OFDM radar communication integrated waveform design and signal processing method based on ZC sequence

Abstract

The invention discloses an OFDM radar communication integrated waveform design and signal processing method based on a ZC sequence, and the method comprises the following steps: selecting the ZC sequence as an OFDM frequency domain coefficient for loading, and obtaining an OFDM radar transmitting signal based on the ZC sequence, modulating communication information by using a variable symbol interval phase mapping modulation algorithm to obtain an OFDM radar communication integrated waveform based on a ZC sequence; and establishing a linear transmitting and receiving model based on a radar communication integrated system, and realizing zero-distance sidelobe pulse compression and low-bit-error-rate communication demodulation of an OFDM radar communication integrated signal based on a ZC sequence according to a ZC-OFDM waveform pulse compression and variable symbol interval phase mapping demodulation algorithm.

Description

Technical Field

[0001] The present invention belongs to the technical fields of wireless communication and radar target detection, and further relates to an OFDM radar communication integrated waveform design and signal processing method based on a ZC sequence. Background Art

[0002] With the advancement of electronic countermeasures technology and the increasing complexity of modern warfare, the military is placing higher demands on integrated radar and communication systems. Balancing radar and communication performance is a key concern. Traditional integrated systems employ discrete designs for communication and detection. While both functions offer good performance with dedicated resources, they lack unified planning and design, resulting in insufficient parallel coordination. Therefore, the design process must not only consider the waveform's adaptability to both radar and communication performance, but also design corresponding radar pulse compression algorithms and communication modulation and demodulation algorithms, while also balancing the system's hardware implementation complexity and power efficiency.

[0003] Xidian University's patent application, "Method for Radar Detection and Communication Transmission Based on Linear Frequency Modulation Signals" (filing date: January 16, 2017, publication number: CN106772350A, publication date: May 31, 2017), discloses a dual-function signal processing method. This technology constructs a multi-carrier linear frequency modulation signal system, where the main carrier maintains the traditional radar detection function, while the subcarrier modulates the communication data using frequency modulation parameters. Its innovation lies in leveraging the cross-correlation characteristics of signals with different frequency modulation slopes to map serial communication data to the subcarrier frequency modulation parameters after group conversion, enabling multi-bit information transmission within a single pulse cycle and effectively reducing the data transmission bit error rate. However, this solution has shortcomings in signal design: while functional multiplexing is achieved by separating the main and subcarriers, it does not fully address the inherent time-frequency coupling characteristics of linear frequency modulation signals that affect system performance. Especially in the distance and speed detection dimensions, the failure to adopt sidelobe suppression measures has led to an aggravation of the sidelobe interference problem in the radar echo signal, which in turn affects the detection accuracy of the radar system and makes it difficult for the target resolution capability to meet the performance requirements of modern radar systems.

[0004] The University of Electronic Science and Technology of China (USTC) has disclosed a 5G signal design method for integrated radar communication in its patent application, "A 5G Signal Design Method for Integrated Radar Communication" (filing date: December 27, 2021, publication number: CN114282369B, publication date: October 25, 2024). Its main feature is the use of an interval-interval linear phase compression modulation algorithm to modulate communication information. This method then solves an optimization model with the frequency-domain subcarrier coefficients of the designed integrated radar communication signal as optimization variables and signal detection performance and communication performance as objective functions. The advantage of using the interval-interval linear phase compression modulation algorithm for communication information modulation lies in its enhanced noise immunity and flexible modulation parameter configuration. However, this communication modulation method still has shortcomings. The compression interval of the interval-interval linear phase compression modulation algorithm is inconsistent with the communication bit error rate (BER), which increases with the increase of the compression interval. Furthermore, the hardware implementation of this algorithm is complex, requiring precise control of the phase compression and demodulation intervals.

[0005] The problems existing in the above research can be summarized into the following two aspects: 1) The pulse compression of the existing radar communication integrated signal has the problem of radar echo signal sidelobe interference, which affects the integrated signal detection performance; 2) The communication information modulation in the existing radar communication integrated signal has the problem of high bit error rate and complex hardware implementation. Summary of the Invention

[0006] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide an integrated waveform design and signal processing method for OFDM radar communication based on ZC sequence, which realizes radar detection and communication transmission functions by transmitting a single signal.

