A multi-pulse repetition frequency-based integrated waveform design method

Abstract

The application provides a multi-pulse repetition frequency (PRF) based integrated sensing and communications (ISAC) waveform design method, which improves the range ambiguity problem of the ISAC system. First, the full-duplex ISAC node transmits different PRF waveforms in multiple coherent processing intervals (CPIs), and under each PRF, fixed-length sensing signals and variable-length communication symbols are transmitted in turn. Second, the full-duplex ISAC node knows the transmitted sensing waveform, and performs target echo matched filtering. Third, the full-duplex self-interference and noise are reduced through pulse-Doppler processing. Finally, when the target is detected in all CPIs, the target apparent time delay in each CPI is obtained according to the range-Doppler matrix, the real time delay is solved by combining the remainder theorem, and the real distance of the target is estimated. The waveform method designed by the application has the ability to resist range ambiguity, significantly expands the maximum unambiguous range, and improves the detection probability and distance estimation accuracy of long-distance targets.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of waveform design, and particularly relates to an anti-distance ambiguity integrated sensing and communication waveform design method based on multiple pulse repetition frequencies. BACKGROUND

[0002] As the next generation of mobile communication systems, 6G is required to have the ability of interconnected sensing in addition to the communication ability. The future 6G system will have higher frequency bands, larger bandwidths, and more densely distributed large-scale antenna arrays to integrate wireless signal sensing and communication capabilities, and further improve the collaboration ability between systems. Integrated sensing and communication (ISAC) is one of the key scenarios of 6G. The research focus is to design a dual-function waveform that can realize sensing and communication through shared signaling resources.

[0003] Due to the wider frequency band, bandwidth, and antenna conditions of 6G, radar systems can be integrated into the ISAC system for ISAC waveform design. Among them, the pulse-Doppler radar system is used to embed communication symbols to form an ISAC system due to its strong long-range sensing ability. The pulse-Doppler radar is based on a single pulse repetition interval (PRI) echo time delay to perform ranging, and at this time, the selection of pulse repetition frequency (PRF) is particularly important, which needs to meet the distance, speed area coverage and resolution requirements, which involves the trade-off between the maximum unambiguous distance and the maximum unambiguous speed.

[0004] The PRF is divided into low, medium and high frequency bands. The low PRF corresponds to a larger PRI, and does not cause distance ambiguity within the maximum effective distance, but cannot guarantee speed ambiguity. The medium PRF has good all-around coverage for targets, but will cause ambiguity in the distance and speed intervals. The high PRF can not only obtain a wider uncluttered region in the frequency domain to ensure speed ambiguity, but also increase the number of cumulative pulses within a coherent processing interval (CPI), thereby improving the detection signal-to-noise ratio, but cannot avoid distance ambiguity. Since speed is crucial for target tracking and needs to be accurately measured, the PD radar usually selects a high PRF, which will often cause distance ambiguity in the PD radar.

[0005] Distance ambiguity is caused by the echo time delay of a long-distance target exceeding the measurable range of PRI, which is due to the defects of radar ranging system. Radar measures the distance according to the time delay between the transmitted signal and the echo within one PRI. When the target is close, the echo arrives before the next PRI transmission signal, and accurate ranging can be achieved at this time. When the target is far away, the echo returns after several PRIs, and the radar misjudges the target in the current PRI at this time. The true time delay is folded into one PRI range, resulting in a serious decrease in ranging accuracy with the increase of the number of echo delays. Therefore, in the design of ISAC waveform, it is necessary to not only ensure the communication performance, such as transmission rate, but also ensure the sensing performance, such as ranging accuracy. Therefore, it is necessary to effectively solve the ambiguity of the measured distance to achieve more accurate target distance estimation.

[0006] To solve the problem of distance ambiguity, the application designs a multi-pulse repetition frequency based integrated sensing and communication waveform design method. The folded time delay in each PRF is obtained by transmitting different PRFs in multiple CPIs, the unfolded time delay is solved by combining the remainder theorem, and the true distance of the target is estimated according to the unfolded time delay. The proposed waveform design can effectively improve the distance ambiguity problem, expand the maximum non-ambiguous distance range, improve the detection probability and distance estimation accuracy of long-distance targets, and further improve the performance of the ISAC system. SUMMARY

[0007] The purpose of the application is to provide a multi-pulse repetition frequency based integrated sensing and communication waveform design method under the ISAC system, which can improve the distance ambiguity problem caused by long-distance targets, expand the maximum non-ambiguous distance range, and improve the detection probability and distance estimation accuracy of long-distance targets.

