A method for inhibiting signal processing of an ICI radar communication integrated system

Abstract

The application discloses a kind of inhibiting ICI radar communication integrated system signal processing method, compensates ICI in echo signal using SIDFnT algorithm, removes the influence of random communication information loaded in echo signal using Hadamard division, the phase matrix of Hadamard quotient is sought, remove the influence of excessive amplitude produced by division, finally using the characteristics of two-dimensional FFT energy accumulation, target energy is concentrated, so as to estimate target distance and speed by the position of maximum amplitude in matrix, and the estimated result is used to complete the compensation of interference caused by speed distance. The application uses the energy focusing characteristics of SIDFnT, suppresses echo ICI, can effectively improve radar target estimation accuracy, and directly uses radar estimation result to complete communication end compensation, greatly reduces the complexity of communication end processing method.

Description

Technical Field

[0001] This invention relates to the field of radar-communication integration, and specifically to a method for suppressing signal processing in an integrated radar-communication system with ICI (Integrated Controlled Interference) technology. Background Technology

[0002] Radio spectrum is a fixed resource, encompassing civilian communication spectrum and military spectrum. With the expansion of spectrum resources, these two types of spectrum, originally used independently, have begun to compete for resources, leading to mutual interference. Simultaneously, continuous technological advancements place higher demands on system integration and functional diversity. The integration of radar and communication allows for the merging of previously separate radar and communication equipment into a single, highly integrated system. This increases space utilization, reduces equipment costs, and makes operation more flexible, offering advantages in both electronic warfare and communication fields. Simultaneously performing range and velocity measurement functions with communication data transmission significantly improves system efficiency.

[0003] Currently, radar-communication integrated waveforms are mainly divided into two categories: multiplexed signals and shared signals. Multiplexed signal schemes refer to radar and communication each designing dedicated signals within time-division, frequency-division, code-division, and space-division frameworks, and then superimposing these dedicated signals into a single signal. However, this scheme suffers from insufficient utilization of time and frequency resources and mutual interference between radar and communication, limiting its practical value. Shared signal schemes refer to radar and communication sharing the same signal. The research path for this scheme can be further subdivided into: improving the design of radar signals to incorporate communication functions; and improving the design of communication signals to incorporate radar functions.

[0004] Commonly used radar communication integrated signals include multi-carrier signals such as Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Linear Frequency Modulation Wavelength Division Multiplexing (OCDM). Multi-carrier signals have the characteristics of strong anti-multipath interference capability and high spectrum utilization, but they can be affected by ICI due to factors such as Doppler frequency offset, resulting in inaccurate results. Summary of the Invention

[0005] This invention is used to process radar-communication integrated signals loaded with communication information. By utilizing the energy focusing characteristics of the SIDFnT algorithm to compensate for ICI, more accurate range and velocity estimation can be achieved at the radar processing end of the integrated system. At the same time, it also simplifies the signal demodulation steps at the communication end.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A method for suppressing signal processing in an integrated ICI radar and communication system, comprising the following specific steps:

[0007] Step 1: Determine the traversal range and step size for the variable scale factor;

[0008] Step 2: Perform a variable-scale Fresnel inverse transform on the transmitted signal matrix of a pulse to obtain the information of the transmitted signal in the variable-scale Fresnel domain;

[0009] Step 3: Perform a variable-scale inverse Fresnel transform on the echo signal matrix corresponding to the transmitted signal to obtain the information of the received signal in the variable-scale Fresnel domain.

[0010] Step 4: In the variable-scale Fresnel domain, the received signal information points are divided by the transmitted signal information to obtain the Hadamard quotient matrix that couples the velocity and distance information.

[0011] Step 5: Remove the amplitude information from the Hadamard quotient matrix to obtain the phase matrix;

[0012] Step 6: Perform a two-dimensional Fourier transform on the phase matrix to obtain the range Doppler map of the radar. Determine the variable scale factor. If the variable scale factor has not been traversed completely, add the traversal step to the variable scale factor as a new variable scale factor and return to step 2. If the traversal is complete, proceed to step 7.

[0013] Step 7: Compare the peak values ​​of the range Doppler images corresponding to each variable scale factor, select the image with the largest peak value, and use its peak location information as the radar estimation result;

[0014] Step 8: Use the radar estimation results to compensate for the received signal.

