noise.

[0019] Ignore the phase changes that do not constitute a cycle, that is, According to step 1, the transmitted signal x of the kth PRI of the i-th CPI i,k (t), the received signal y of the kth PRI of the i-th CPI i,k (t) is expressed as:

[0020]

[0021] The actual delay τ due to distance ambiguity s It is folded to different degrees at each PRF. For example, it is folded into the apparent delay at the i-th PRF. The distance gate where the real delay is located is represented by n τ =round(Bτ s ), round(·) indicates the nearest integer operation, and the range gate corresponding to the apparent delay under the i-th PRF is The distance gate n where the real delay is located τ The distance gate where the apparent delay is located The relationship is:

[0022]

[0023] The received signal y of the kth PRI of the i-th CPI i,k (t) is represented by the vector y i,k The form is expressed as:

[0024]

[0025] where x i,k represents the emission vector, Indicates that after n τ,i The transmitted vector after unit time intervals, n i,k represents a noise vector and any element n i,k [·] all satisfy n i,k [·]~CN(0,N0), N0 represents the noise power spectrum density, p represents the power vector of all pulse repetition periods in the i-th CPI, r i,k is the fast time code vector c corresponding to LFM and J i Communication symbols i,k [·] composed of a vector, represents the delayed p, represents the delayed ri,k ,at the same time:

[0026]

[0027] in, means (N+J i )×1 column vector of all ones.

[0028] For the received vector y i,k Using modern filters to improve the self-interference problem of full-duplex ISAC nodes, the residual self-interference is a random signal proportional to the transmitted signal power. The received signal after filtering It is expressed as:

[0029]

[0030] Among them, ∈ represents the degree of elimination of full-duplex self-interference, z i,k =[z i,k [0],…,z i,k [N+J i ]] T represents the residual self-interference vector and represents the Hadamard product.

[0031] Step 3: Get the value from step 2 Perform matched filtering to filter out random communication signals that affect perception when distance ambiguity occurs, thereby improving the perceived signal-to-interference ratio. The specific process is as follows:

[0032] When the target is far away and the distance is ambiguous, the echo arrives after several PRIs. At this time, only the sent signal and the received signal perception part can match. Received signal perception vector It can be expressed as:

[0033]

[0034] in, It is a vector composed of the fast time code vector c corresponding to LFM and zero value, expressed as:

[0035]

[0036] Therefore, in order to eliminate the influence of random communication symbols on the matching results, the ISAC matching filter h i,k Designed as the sensing part of the original waveform, it is expressed as:

[0037]

[0038] In the kth PRI of the ith CPI, k=d,d+1,…,K i-1, the result of performing matched filtering It is expressed as:

[0039]

[0040] in, express Middle elements, * indicates a convolution operation.

[0041] In the i-th CPI, K i with the same PRFF i The pulse matching filter results are aligned according to the range gate to form a matching filter result matrix It is expressed as:

[0042]

[0043] in, For the general A vector written as columns,

[0044] In the kth PRI, when Corresponding to the target apparent delay The corresponding range gate under the i-th PRF Place, that is hour, The range gate corresponding to the target's true distance The peak value is obtained at It is expressed as:

[0045]

[0046] in,(·) H represents the conjugate transpose, x i,k,r 、z i,k and n i,k are the results of the sensing part of the transmitted signal, self-interference and noise passing through the matched filter, expressed as:

[0047]

[0048] Among them, when the perceived signal power and communication signal power When fixed, i is a constant, expressed as:

[0049]

[0050] Step 4: The matched filtering result matrix obtained in step 3 Pulse-Doppler processing is performed to reduce full-duplex self-interference and noise, and further enhance the perceived signal-to-interference ratio. The specific process is as follows:

[0051] right No. Perform Fast Fourier Transform (FFT) on the column to obtain the vector after FFT for:

[0052]

[0053] Among them, the vector The calculation method for each element in is:

[0054]

[0055] Will The vectors of each column FFT are combined into a range-Doppler matrix It is expressed as:

[0056]

[0057] When q′ corresponds to the target Doppler frequency shift f d The corresponding Doppler gate At q′=q, at the same time Range-Doppler Matrix Get the peak value, the peak It is expressed as:

[0058]

[0059] in, and They represent the results of pulse-Doppler processing of the perceived part of the transmitted signal, self-interference and noise. The perceived part of the transmitted signal is amplified by K i -d times.