[0007] The objective of the present invention is achieved through the following technical solutions: an integrated waveform design and signal processing method for OFDM radar communication based on a ZC sequence, a variable symbol interval phase mapping modulation algorithm for modulating communication information, and a ZC-OFDM waveform pulse compression algorithm for radar signal pulse compression; the specific steps of the method are as follows:

[0008] S1. Designing an OFDM radar communication integrated signal based on a ZC sequence; including the following sub-steps:

[0009] S11. Use ZC sequence as OFDM frequency domain coefficient for loading; let the number of subcarriers be N and the frequency domain complex weighting coefficient be R k The expression of the OFDM radar transmission signal based on the ZC sequence is:

[0010]

[0011] where k = 0, 1, ..., N-1; f k=kΔf, Δf is the bandwidth of each OFDM subcarrier; T is the time width within one period of OFDM symbol; where R k is a ZC sequence;

[0012] S12, using the variable symbol interval phase mapping modulation algorithm to modulate the communication information; assuming that the number of bits of the binary symbol is 1, the modulation coefficient of the frequency domain subcarrier is D=2 I The transmitted bit combination is represented as {χ1,χ2,…,χ D}, let the phase mapping function be P(·); when the communication symbol χ is transmitted j When , the phase mapping principle is:

[0013]

[0014] In the above formula, j = 1, 2, ... D, e j is the lower boundary of the D interval, σ is the width of the compression interval, D = 2πσ; when the input phase belongs to the symbol mapping interval, its original phase information will be retained. When the input phase does not belong to the original symbol mapping interval, the input phase is adjusted through the phase mapping function;

[0015] Assume that the modulation function is G(·) and the modulation interval is μ. The frequency domain coefficients of the modulated OFDM signal are:

[0016]

[0017] ρ is a continuous sequence of non-negative integers not greater than (N-1) / μ;

[0018] S2. Establishing a linear transmission and reception model based on the radar communication integrated system; including the following sub-steps:

[0019] S21. Discretely sample the s′(t) signal to obtain the transmitted signal:

[0020]

[0021] S22. Assume that the radar detection area is divided into M range resolution units. The echo signal finally received by the radar is the superposition of the radar echo signals of each range resolution unit. The radar echo signal obtained is:

[0022]

[0023] Among them, d m represents the scattering coefficient of each distance resolution unit, is the time domain sampling sequence of additive white Gaussian noise;

[0024] S23. Suppose there are W communication multipath channels, where the response of the wth channel is hw , then the communication receiving signal expression of the radar base station is:

[0025]

[0026] S3, ZC-OFDM waveform pulse compression and communication demodulation of OFDM radar communication integrated signal based on ZC sequence; including the following sub-steps:

[0027] S31. Implement radar pulse compression using the ZC-OFDM waveform pulse compression algorithm.

[0028] S32, by calculating the demodulated data and the modulation time The Euclidean distance between the two situations is used to determine the optimal demodulation situation based on the minimum distance principle:

[0029]

[0030] in j=1,2,…,D is the modulation phase, It is the demodulation phase of the variable symbol interval phase mapping modulation algorithm in step S12.

[0031] The beneficial effects of the present invention are as follows: first, the present invention modulates the OFDM radar transmission signal based on the ZC sequence based on the variable symbol interval phase mapping modulation algorithm to obtain the OFDM radar communication integrated signal based on the ZC sequence; second, based on the radar communication integrated system, a linear signal transmission and reception model is established; then, the radar signal pulse compression and communication signal demodulation are realized using the ZC-OFDM waveform pulse compression and the variable symbol interval phase mapping modulation algorithm. The present invention modulates the communication information through the variable symbol interval phase mapping modulation algorithm, which reduces the bit error rate and simplifies the hardware system complexity compared to the traditional linear phase compression modulation algorithm; and uses the ZC-OFDM waveform pulse compression method to achieve a range-free sidelobe pulse compression effect. Therefore, the use of the OFDM radar communication integrated waveform design and signal processing method based on the ZC sequence of the present invention can effectively improve the overall performance of the radar communication integrated signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a radar communication integrated system according to an embodiment of the present invention;

[0033] Figure 2 is a flowchart of steps in an embodiment of the present invention;

[0034] Figure 3 This is a diagram of the amplitude-frequency characteristics of a ZC sequence according to an embodiment of the present invention;

[0035] Figure 4Schematic diagram showing a comparison of information modulation and demodulation performance between a variable symbol interval phase mapping modulation algorithm according to an embodiment of the present invention and a traditional interval linear phase compression modulation algorithm;

[0036] Figure 5 This is a performance analysis diagram of the ZC-OFDM waveform pulse compression algorithm according to an embodiment of the present invention;

[0037] Figure 6 This is a performance comparison diagram of the ZC-OFDM waveform pulse compression algorithm according to an embodiment of the present invention and the traditional matched filter pulse compression effect;

[0038] Figure 7 This is a performance comparison chart of the pulse compression effects of the ZC-OFDM waveform pulse compression algorithm and the CP-OFDM inverse filtering pulse compression algorithm according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention is verified by simulation experiments, and the relevant processes and conclusions are verified based on the Matlab2020b platform. The technical solution of the present invention is further described below with reference to the accompanying drawings and specific embodiments.