[0008] The multi-pulse repetition frequency based integrated sensing and communication waveform design method comprises the following steps:

[0009] Step one: construct an I-pulse repetition frequency integrated sensing and communication transmission signal, and the specific process is as follows:

[0010] In the ISAC transmission waveform of the continuous I CPIs transmitting I PRFs, the PRF vector is F=[F1, F2, …, FI], and the corresponding pulse repetition interval (PRI) is I . In the ith CPI, i=1, 2, …, I, there is T CPI =K i T i , wherein T CPI represents the duration of the CPI, and K i represents the PRF Fi The number of pulses in each CPI. The ISAC transmit waveform is designed within each CPI, the sensing signal is a linear frequency modulation (LFM), and the duration is fixed as T p ; the communication signal is a phase shift keying (PSK) modulated symbol, and the length varies as T i T i -T p The transmit signal x(t) at the full-duplex ISAC node is represented as:

[0011]

[0012] where x i,k (t) represents the transmit signal of the i-th CPI and the k-th PRI, and is represented as:

[0013]

[0014] where T c represents the sampling interval, and c[n] = exp(jπn 2 / N), n = 0, 1, …, N-1 represent the LFM corresponding to the fast time code, and the length is s i,k [j], j = 0, 1, …, J i -1 represents the j-th communication symbol of the i-th CPI and the k-th PRI, k = 0, 1, …, K i -1, and the length is Then the number of distance ambiguity of the i-th PRF is N+J i , and ψ(t) represents the Nyquist waveform with a bandwidth of B = 1 / T c .

[0015] Step two: the full-duplex ISAC node obtains the echo signal of the distance ambiguity target after several PRIs, and the specific process is as follows:

[0016] The transmit signal in step one after reflection by the target, the received signal y(t) at the full-duplex ISAC node is represented as:

[0017]

[0018] where α represents the complex channel coefficient of the target reflection path, β represents the complex channel coefficient of the full-duplex self-interference, f d represents the Doppler shift of the target, represents the transmit signal after several PRIs, represents the apparent time delay, and τ represents the true time delays The relationship between the two is d represents the PRI number of the delay return of the transmitted signal, d = 1, 2, …, K i , βx(t) represents the self-interference caused by full duplex, and n(t) represents channel noise.

[0019] Neglect the phase change that does not constitute a cycle, that is According to step one, the transmitted signal x i,k (t) of the i-th CPI and the k-th PRI, and the received signal y i,k (t) of the i-th CPI and the k-th PRI are represented as:

[0020]

[0021] Due to the distance ambiguity, the real time delay τ s is folded to different degrees under each PRF, for example, under the i-th PRF, it is folded to the apparent time delay The distance gate where the real time delay is located is represented as n τ = round(Bτ s ), round(·) represents the nearest integer operation, and the distance gate corresponding to the apparent time delay under the i-th PRF is The relationship between the distance gate n τ where the real time delay is located and the distance gate where the apparent time delay is located is:

[0022]

[0023] The received signal y i,k (t) of the i-th CPI and the k-th PRI is represented as a vector y i,k in the form, which is represented as:

[0024]

[0025] where x i,k represents the transmitted vector, represents the transmitted vector after n τ,i unit time intervals, n i,k represents the noise vector, and any element n i,k [·] in it satisfies n i,k [·] ~ CN(0, N0), N0 represents the noise power spectral density, p represents the power vector of all pulse repetition periods within the i-th CPI, r i,k is a vector composed of the fast time code vector c corresponding to the LFM and J i communication symbols s i,k [·], represents p after the time delay, represents r after the time delayi,k Meanwhile:

[0026]

[0027] where, represents an (N+J i ) x 1 all-one column vector.