[0015] Preferably, the range of the variable scaling factor is from the minimum value α = j to the maximum value α = jsqrt(MN), where M is the number of symbols and N is the number of subcarriers.

[0016] Preferably, the signal is transmitted as follows:

[0017]

[0018] make Its m-th symbol is expressed in discrete form as follows:

[0019]

[0020] In the formula, N is the number of subcarriers, M is the number of symbols, k represents the k-th discrete sampling point, n and m represent the n-th subcarrier and the m-th symbol, and d n,m This represents the loaded communication data. rect() is the rectangle function, T is the duration of a symbol, and α is the scaling factor.

[0021] Preferably, the result obtained by performing a variable-scale inverse Fresnel transform on the transmitted signal matrix of a pulse is:

[0022]

[0023] Preferably, the echo signal is specifically:

[0024]

[0025] make Its m-th symbol can be expressed in discrete form as:

[0026]

[0027] In the formula, A m For channel attenuation, τ is the time delay caused by distance, and f d The Doppler frequency shift caused by the speed is given by Δf, the subcarrier spacing is given by Δf, n and m represent the nth subcarrier and the mth symbol, d represents the loaded communication data, N is the number of subcarriers, M is the number of symbols, T is the duration of a symbol, α is the variable scaling factor, and k represents the kth discrete sampling point.

[0028] Preferably, the specific formula for performing a variable-scale inverse Fresnel transform on the echo signal matrix corresponding to the transmitted signal is as follows:

[0029]

[0030] Preferably, by removing the amplitude information from the Hadamard quotient matrix, the phase matrix formula is obtained as follows:

[0031] A m,n =A m,n / abs(A m,n ).

[0032] Compared with the prior art, the significant advantages of this invention are: it suppresses the influence of ICI, can accurately estimate the target speed and distance, effectively improves the accuracy of radar target estimation, and directly uses the radar estimation results to complete the compensation at the communication end, greatly reducing the complexity of the communication end processing method. Attached Figure Description

[0033] Figure 1 This is a block diagram of the signal processing method for the radar-communication integrated system of the present invention.

[0034] Figure 2 The flowchart shows the process of traversing the radar-side algorithm of this invention once.

[0035] Figure 3 A comparison of the radar range estimation performance of SIDFnT-based methods and traditional two-dimensional FFT-based methods is presented.

[0036] Figure 4 A comparison of the performance of SIDFnT-based methods and traditional two-dimensional FFT-based methods for radar velocity estimation. Detailed Implementation

[0037] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments:

[0038] Step 1: Determine the traversal range and step size for the variable scale factor;

[0039] In a further embodiment, the range of the variable scaling factor is from the minimum value α = j to the maximum value α = jsqrt(MN), where M is the number of signs, and the step size is determined to be jsqrt(MN) / 8.

[0040] Step 2: Perform a variable-scale Fresnel transform on the transmitted signal matrix of a pulse to obtain the information of the transmitted signal in the variable-scale Fresnel domain. The specific steps are as follows:

[0041] When the transmitted signal is a Scaled Orthogonal Chirp Division Multiplexing (SOCDM) signal, it can be expressed as:

[0042]

[0043] make Its m-th symbol can be expressed in discrete form as:

[0044]

[0045] Where k represents the k-th discrete sampling point, n and m represent the n-th subcarrier and the m-th symbol, d represents the loaded communication data, and rect() is a rectangular window function. Since the signal is obtained by the variable-scale inverse Fresnel transform, the communication information matrix with dimensions M×N will be directly obtained after the variable-scale Fresnel transform.

[0046] After undergoing a variable-scale Fresnel transform, the transmitted signal can be expressed as:

[0047]

[0048] The communication information can be directly restored.

[0049] Step 3: Perform a variable-scale Fresnel transform on the echo signal matrix corresponding to the transmitted signal to obtain the information of the received signal in the variable-scale Fresnel domain, specifically:

[0050] Step 3-1: The received signal, based on the transmitted signal, will be affected by time delay and Doppler shift, which can be expressed as:

[0051]

[0052] make Its m-th symbol can be expressed in discrete form as:

[0053]

[0054] Where Am represents channel attenuation, τ represents the time delay due to distance, fd represents the Doppler frequency shift due to velocity, and Δf represents the subcarrier spacing. After undergoing variable-scale Fresnel transform, the signal is coupled with velocity and distance information, and is also affected by random communication information.