[0060] I CPI will get I range-Doppler matrix Find each The range-Doppler gate where the peak is located performs target detection. When a target exists, the range-Doppler matrix The peak value is When there is no target, the range-Doppler matrix The peak value is a random number The hypothesis test is expressed as:

[0061]

[0062] In a linear detector, the envelope The false alarm probability P can be obtained FA and the detection probability P D , expressed as:

[0063]

[0064] in, represents the detection threshold within the i-th CPI. After the false alarm probability is constant, can be solved as:

[0065]

[0066] Step 5: After the target is detected under all the PRFs in step 4, the apparent delay under multiple PRFs is combined with the remainder theorem to perform fuzzy distance resolution. The specific algorithm flow is as follows:

[0067] Use the remainder theorem to estimate the distance gate where the actual delay is located It is expressed as:

[0068]

[0069] Among them, the inverse element η i It can be obtained by the extended Euclidean algorithm, γ i It represents the product of the number of other I-1 PRF range gates except the number of the i-th PRF range gate, expressed as:

[0070]

[0071] The true distance to the unfolded target is estimated as:

[0072]

[0073] Estimated distance The real distance R real The root mean square error (RMSE) is expressed as:

[0074]

[0075] After using multiple PRFs, the maximum unambiguous range is extended to:

[0076]

[0077] Step 6: Power constraint for a single PRI in step 1. The specific process is as follows:

[0078] The maximum power within a single pulse repetition period of the i-th CPI is set to in, Represent the perceived signal power and the communication signal power respectively. If the communication receiver remains stationary, the ISAC signal y received by the communication receiver c (t) is expressed as:

[0079] y c (t)=hx(t)+n(t),0≤t≤IT CPI

[0080] For a single PRF waveform, the maximum transmission rate within the i-th CPI is:

[0081]

[0082] Therefore, for the multiple PRF (I) waveform, the average maximum transmission rate is calculated as:

[0083]

[0084] Beneficial Effects

[0085] This method uses a full-duplex ISAC node to transmit multiple pulse repetition periods within a coherent processing interval (CPI). In each pulse repetition period, the perception signal and communication symbol are transmitted in turn. In multiple CPIs, by changing the length of the communication symbol, a transmission signal with multiple PRFs is formed. Secondly, the perception part of the known transmission signal of the full-duplex ISAC node is used to match filter the echo of the range-ambiguous target, thereby avoiding the influence of random communication symbols on perception. Thirdly, the full-duplex self-interference and noise are reduced by pulse-Doppler processing, thereby enhancing the perception signal-to-interference ratio. On this basis, a fixed threshold is used for target detection in each CPI. Finally, when all CPIs detect the target, the peak is found in the range-Doppler matrix obtained after pulse-Doppler processing to obtain the target apparent delay in each CPI, and the real delay is solved by combining the remainder theorem to estimate the real distance of the target.

[0086] The waveform of the multiple pulse repetition frequency designed in the present invention has the characteristic of resisting distance ambiguity, can expand the maximum unambiguous distance range, improve the detection probability and distance estimation accuracy of long-distance targets, and lay a good foundation for the widespread application of ISAC systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 Schematic diagram of synaesthesia integrated waveform based on multiple pulse repetition frequencies.

[0088] Figure 2 The present invention provides a specific implementation process for resolving distance ambiguity based on synaesthesia integrated waveform with multiple pulse repetition frequencies. Specific implementation plan

[0089] The purpose of the present invention is to provide a synaesthesia integrated waveform design method with multiple pulse repetition frequencies under the ISAC system, which can improve the distance ambiguity problem in the ISAC system, expand the maximum unambiguous distance range, and improve the detection probability and distance estimation accuracy of long-distance targets.