[0028] 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 transmit signal power. The filtered received signal is expressed as:

[0029]

[0030] where, ∈ 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 three: Perform matched filtering on the received vector y obtained in step two, filter out the random communication signal affecting perception when range ambiguity occurs, and improve the perception signal-to-interference ratio. The specific process is as follows:

[0032] When the target distance is far away and range ambiguity occurs, the echo arrives after experiencing several PRIs. At this time, only the transmitted signal and the received signal perception part can be matched. The received signal perception vector can be expressed as:

[0033]

[0034] where, is a vector composed of the fast-time code vector c corresponding to the LFM and zero values, and is expressed as:

[0035]

[0036] Therefore, in order to eliminate the influence of random communication symbols on the matching result, the ISAC matched filter h i,k is designed as the perception part in the original waveform, expressed as:

[0037]

[0038] In the k-th PRI within the i-th CPI, k = d, d + 1, …, K i-1, the result of performing matched filtering Expressed as:

[0039]

[0040] in, express Middle elements, * indicates 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 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 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 perception 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, ξ i is a constant, expressed as:

[0049]

[0050] Step 4: Matched filtering result matrix obtained in step 3 The pulse-Doppler processing is performed, the full duplex self-interference and noise are reduced, and the perceived signal-to-interference ratio is further enhanced. The specific process is as shown below:

[0051] The The The Fast Fourier Transform (FFT) is performed on each column to obtain the FFT vector The

[0052]

[0053] The calculation method of each element in the vector is as follows:

[0054]

[0055] The The FFT vectors of each column are combined into a range-Doppler matrix The

[0056]

[0057] When q' corresponds to the target Doppler shift f d The corresponding Doppler gate , that is, q' = q, and The range-Doppler matrix The peak value is obtained, and the peak value The

[0058]

[0059] The and respectively represent the perceived part of the transmitted signal, the self-interference and the noise after the pulse-Doppler processing. The perceived part of the transmitted signal power is amplified K i -d times.

[0060] I range-Doppler matrices are obtained by I CPIs The peak value of each range-Doppler gate in each is found, and target detection is performed. When there is a target, the peak value of the range-Doppler matrix is When there is no target, the peak value of the range-Doppler matrix is a random number The hypothesis test is represented as:

[0061]

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

[0063]

[0064] wherein, represents the detection threshold within the ith CPI. After the false alarm probability is constant, can be solved, and is expressed as:

[0065]

[0066] Step five: after the target is detected under the I PRFs in step four, the apparent time delay under multiple PRFs is used to combine the remainder theorem to perform ambiguous distance resolution, and the specific algorithm flow is as follows:

[0067] The distance gate where the real time delay is estimated using the remainder theorem is expressed as:

[0068]

[0069] wherein, the inverse element η i can be solved by the extended Euclidean algorithm, γ i represents the product of the distance gate numbers of the other I-1 PRFs except the distance gate number of the ith PRF, and is expressed as:

[0070]

[0071] The real distance of the target without folding is estimated as:

[0072]

[0073] The estimated distance and the real distance R real The root mean square error (RMSE) of the real distance R

[0074]

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

[0076]

[0077] Step six: power constraint is performed on the single PRI in step one, and the specific flow is as follows:

[0078] The maximum power within the single pulse repetition period of the ith CPI is set as wherein, respectively, denote the perceived signal power and the communication signal power, respectively. If the communication receiver remains stationary, the ISAC signal y 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 ith CPI is:

[0081]

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

[0083]

[0084] Advantages

[0085] The method utilizes a full-duplex ISAC node to transmit multiple pulse repetition periods within one coherent processing interval (CPI), and sequentially transmits a perceived signal and a communication symbol in each pulse repetition period. In multiple CPIs, a transmission signal with a multi-PRF is formed by changing the length of the communication symbol. Secondly, the echo of the range ambiguity target is matched filtered by the perceived part of the transmission signal known by the full-duplex ISAC node, thereby avoiding the influence of the random communication symbol on perception. Thirdly, the full-duplex self-interference and noise are reduced through 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 the CPIs detect the target, the target apparent time delay in each CPI is obtained by searching for peaks in the range-Doppler matrix obtained after pulse-Doppler processing, and the real time delay is solved by combining the remainder theorem, thereby estimating the real distance of the target.

[0086] The multi-PRF waveform designed in the application has the anti-range ambiguity feature, can expand the maximum non-ambiguous range, improve the detection probability and distance estimation accuracy of long-range targets, and lays a good foundation for the wide application of the ISAC system. BRIEF DESCRIPTION OF DRAWINGS

[0087] Figure 1 It is a schematic diagram of the integrated sensing and communication waveform based on multi-PRF.

