Method for unknown time information high-speed target signal accumulation detection and parameter estimation

Abstract

The application discloses a time information unknown high-speed target signal accumulation detection and parameter estimation method, which is applied to the field of radar signal processing and aims at the problems of poor accumulation detection performance and inaccurate parameter estimation in the prior art under the condition of unknown time information. First, a time information unknown high-speed target echo signal model is established. Then, echo signal pulse compression is carried out, and coherent accumulation is realized through RFT to obtain an initial radial distance coarse estimation value and an accurate estimation value of radial velocity. Subsequently, the pulse compression echo signal is extracted based on the estimated parameters. Then, SFT processing is carried out on the extracted signal to obtain estimation values of a start time and an end time. Finally, the obtained initial radial velocity and start and end times are used to obtain an accurate estimation value of the initial radial distance. Through scale Fourier transform, effective accumulation detection and high-precision parameter estimation of the target are realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of radar signal processing, and particularly relates to a target accumulation detection and parameter estimation technique. BACKGROUND

[0002] In the process of radar detection, the time when the target enters and leaves the radar detection area is often unknown. For example, in a non-cooperative environment on the battlefield, when the enemy moving target enters a certain airspace and when it leaves the airspace are information that needs to be obtained through radar detection, and the time parameter information of these targets is often unknown in radar detection. However, the current long-time coherent accumulation signal processing method often assumes that the time parameter information of the target is known. When the assumption does not hold, the long-time coherent accumulation signal processing method based on the known time information of the target is likely to suffer a huge performance loss or even completely fail. Therefore, how to improve the detection capability of radar for high-speed targets with unknown time information has become an important topic in the field of radar research.

[0003] Domestic and foreign scholars have carried out research on the signal accumulation detection and parameter estimation method of high-speed targets with unknown time information.

[0004] In order to realize the coherent accumulation and parameter estimation of weak moving targets, Xu et al. proposed Radon Fourier transform (RFT) for range migration (RM) correction and radar moving target focusing. Since RFT is only applicable to uniform velocity targets, a generalized RFT (GRFT) was further developed to obtain the coherent accumulation of targets with high-order motion parameters. GRFT realizes coherent accumulation and parameter estimation through joint search in parameter space. However, the above-mentioned coherent accumulation methods all assume that the entering time and leaving time of the target are known, but in real radar applications, the time when the moving target enters or leaves the radar coverage area is often unknown. When the time information is unknown, the detection and estimation performance of the above algorithms will sharply decrease.

[0005] To realize effective accumulation and detection of echo signal energy among different motion modalities, Li et al. proposed a long-time coherent accumulation method based on short-time GRFT (STGRFT). For the problem of unknown time information, Li et al. proposed a windowed Radon fractional Fourier transform (WRFRFT) for detecting a moving target with partial dwell time within an observation period. However, on the one hand, the WRFRFT algorithm has high computational complexity due to the need for high-dimensional search; on the other hand, the WRFRFT method will defocus the integration result in the end time dimension when processing high-speed uniform velocity targets with unknown time information. In addition, Li et al. also proposed a method based on extended GRFT (EGRFT) and windowed fractional Fourier transform (WFRFT) (i.e., EGRFFT-WFRFT). By performing a four-dimensional search in the parameter space, EGRFT can extract target signals and output peak values, thereby estimating the initial distance, radial velocity, acceleration and entry time of the target. Then, according to the estimated parameters, the radar echo containing the target signal is extracted, and the termination time is estimated using WFRFT. However, this algorithm still has the problem of parameter estimation error in the end time dimension when processing high-speed uniform velocity targets with unknown time information.

[0006] In addition to the above accumulation methods, other scholars have also conducted some related research, but it should be noted that these accumulation methods currently have the problems of insufficient excellent accumulation and detection performance under unknown time information, inaccurate parameter estimation, etc. SUMMARY

[0007] To solve the above technical problems, the present application proposes a time information unknown high-speed target signal accumulation detection and parameter estimation method based on scaling Fourier transform RFT-SFT (Radon Fourier Transform-Scaling Fourier Transform), which significantly improves the detection performance and parameter estimation accuracy of the radar.