[0040] A typical radar communication integrated system is as follows: Figure 1 The radar communication integration system transmits radar communication integration signals and receives target echoes, and a communication link exists between the radar communication integration system and the communication base station.

[0041] The invention discloses an integrated waveform design and signal processing method for OFDM radar communication based on ZC sequence, which uses variable symbol interval phase mapping modulation algorithm to modulate communication information and uses ZC-OFDM waveform pulse compression algorithm to realize radar signal pulse compression; Figure 2 As shown, the specific steps of the method are as follows:

[0042] S1. Designing an OFDM radar communication integrated signal based on a ZC sequence; including the following sub-steps:

[0043] S11. Use ZC sequence as OFDM frequency domain coefficient for loading; let the number of subcarriers be N and the frequency domain complex weighting coefficient be R k The expression of the OFDM radar transmission signal based on the ZC sequence is:

[0044]

[0045] where k = 0, 1, ..., N-1; f k =kΔf, Δf is the bandwidth of each OFDM subcarrier; assuming the signal bandwidth is B, then Δf = B / N; T is the time width within one period of OFDM symbol; where R kis the ZC sequence; the ZC sequence has good autocorrelation and cross-correlation properties, and its expression is:

[0046]

[0047] Where r is the root index, N zc is the length of the ZC sequence, and the amplitude-frequency characteristic of the ZC sequence is shown in the figure below: Figure 3 As shown, it can be seen that the ZC sequence is still a constant modulus sequence after FFT.

[0048] S12. Modulate communication information using a variable symbol interval phase mapping modulation algorithm. While the interval linear phase compression modulation algorithm has advantages such as loose waveform frequency domain constraints and high phase design freedom, it still suffers from high bit error rates and high hardware implementation complexity. Therefore, the present invention uses a variable symbol interval phase mapping modulation algorithm to expand the error tolerance space, reduce complexity, and thus improve communication transmission performance.

[0049] In the principle explanation, assuming that the number of bits of the binary symbol is 1, the modulation coefficient of the frequency domain subcarrier is D=2 I The bit combination transmitted can be expressed as {χ1,χ2,…,χ D}, let the phase mapping function be P(·). When the communication symbol χ is transmitted j When , the phase mapping principle is:

[0050]

[0051] In the above formula, j = 1, 2, ... D, e j is the lower boundary of the D interval, and σ is the width of the compression interval. It is easy to see that D = 2π / σ. From the above formula, we can see that when the input phase falls within the symbol mapping interval, its original phase information will be retained. When the input phase does not fall within the original symbol mapping interval, the input phase is adjusted using the phase mapping function.

[0052] In practical applications, the variable symbol interval phase mapping modulation algorithm first extracts the frequency domain coefficients containing the communication bits based on a designed sampling function. Since there are D possible combinations of transmitted bits, and D typically takes values ​​of 2, 4, or 8, further increasing the symbol spacing would reduce the bit error rate, leading to unacceptable levels. Therefore, the improvement proposed in this invention is actually a special simplified processing method for the case where D = 2, 4, or 8. This method uses the real and imaginary signs of the input data instead of the original phase rotation to achieve the same effect.

[0053] Assume that the modulation function is G(·) and the modulation interval is μ. The frequency domain coefficients of the modulated OFDM signal are:

[0054]

[0055] ρ is a continuous sequence of non-negative integers not greater than (N-1) / μ;

[0056] The modulation function G(·) here and the phase mapping function P(·) mentioned above are different forms of the same modulation algorithm in terms of signal complex data and signal phase. The modulation process of the modulation function G(·) is: In the results It is still a complex number. The modulation function G(·) of the variable symbol interval phase mapping modulation algorithm is expressed as:

[0057]

[0058] in Represents the frequency domain coefficient of the modulation signal, and the absolute value of the real part is The absolute value of the imaginary part is The symbol of the real part is s re , the symbol of the imaginary part is s im ;

[0059] The value of bit combination D represents different s re 、s im ; The following discussion is divided into cases where D takes values ​​of 2, 4, and 8.