[0090] The invention discloses a synaesthesia integrated waveform design method based on multiple pulse repetition frequencies, which specifically comprises the following steps:

[0091] Step 1: Construct a synaesthesia integrated transmission signal with I pulse repetition frequency. The specific process is as follows:

[0092] The ISAC transmits a waveform of I PRF at I consecutive CPIs, and the PRF vector is F = [F1, F2, ..., F I ], and its corresponding pulse repetition interval (PRI) is In the i-th CPI, i=1,2,…,I, there exists T CPI =K i T i , where T CPI Indicates the duration of CPI, K i Indicates that the PRF in this CPI is F i The ISAC transmission waveform is designed within each CPI, and the sensing signal is a linear frequency modulation (LFM) wave with a fixed duration of T. p ; The communication signal is a symbol modulated by Phase Shift Keying (PSK), and its length varies with T i Change to T i -T p The transmitted signal x(t) at the full-duplex ISAC node is expressed as:

[0093]

[0094] Among them, x i,k (t) represents the transmission signal of the kth PRI of the i-th CPI, expressed as:

[0095]

[0096] Among them, T c represents the sampling interval, denote the perceived signal power and the communication signal power respectively, c[n]=exp(jπn 2 / N), n=0,1,…,N-1 represents the fast time code corresponding to LFM, and its length is s i,k [j],j=0,1,…,J i -1 represents the i-th CPI, k-th PRI, j-th communication symbol, k = 0, 1, ..., K i -1, length is Then the number of range gates for the i-th PRF is N+J i , ψ(t) represents the bandwidth B = 1 / T c The Nyquist waveform.

[0097] Step 2: The full-duplex ISAC node obtains the echo signal of the range-ambiguous target after several PRIs. The specific process is as follows:

[0098] After the transmitted signal in step 1 is reflected by the target, the received signal y(t) at the full-duplex ISAC node is expressed as:

[0099]

[0100] Where α represents the complex channel coefficient of the target reflection path, β represents the complex channel coefficient of full-duplex self-interference, and f d represents the Doppler shift of the target, Indicates the transmitted signal after several PRIs. Represents the apparent delay, which is different from the real delay τ s The relationship between d represents the number of PRIs that the transmitted signal is delayed to return, d = 1, 2, ..., K i , βx(t) represents the self-interference caused by full-duplex, and n(t) represents the channel noise.

[0101] Ignore the phase changes that do not constitute a cycle, that is, According to step 1, the transmitted signal x of the kth PRI of the i-th CPI i,k (t), the received signal y of the kth PRI of the i-th CPI i,k (t) is expressed as:

[0102]

[0103] The actual delay τ due to distance ambiguity s It is folded to different degrees at each PRF. For example, it is folded into the apparent delay at the i-th PRF. The distance gate where the real delay is located is represented by n τ =round(Bτ s ), round(·) indicates the nearest integer operation, and the range gate corresponding to the apparent delay under the i-th PRF is The distance gate n where the real delay is located τ The distance gate where the apparent delay is located The relationship is:

[0104]

[0105] The received signal y of the kth PRI of the i-th CPI i,k (t) is represented by the vector y i,k The form is expressed as:

[0106]

[0107] where x i,k represents the emission vector, Indicates that after n τ,i The emission vector after unit time intervals, n i,k represents a noise vector and any element n i,k [·] all satisfy n i,k [·]~CN(0,N0), N0 represents the noise power spectrum density, p represents the power vector of all pulse repetition periods in the i-th CPI, r i,k is the fast time code vector c corresponding to LFM and J i Communication symbols i,k [·] composed of a vector, represents the delayed p, represents the delayed r i,k ,at the same time:

[0108]

[0109] in, means (N+J i )×1 column vector of all ones.

[0110] For the received vector y i,k Using modern filters to improve the self-interference problem of full-duplex ISAC nodes, the residual self-interference is a random signal proportional to the transmitted signal power. The received signal after filtering It is expressed as:

[0111]

[0112] Among them, ∈ represents the degree of elimination of full-duplex self-interference, z i,k =[z i,k [0],…,z i,k [N+J i ]] T represents the residual self-interference vector and represents the Hadamard product.