[0088] Figure 2 It is a specific implementation process for resolving the range ambiguity of the integrated sensing and communication waveform based on multi-PRF. DETAILED DESCRIPTION

[0089] The purpose of the present application is to provide a multi-pulse repetition frequency integrated sensing and communication waveform design method under the ISAC system, which can improve the range ambiguity problem in the ISAC system, expand the maximum non-ambiguous range, and improve the detection probability and distance estimation accuracy of the long-distance target.

[0090] The multi-pulse repetition frequency integrated sensing and communication waveform design method comprises the following steps:

[0091] Step one: constructing I-pulse repetition frequency integrated sensing and communication transmission signal, the specific process is as follows:

[0092] In the continuous I CPI, I kinds of PRF ISAC transmission waveforms are transmitted, the PRF vector is F=[F1, F2,…, FI], and the corresponding pulse repetition interval (PRI) is I . In the i-th CPI, i=1, 2,…, I, there are T CPI =K i T i , wherein T CPI represents the duration of the CPI, K i represents the number of pulses with PRF F i in the CPI. In each CPI, the ISAC transmission waveform is designed, the sensing signal is a linear frequency modulation (LFM), and the duration is fixed as T p ; the communication signal is a phase shift keying (PSK) modulated symbol, and the length changes with T i as T i -T p . The transmission signal x(t) at the full-duplex ISAC node is represented as:

[0093]

[0094] Wherein, x i,k (t) represents the transmission signal of the i-th CPI and the k-th PRI, and is represented as:

[0095]

[0096] Wherein, T c represents the sampling interval, respectively represent the sensing signal power and the communication signal power, c[n]=exp(jπn 2 / N), n=0, 1,…, N-1 represents the fast time code corresponding to the LFM, and the length is s i,k [j],j=0,1,…,J i -1 represents the i-th CPI the k-th PRI the j-th communication symbol, k = 0, 1, …, K i -1, length is The number of distance bins of the i-th PRF is N + J i , ψ(t) represents the Nyquist waveform with bandwidth B = 1 / T c .

[0097] Step two: the full-duplex ISAC node obtains the echo signal of the range ambiguity target after several PRIs, and the specific process is as follows:

[0098] The received signal y(t) at the full-duplex ISAC node after the target reflection of the transmitting signal in step one is represented as:

[0099]

[0100] Wherein, α represents the complex channel coefficient of the target reflection path, β represents the complex channel coefficient of the full-duplex self-interference, f d represents the Doppler shift of the target, represents the transmitting signal after experiencing several PRIs, represents the apparent time delay, and the relationship between the real time delay τ s is d represents the number of PRIs of the transmitting signal delay return, d = 1, 2, …, K i , βx(t) represents the self-interference caused by full-duplex, and n(t) represents the channel noise.

[0101] Neglect the phase change that does not constitute a period, that is, According to the transmitting signal x i,k (t) of the i-th CPI the k-th PRI in step one, the received signal y i,k (t) of the i-th CPI the k-th PRI is represented as:

[0102]

[0103] Due to the range ambiguity, the real time delay τ s is folded to different degrees under each PRF, for example, under the i-th PRF, it is folded to the apparent time delay The distance bin where the real time delay is located is represented as n τ = round(Bτ s ), round(·) represents the nearest integer operation, and the distance bin corresponding to the apparent time delay under the i-th PRF is The distance bin n τ where the real time delay is located and the distance bin where the apparent time delay is located The relationship is:

[0104]

[0105] The received signal y i,k (t) of the ith CPI and the kth PRI is expressed as a vector y i,k (t) is expressed as:

[0106]

[0107] where x i,k represents a transmit vector, represents a transmit vector after n τ,i unit time intervals, n i,k represents a noise vector and any element n i,k [·] in it satisfies n i,k [·] ~ CN(0, N0), N0 represents a noise power spectral density, p represents a power vector of all pulse repetition periods in the ith CPI, r i,k is a vector composed of a fast time code vector c corresponding to the LFM and J i communication symbols s i,k [·], represents p after time delay, represents r i,k after time delay, and

[0108]

[0109] wherein, represents an (N+J i ) × 1 all-1 column vector.