[0060] A. When D = 2, the modulation information has only one bit b0, s im and Following the imaginary part of the input value, when b0 is 0, s re Take +1, otherwise take -1; It is determined according to the absolute value of the real part of the input data;

[0061] B. When D = 4, the modulation information has two bits b0b1, and its structure is as follows:

[0062]

[0063] C. When D = 8, the modulation information has three bits b0b1b2, and its structure is as follows:

[0064]

[0065] The final OFDM radar communication integrated signal based on the ZC sequence is:

[0066]

[0067] S2. Establishing a linear transmission and reception model based on the radar communication integrated system; including the following sub-steps:

[0068] S21. Discretely sample the s′(t) signal to obtain the transmitted signal:

[0069]

[0070] S22. Assume that the radar detection area is divided into M range resolution units. The echo signal finally received by the radar is the superposition of the radar echo signals of each range resolution unit. The radar echo signal obtained is:

[0071]

[0072] in, Represents the scattering coefficient of each distance resolution unit, g m is the equivalent radar cross-sectional area corresponding to the scattering coefficients of all scattering points in the mth range unit illuminated by the radar at the slow time η; 4πf c R m (η) / c is the directional phase; is the time domain sampling sequence of additive white Gaussian noise with variance σ 2 ;

[0073] S23. Suppose there are W communication multipath channels, where the response of the wth channel is h w , then the communication receiving signal expression of the radar base station is:

[0074]

[0075] S3, ZC-OFDM waveform pulse compression and communication demodulation of OFDM radar communication integrated signal based on ZC sequence; including the following sub-steps:

[0076] S31. Implement radar pulse compression using the ZC-OFDM waveform pulse compression algorithm.

[0077] The transmission sequence s=[s1,s2,…,s N-1 ] and add a 0-value sequence before and after as a protection unit. The length of the single-side protection unit is M-1, and the new transmission sequence s′ is obtained:

[0078]

[0079] The radar base station transmits the radar communication integrated signal s′. When the radar base station obtains a discrete echo sequence, since the first M-1 sampling values ​​and the last M-1 sampling values ​​do not contain the echo energy of all M different range resolution units, the first M-1 and last M-1 sampling values ​​of the echo sequence are removed (that is, removing the cyclic prefix in communication technology, removing the first and last M-1 rows of the echo matrix), and the following sequence can be obtained:

[0080]

[0081] Then, the received echo sequence vector It can be expressed as:

[0082]

[0083] in, Representation matrix Perform linear convolution with s′; H can be expressed as:

[0084]

[0085] The noise vector v is a time domain sampling sequence of additive white Gaussian noise, which can be expressed as

[0086] Since the M-1 values ​​at the beginning and end of the transmitted sequence s′ are all 0, we can remove the beginning and end of the transmitted sequence s′ to obtain s t =[s0,s1,…,s N-1 ] T ; and the matrix Delete the first M-1 columns and the last M-1 columns to get the matrix H:

[0087]

[0088] Therefore, the echo sequence u can be expressed as:

[0089]

[0090] in [·] T is the transpose operation; is the time domain sampling sequence of additive white Gaussian noise;

[0091] Rewrite H as a circulant matrix to obtain H′; fold back the received signal to obtain u′, and then obtain a new signal model:

[0092]

[0093] Here, rewriting the matrix H as a circulant matrix means splicing the matrix H from the bottom up to the M-1 layers from the top to the 1 to M-1 layers, obtaining an N×N circulant matrix H′:

[0094]

[0095] Back-folding the received signal u means concatenating u from the bottom up to the M-1 layers to obtain u′ from the 1 to M-1 layers, that is:

[0096]

[0097] right Performing fast Fourier transform on both sides of the equation yields:

[0098] U k =D k S k +V k ,k=0,1,…,N-1

[0099] Among them U k is the fast Fourier transform result of the received echo u′; S k is the time domain transmission sequence s t The fast Fourier transform result of V k is the noise vector The fast Fourier transform result of is the fast Fourier transform result of the scattering coefficient of each distance resolution unit of M; D k The estimated value of is:

[0100]

[0101] Due to S k with U k Known, so D can be obtained from the above formula k Estimated value of Again Perform IFFT to obtain the scattering coefficient vectors of M range resolution units, and then obtain the equivalent RCS of each range unit to complete the radar pulse compression of the ZC-OFDM radar communication integrated signal;

[0102] S33, by calculating the demodulated data and the modulation time The Euclidean distance between j=1,2,…,D cases is used to determine the optimal demodulation situation according to the minimum distance principle:

[0103]

[0104] in j=1,2,…,D is the modulation phase, is the demodulation phase of the symbol interval phase mapping modulation algorithm in step S12. By determining the minimum absolute value of the phase angle difference in the above formula and judging the corresponding specific bit combination according to the criterion, the communication demodulation of the OFDM radar communication integrated signal based on the ZC sequence can be completed.