[0113] Step 3: Get the value from step 2 Perform matched filtering to filter out random communication signals that affect perception when distance ambiguity occurs, thereby improving the perceived signal-to-interference ratio. The specific process is as follows:

[0114] When the target is far away and the distance is ambiguous, the echo arrives after several PRIs. At this time, only the sent signal and the received signal perception part can match. Received signal perception vector It can be expressed as:

[0115]

[0116] in, It is a vector composed of the fast time code vector c corresponding to LFM and zero value, expressed as:

[0117]

[0118] Therefore, in order to eliminate the influence of random communication symbols on the matching results, the ISAC matching filter h i,k Designed as the sensing part of the original waveform, it is expressed as:

[0119]

[0120] In the kth PRI of the ith CPI, k=d,d+1,…,K i -1, the result of performing matched filtering It is expressed as:

[0121]

[0122] in, express Middle elements, * indicates a convolution operation.

[0123] In the i-th CPI, K i with the same PRFF i The pulse matching filter results are aligned according to the range gate to form a matching filter result matrix It is expressed as:

[0124]

[0125] in, For the general A vector written as columns,

[0126] In the kth PRI, when Corresponding to the target apparent delay The corresponding range gate under the i-th PRF Place, that is hour, The range gate corresponding to the target's true distance The peak value is obtained at It is expressed as:

[0127]

[0128] in,(·) H represents the conjugate transpose, x i,k,r 、z i,k and n i,k are the results of the sensing part of the transmitted signal, self-interference and noise passing through the matched filter, expressed as:

[0129]

[0130]

[0131] Among them, when the perceived signal power and communication signal power When fixed, i is a constant, expressed as:

[0132]

[0133] Step 4: The matched filtering result matrix obtained in step 3 Pulse-Doppler processing is performed to reduce full-duplex self-interference and noise, and further enhance the perceived signal-to-interference ratio. The specific process is as follows:

[0134] right No. Perform Fast Fourier Transform (FFT) on the column to obtain the vector after FFT for:

[0135]

[0136] Among them, the vector The calculation method for each element in is:

[0137]

[0138] Will The vectors of each column FFT are combined into a range-Doppler matrix It is expressed as:

[0139]

[0140] When q′ corresponds to the target Doppler frequency shift f d The corresponding Doppler gate At q′=q, at the same time Range-Doppler Matrix Get the peak value, the peak It is expressed as:

[0141]

[0142] in, and They represent the results of pulse-Doppler processing of the perceived part of the transmitted signal, self-interference and noise. The perceived part of the transmitted signal is amplified by K i -d times.

[0143] I CPI will get I range-Doppler matrix Find each The range-Doppler gate where the peak is located is used to perform target detection. When a target is present, the range-Doppler matrix The peak value is When there is no target, the range-Doppler matrix The peak value is a random number The hypothesis test is expressed as:

[0144]

[0145] In a linear detector, the envelope The false alarm probability P can be obtained FA and the detection probability P D , expressed as:

[0146]

[0147] in, represents the detection threshold within the i-th CPI. After the false alarm probability is constant, can be solved as:

[0148]

[0149] Step 5: After the target is detected under all the PRFs in step 4, the apparent delay under multiple PRFs is combined with the remainder theorem to perform fuzzy distance resolution. The specific algorithm flow is as follows:

[0150] Use the remainder theorem to estimate the distance gate where the actual delay is located It is expressed as:

[0151]

[0152] Among them, the inverse element η i It can be obtained by the extended Euclidean algorithm, γ iIt represents the product of the number of other I-1 PRF range gates except the number of the i-th PRF range gate, expressed as:

[0153]

[0154] The true distance to the unfolded target is estimated as:

[0155]

[0156] Estimated distance The real distance R real The root mean square error (RMSE) is expressed as:

[0157]

[0158] After using multiple PRFs, the maximum unambiguous range is extended to:

[0159]