[0055] Step 3-2: Process the received signal through a variable-scale Fresnel transform to obtain:

[0056]

[0057] in For ICI, when the value of α is close to jsqrt(RN / (vf) c T 2 When α = jsqrt(RN / (vf)), it can effectively suppress ICI. c T 2 When ICI is eliminated, it can be eliminated.

[0058] Step 4: In the variable-scale Fresnel domain, divide the received signal information points by the transmitted signal information to obtain the Hadamard quotient matrix that couples the velocity and distance information. In order to eliminate the influence of random communication information, divide the received information and transmitted information points in the variable-scale Fresnel domain, that is, divide the data at each corresponding position, so that the communication information on each data point can be eliminated.

[0059]

[0060] Where A m,n The value in the m-th row and n-th column of the Hadamard matrix contains a scalar with respect to α, suppressed ICI, and radar information coupled with velocity and range.

[0061] Step 5: Since step 4 uses division, a very small divisor can cause a maximum value in the division result, severely impacting the correctness of subsequent algorithms. This is especially true when the transmitted signal is Orthogonal Frequency Division Multiplexing (OFDM), where the minimum value is very significant. Furthermore, both distance and velocity are phase information; therefore, only the phase information of the matrix is ​​retained, while the amplitude information is removed. The specific formula is:

[0062] A m,n =A m,n / abs(A m,n )

[0063] Where abs() is the modulo function.

[0064] Step 6: Perform a two-dimensional Fourier transform on the phase matrix to obtain the range Doppler map of the radar. Determine the variable scale factor. If the variable scale factor has not been traversed completely, add the traversal step to the variable scale factor as a new variable scale factor and return to step 2. If the traversal is complete, proceed to step 7.

[0065] Step 7: Compare the peak values ​​of the range Doppler images corresponding to each variable scale factor, select the image with the largest peak value, and use its peak location information as the radar estimation result.

[0066] The peak position information represents the radar estimation result. If the horizontal axis is p and the vertical axis is q, then the radar estimation result is... Where B is the signal bandwidth.

[0067] Step 8: Compensate the received signal using the radar estimation results, specifically as follows:

[0068] Step 8-1: By directly using the range and velocity information estimated by the radar to compensate for the equation in step 3-1, we can obtain:

[0069]

[0070] Step 8-2: Downconvert the result of step 7-1, and then perform a variable-scale Fresnel inverse transform to obtain the communication information.

[0071] This invention transmits a multi-carrier integrated waveform variable-scale orthogonal linear frequency modulation wavelength division multiplexing (SOCDM) signal loaded with communication information. The echo signal is affected by speed and distance on the basis of the transmitted signal. The SIDFnT algorithm with the optimal variable scale factor is used to compensate for ICI in the echo signal. The influence of random communication information loaded in the echo signal is removed by Hadamard division. The phase matrix of the Hadamard quotient is calculated to remove the influence of excessive amplitude caused by the division. Finally, the energy accumulation characteristics of two-dimensional FFT are used to concentrate the target energy, thereby estimating the target distance and speed by the position of the largest amplitude in the matrix.

[0072] The invention will be further illustrated by a specific example.

[0073] In this example, a SOCDM signal is transmitted, with N = 256 subcarriers and M = 64 symbols. The communication information is loaded onto the SOCDM using 16-quadrature amplitude modulation (QAM) and finally loaded onto f. c On a 35GHz radio frequency signal, the maximum unambiguous range is 1500m, and the maximum unambiguous velocity is 428.68m / s. Let the transmitted signal travel a distance of x = 1000m to hit a target with a velocity of v = 400m / s, and then reflect back to obtain the received signal. The radar performance results are compared with the traditional two-dimensional FFT algorithm as follows:

[0074] Mean square error of radar range estimation

[0075]

[0076] Mean square error of radar velocity estimation

[0077]

[0078] As can be seen from the table, the mean squared error of this invention is significantly better than that of the traditional two-dimensional FFT. This is because this invention suppresses the influence of ICI.