[0105] To verify the integrated waveform design and signal processing method of OFDM radar communication based on ZC sequence in the present invention and to test its radar detection performance and communication performance, the following experiments were conducted:

[0106] Simulation Experiment 1: Simulation Experiment 1 is to use the QPSK modulation algorithm, the interval region phase compression modulation algorithm and the variable symbol interval phase mapping modulation algorithm used in the present invention to conduct a comparative analysis on the signal communication performance. The number of subcarriers of the designed basic OFDM waveform is 1024, and the modulation interval is set to 4. The interval region phase compression modulation algorithm is expressed as QPC (Quadrature Phase Compression), and the variable symbol interval phase mapping modulation algorithm is expressed as VQPM (Variablesymbol Quadrature Phase Mapping). The bit error rate curves of QPC, VQPM and QPSK algorithms under different signal-to-noise ratio conditions are compared respectively. The bit error rate variation range is set to -10dB to 10dB, and the incremental step size is 1dB. 3000 Monte Carlo simulations are run under each signal-to-noise ratio condition, and the average value is taken as the bit error rate value under the signal-to-noise ratio condition. The final simulation results are as follows. Figure 4 shown.

[0107] from Figure 4 As can be seen from the figure, the bit error rate curves for the VQPM and QPSK algorithms are nearly identical, demonstrating that they are very similar in terms of communication information modulation and demodulation performance. The QPC bit error rate curve, on the other hand, is significantly higher than the other two algorithms, demonstrating that, under the same conditions, communication transmission performance using the QPC algorithm will be slightly reduced.

[0108] on the other hand, Figure 4 The results also show that the VQPM algorithm improves communication transmission performance from the original QPC curve to the QPSK curve. The QPSK bit error rate curve was chosen for comparison because, under additive white Gaussian noise (AWGN) channel conditions, QPSK is the theoretically optimal bit error rate for quadrature phase modulation. The bit error rate curves of other quadrature phase modulation schemes are generally not lower than that of QPSK. In other words, the VQPM algorithm has achieved the theoretically optimal bit error rate for quadrature phase modulation.

[0109] Simulation Experiment 2: Simulation Experiment 2 is a performance analysis of the pulse compression effect of the ZC-OFDM waveform pulse compression algorithm used in this invention. Considering the case of no noise, the number of random targets within the detection range is designed to be 10, and the equivalent radar scattering coefficient of each target is designed to randomly vary between -20dB and 0dB. The final simulation results are as follows: Figure 5 shown.

[0110] from Figure 5 (a) It can be seen that the ZC-OFDM waveform has good time-frequency domain properties, and in principle meets the equivalent conditions of low PAPR and high distance unit signal-to-noise ratio.

[0111] from Figure 5As can be seen in Figure (b), the pulse compression noise floor can reach approximately -340dB, equivalent to zero noise. This demonstrates that this method can achieve pulse compression with zero range sidelobes. In other words, when executing the pulse compression algorithm using a pure waveform, the noise floor will not be artificially elevated due to factors such as range sidelobe interference, which would otherwise result in "false zero noise."

[0112] Simulation Experiment 3: Simulation Experiment 3 is a test of the difference between the pulse compression effect of the ZC-OFDM waveform pulse compression algorithm and the traditional matched filter in the absence of noise. In the simulation experiment, the number of random targets within the detection range is set to 10, the equivalent radar scattering coefficient varies randomly between -20dB and 0dB, and the waveform used in the matched filter is the ZC-OFDM waveform with the same parameters. The final simulation effect is as follows: Figure 6 shown.