[0110] The received vector y i,k is filtered using a modern filter to improve the self-interference problem of the full-duplex ISAC node, and then the residual self-interference is a random signal proportional to the transmit signal power. The filtered received signal is expressed as:

[0111]

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

[0113] Step three: the residual self-interference vector z Perform matched filtering to filter out random communication signals that affect perception when range 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. 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 The design is the perception part of the original waveform, expressed as:

[0119]

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

[0121]

[0122] in, express Middle elements, * indicates 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 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 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 perception 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, ξ i is a constant, expressed as:

[0132]

[0133] Step 4: Matched filtering result matrix obtained in step 3 Pulse-Doppler processing is performed to reduce full-duplex self-interference and noise, further enhancing 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 the range-Doppler matrix Expressed as:

[0139]

[0140] When q′ corresponds to the target Doppler frequency shift f d The corresponding Doppler gate At the same time, i.e. q' = q Range-Doppler matrix Obtain the peak value, the peak value is expressed as:

[0141]

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

[0143] I CPIs will obtain I range-Doppler matrices respectively find the range-Doppler gate where the peak value in each , perform target detection. When there is a target, the peak value of the range-Doppler matrix is When there is no target, the peak value of the range-Doppler matrix is a random number The hypothesis test is expressed as:

[0144]

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

[0146]

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

[0148]

[0149] Step five: after detecting the target under the I PRFs in step four, use the apparent time delay under multiple PRFs to combine the remainder theorem to perform ambiguous range resolution, and the specific algorithm flow is as follows:

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

[0151]

[0152] wherein, the inverse element η i can be obtained by the extended Euclidean algorithm, and γ idenotes the product of the other I-1 PRF range gates other than the ith PRF range gate, and is denoted as:

[0153]

[0154] The unfolded target true range is estimated as:

[0155]

[0156] The estimated range The root mean square error (RMSE) of the true range R real is denoted as:

[0157]

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

[0159]

[0160] Step six: power constraint on the single PRI of step one, the specific process is shown as follows:

[0161] The maximum power in the single pulse repetition period of the ith CPI is set as wherein, denote the sensing signal power and the communication signal power, respectively. If the communication receiver remains in a static state, the ISAC signal y c received by the communication receiver is denoted as:

[0162] y c (t) = hx(t) + n(t), 0≤t≤IT CPI

[0163] For a single PRF waveform, the maximum transmission rate in the ith CPI is:

[0164]

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

[0166]

Claims

1. A method for designing a synaesthesia integrated waveform 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. In each pulse repetition period, the sensing signal and the communication symbol are transmitted in sequence. By changing the length of the communication symbol within multiple CPIs, a transmission signal x(t) with multiple PRFs is formed. The single CPI is fixed to T CPI =K i T i , K i Indicates that the PRI within 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, expressed as T i -T p The transmitted signal x(t) at the full-duplex ISAC node is expressed as: Among them, x i,k (t) represents the transmitted signal of the kth PRI of the i-th CPI, which is expressed as: Among them, T c represents the sampling interval, P r i 、P c i 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, and j-th communication symbol, k=0,1,…,K i -1, length is Then the number of range gates of the i-th PRF is N+J i , ψ(t) represents the bandwidth B = 1 / T c Nyquist waveform; Step 2: The full-duplex ISAC node obtains the echo signal y(t) of the range-ambiguous target after several PRIs. Based on this, the echo vector y of the pulse repetition period within 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 , perform matched filtering on the echo of the range-ambiguous target, and then eliminate the interference of random communication symbols, and convert K 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 within 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 CPI to obtain the target apparent delay within each CPI, and use the remainder theorem to solve the real delay, and then 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 (PRFs) in claim 1, step three, using the known sensing portion of the transmitted signal of the full-duplex ISAC node to perform matched filtering on the echo of the range-ambiguous target to eliminate interference from random communication symbols, comprises 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. The 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 perception signal power and 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 The design is the perception part of the original waveform, expressed as: In the kth PRI of the i-th CPI, k=d,d+1,…,K i -1, the result of performing matched filtering Expressed as: in, express Middle elements, * indicates 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 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 Expressed as: in,(·) H represents the conjugate transpose, x i,k,r 、z i,k and n i,k are the results of the perception 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, ξ i is a constant, expressed as:

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