Claims

1. A method for suppressing signal processing in an integrated ICI radar and communication system, characterized in that, The specific steps are as follows: Step 1: Determine the traversal range and step size for the variable scale factor; Step 2: Perform a variable-scale Fresnel inverse transform on the transmitted signal matrix of a pulse to obtain the information of the transmitted signal in the variable-scale Fresnel domain; Step 3: Perform a variable-scale inverse Fresnel transform on the echo signal matrix corresponding to the transmitted signal to obtain the information of the received signal in the variable-scale Fresnel domain. Step 4: In the variable-scale Fresnel domain, divide the received signal information by the transmitted signal information to obtain the Hadamard quotient matrix that couples the velocity and range information, specifically: The Hadamard quotient matrix is ​​obtained by dividing the received and transmitted information points on a variable-scale Fresnel field, i.e., by dividing the data at each corresponding position. Specifically: Where A m,n The value in the m-th row and n-th column of the Hadamard matrix contains a scalar with respect to α, suppressed ICI, and radar information coupled with velocity and range. N is the number of subcarriers. T is the duration of a symbol, and α is the scaling factor; A m For channel attenuation, τ is the time delay caused by distance, and f d The Doppler frequency shift caused by velocity, Δf is the subcarrier spacing, and n and m represent the nth subcarrier and the mth symbol, respectively. Step 5: Remove the amplitude information from the Hadamard quotient matrix to obtain the phase matrix; Step 6: Perform a two-dimensional Fourier transform on the phase matrix to obtain the range Doppler map of the radar. Determine the variable scale factor. If the variable scale factor has not been traversed completely, add the traversal step to the variable scale factor as a new variable scale factor and return to step 2. If the traversal is complete, proceed to step 7. Step 7: Compare the peak values ​​of the range Doppler images corresponding to each variable scale factor, select the image with the largest peak value, and use its peak location information as the radar estimation result; Step 8: Use the radar estimation results to compensate for the received signal.

2. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, The range of values ​​for the variable scaling factor is: minimum value To the maximum value Where M is the number of symbols and N is the number of subcarriers.

3. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, Send signal Specifically: in, ; Discrete form of the m-th symbol Expressed as: In the formula, N is the number of subcarriers, M is the number of symbols, k represents the k-th discrete sampling point, n and m represent the n-th subcarrier and the m-th symbol, and d n,m This indicates the communication data being loaded. It is a rectangular function, where T is the duration of a symbol and α is a variable scaling factor.

4. The signal processing method for suppressing ICI radar communication integrated system according to claim 3, characterized in that, The result obtained by performing a variable-scale inverse Fresnel transform on the transmitted signal matrix of a pulse. for: 。 5. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, echo signal Specifically: make The discrete form of its m-th symbol is expressed as: In the formula, A m For channel attenuation, τ is the time delay caused by distance, and f d The Doppler frequency shift caused by the speed is given by Δf, where Δf is the subcarrier spacing, n and m represent the nth subcarrier and the mth symbol, d represents the loaded communication data, N is the number of subcarriers, M is the number of symbols, T is the duration of a symbol, α is the variable scaling factor, and k represents the kth discrete sampling point.

6. The signal processing method for suppressing ICI radar communication integrated system according to claim 5, characterized in that, The specific formula for performing a variable-scale inverse Fresnel transform on the echo signal matrix corresponding to the transmitted signal is as follows: In the formula, This is the result obtained by performing a variable-scale inverse Fresnel transform on the echo signal matrix corresponding to the transmitted signal.

7. The signal processing method for suppressing ICI radar communication integrated system according to claim 5, characterized in that, After removing the amplitude information from the Hadamard quotient matrix, the phase matrix is ​​obtained. The formula is: 。 8. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, The image with the largest peak value is selected, and its peak location information is used as the radar estimation result, specifically: In the formula, (p, q) are the peak position coordinates, B is the signal bandwidth, N is the number of subcarriers, M is the number of symbols, and c is the speed of light. For carrier frequency.

9. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, The result of using radar-estimated range and velocity information to compensate for the received signal for: .

10. The signal processing method for suppressing ICI radar communication integrated system according to claim 1, characterized in that, Steps 1-9 are completed by the radar end, and step 8 is completed by the communication end.

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