[0113] from Figure 6 As can be seen from the figure, the noise floor of the matched filter is approximately -50dB. This is because, as a pulse compression algorithm, matched filtering will cause a certain degree of sidelobe interference around the correlation peak (detected target), thus reflecting this "false zero noise" characteristic. In reality, signal transmission is of course impossible in a zero-noise environment. In this case, the sidelobe interference will be more obvious, so that to a certain extent, it will affect the radar's target detection. However, the noise floor of the ZC-OFDM waveform pulse compression algorithm in the present invention is significantly reduced to about -350dB, which effectively avoids the sidelobe interference of other distance units. Therefore, the method used in the present invention is far more capable of reducing sidelobe than matched filtering.

[0114] Simulation Experiment 4: Simulation Experiment 4 compares the pulse compression effect of the ZC-OFDM waveform pulse compression algorithm used in the present invention with that of the traditional CP-OFDM algorithm. The simulation experiment sets 10 random targets and random scattering coefficients, but sets the waveform and noise signal-to-noise ratio to 3dB. The ZC-OFDM waveform with the same parameters is used as the radar basic waveform, and only the signal processing method is changed. The final simulation effect is as follows Figure 7 shown.

[0115] from Figure 7 (b) It can be seen that the traditional CP-OFDM algorithm does not have specific constraints on the reference signal frequency domain. Therefore, the reference signal frequency domain amplitude may reach a minimum value somewhere. Since the reference signal will eventually appear in the denominator, a denominator of 0 will have a significant impact on the pulse compression algorithm. Therefore, the CP-OFDM algorithm considers using an algorithm similar to clipping in its waveform design to optimize its frequency domain constant modulus property.

[0116] from Figure 7(a) It can be seen that the ZC-OFDM waveform pulse compression algorithm used in the present invention has good pulse compression performance and is more robust to outliers of the reference signal. This is because it takes into account the protection of the constant modulus of the reference signal in the frequency domain, thereby simplifying the waveform design and improving the pulse compression effect.

[0117] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. An integrated waveform design and signal processing method for OFDM radar communication based on ZC sequence, characterized by: The communication information is modulated using a variable symbol interval phase mapping modulation algorithm, and the radar signal pulse compression is achieved using a ZC-OFDM waveform pulse compression algorithm. The specific steps of this method are as follows: S1. Designing an OFDM radar communication integrated signal based on a ZC sequence; including the following sub-steps: S11. Use ZC sequence as OFDM frequency domain coefficient for loading; let the number of subcarriers be N and the frequency domain complex weighting coefficient be R k The expression of the OFDM radar transmission signal based on the ZC sequence is: where k = 0, 1, ..., N-1; f k =kΔf, Δf is the bandwidth of each OFDM subcarrier; T is the time width within one period of OFDM symbol; where R k is a ZC sequence; S12, using the variable symbol interval phase mapping modulation algorithm to modulate the communication information; assuming that the number of bits of the binary symbol is 1, the modulation coefficient of the frequency domain subcarrier is D=2 I The transmitted bit combination is represented as {χ1,χ2,…,χ D }, let the phase mapping function be P(·); when the communication symbol χ is transmitted j When , the phase mapping principle is: In the above formula, j = 1, 2, ... D, e j is the lower boundary of the D interval, σ is the width of the compression interval, D = 2π / σ; when the input phase belongs to the symbol mapping interval, its original phase information will be retained. When the input phase does not belong to the original symbol mapping interval, the input phase is adjusted through the phase mapping function; Assume that the modulation function is G(·) and the modulation interval is μ. The frequency domain coefficients of the modulated OFDM signal are: ρ is a continuous sequence of non-negative integers not greater than (N-1) / μ; S2. Establishing a linear transmission and reception model based on the radar communication integrated system; including the following sub-steps: S21. Discretely sample the s′(t) signal to obtain the transmitted signal: S22. Assume that the radar detection area is divided into M range resolution units. The echo signal finally received by the radar is the superposition of the radar echo signals of each range resolution unit. The radar echo signal obtained is: Among them, d m represents the scattering coefficient of each distance resolution unit, is the time domain sampling sequence of additive white Gaussian noise; S23. Suppose there are W communication multipath channels, where the response of the wth channel is h w , then the communication receiving signal expression of the radar base station is: S3, ZC-OFDM waveform pulse compression and communication demodulation of OFDM radar communication integrated signal based on ZC sequence; including the following sub-steps: S31. Implement radar pulse compression using the ZC-OFDM waveform pulse compression algorithm. S32, by calculating the demodulated data and the modulation time The Euclidean distance between the two situations is used to determine the optimal demodulation situation based on the minimum distance principle: in is the modulation phase, It is the demodulation phase of the variable symbol interval phase mapping modulation algorithm in step S12.

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