[0160] Step 6: Power constraint for a single PRI in step 1. The specific process is as follows:

[0161] Set the maximum power within a single pulse repetition period of the i-th CPI to in, Represent the perceived signal power and the communication signal power respectively. If the communication receiver remains stationary, the ISAC signal y received by the communication receiver c (t) is expressed as:

[0162] y c (t)=hx(t)+n(t),0≤t≤IT CPI

[0163] For a single PRF waveform, the maximum transmission rate within the i-th CPI is:

[0164]

[0165] Therefore, for the multiple PRF (I) waveform, the average maximum transmission rate is calculated as:

[0166]

Claims

1. A synaesthesia integrated waveform design method based on multiple pulse repetition frequencies, comprising the following steps: Step 1: The full-duplex ISAC node transmits multiple pulse repetition periods within one CPI, and transmits the sensing signal and the communication symbol in turn within each pulse repetition period. By changing the length of the communication symbol within multiple CPIs, a transmission signal x(t) with multiple PRFs is formed. Among them, a single CPI is fixed to T CPI =K i T i , K i Indicates that the PRI in this CPI is T i The pulse repetition period is T; the sensing signal is LFM, and the duration is fixed at T p ; The communication signal is a PSK modulated symbol, and its length varies with T i Change, denoted as T i -T p ; Step 2: The full-duplex ISAC node obtains the echo signal y(t) of the range-ambiguous target after several PRIs. On this basis, the echo vector y of the pulse repetition period in each CPI is obtained through preprocessing i,k ; Step 3: Full-duplex ISAC nodes use the known sensing portion of the transmitted signal Construct the matched filter h i,k , match the echo of the target with ambiguous range to eliminate the interference of random communication symbols. i The result of the pulse repetition period matched filtering is constructed into a matrix Step 4: Use FFT to perform pulse-Doppler processing to reduce full-duplex self-interference and noise, thereby enhancing the perceived signal-to-interference ratio and obtaining the range-Doppler matrix On this basis, a fixed threshold is used for target detection in each CPI; Step 5: When all CPIs have detected the target, the range-Doppler matrix of each CPI is Find the peak value in the equation to obtain the target apparent delay in each CPI, and then solve the real delay by combining the remainder theorem to estimate the real distance of the target. Step 6: Set power constraints for each CPI Weighing the perceived signal power of each pulse repetition period and communication signal power Afterwards, the communication receiver obtains the average maximum transmission rate under multiple PRFs.

2. According to the method for designing a synaesthesia integrated waveform based on multiple pulse repetition frequencies according to claim 1, the step three uses the perception part of the known transmission signal of the full-duplex ISAC node to match filter the echo of the range-ambiguous target to eliminate the interference of random communication symbols, comprising the following steps: When the target is far away and the distance is ambiguous, the echo arrives after several PRIs. At this time, only the sent signal and the received signal perception part can match. Received signal perception vector It can be expressed as: in, represents the power vector of all pulse repetition periods within the i-th CPI, denote the perceived signal power and the communication signal power respectively, It is a vector composed of the fast time code vector c corresponding to LFM and zero value, expressed as: Therefore, in order to eliminate the influence of random communication symbols on the matching results, the ISAC matching filter h i,k Designed as the sensing part of the original waveform, it is expressed as: In the kth PRI of the ith CPI, k=d,d+1,…,K i -1, the result of performing matched filtering It is expressed as: in, express Middle elements, * indicates a convolution operation. In the i-th CPI, K i with the same PRFF i The pulse matching filter results are aligned according to the range gate to form a matching filter result matrix It is expressed as: in, For the general A vector written as columns, In the kth PRI, when Corresponding to the target apparent delay The corresponding range gate under the i-th PRF Place, that is hour, The range gate corresponding to the target's true distance The peak value is obtained at It is expressed as: in,(·) H represents the conjugate transpose, x i,k,r 、z i,k and n i,k are the results of the sensing part of the transmitted signal, self-interference and noise passing through the matched filter, expressed as: Among them, when the perceived signal power and communication signal power When fixed, i is a constant, expressed as:

Images