[0008] The technical scheme adopted by the present application is: a time information unknown high-speed target signal accumulation detection and parameter estimation method, comprising:

[0009] S1, establishing a time information unknown high-speed target echo signal model;

[0010] S2, pulse compression is performed on the received echo signal to obtain a pulse compression echo signal;

[0011] S3, determining the search range and search step of the search parameters;

[0012] S4, using the search parameters set in step S3, the radar echo signal after pulse compression is processed by RFT accumulation, and the corresponding RFT accumulation output is obtained, and the estimated parameters are obtained through the peak position of the RFT accumulation output, the estimated parameters include: the initial radial distance rough estimation value r' and the accurate estimation value v' of the radial velocity of the target signal;

[0013] S5, the distance-pulse number domain pulse compression signal is addressed and extracted according to the estimated parameters obtained in S4;

[0014] S6, the extracted distance-pulse number domain echo signal is scaled Fourier transformed to obtain the estimation value of the start time and the end time;

[0015] S7, the accurate estimation value of the radial distance is obtained according to the estimation value of the radial velocity, the start time and the end time, and the radial distance rough estimation value.

[0016] The beneficial effects of the present application: a time information unknown high-speed target signal accumulation detection and parameter estimation method based on scale Fourier transform (RFT-SFT) is provided, which studies the coherent accumulation and parameter estimation method of high-speed target echo signal under the condition of unknown time information; first, a high-speed target echo signal model under the condition of unknown time information is established; then, the echo signal is pulse compressed and coherent accumulation is realized by RFT to obtain the initial radial distance rough estimation value and the accurate estimation value of the radial velocity; subsequently, the extracted echo signal is processed by SFT to obtain the estimation value of the start time and the end time; finally, the accurate estimation value of the initial radial distance is obtained by using the initial radial velocity and the start and end time. Through scale Fourier transform, effective accumulation detection and high-precision parameter estimation of the target are realized. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 The flowchart of the embodiment of the present application is shown in the figure;

[0018] Figure 2 The pulse compression echo schematic diagram is shown in the figure;

[0019] Figure 3 The projection in the distance-velocity domain after RFT processing is shown in the figure;

[0020] Figure 4 The extracted distance unit-pulse number domain echo is shown in the figure;

[0021] Figure 5 The output result of the start pulse-end pulse domain is shown in the figure;

[0022] Figure 6 The distance-velocity domain projection corresponding to the algorithm is shown in the figure;

[0023] Figure 7 is the MTD output result;

[0024] Figure 8 is the STGRFT algorithm corresponding distance-velocity domain projection;

[0025] Figure 9 is the STGRFT algorithm corresponding termination time-start time domain projection;

[0026] Figure 10 is the EGRFT-WFRFT algorithm corresponding distance-velocity domain projection;

[0027] Figure 11 is the EGRFT-WFRFT algorithm corresponding start time-velocity domain projection;

[0028] Figure 12 is the EGRFT-WFRFT algorithm corresponding termination time estimation. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to understand the technical content of the present application, the content of the present application is further explained below in combination with the drawings.

[0030] The present application adopts the method of Matlab simulation experiment for verification, and verifies the correctness and effectiveness of the present application on the scientific calculation software Matlab R2021b. The embodiments of the present application are further described below in combination with the drawings.

[0031] As shown in Figure 1 , the present application proposes a time information unknown high-speed target signal accumulation detection method, which is specifically implemented by the following process:

[0032] Step 1, assuming that [T0, T1] represents the observation period of the radar, during which the radar adopts a linear frequency modulation signal as the transmitting signal which can be expressed as:

[0033]

[0034] wherein, is a rectangular window function, corresponding to is the fast time, T p is the pulse duration, γ is the linear frequency modulation (LFM) rate, and f c is the carrier frequency. T0 and T1 represent the start time and termination time of the radar observation respectively.

[0035] The radar parameter setting used in this example is: carrier frequency fc = 0.6 GHz, bandwidth B = 10 MHz, sampling frequency f s = 50 MHz, pulse repetition frequency PRT = f r = 200 Hz, pulse duration T p = 5 μs. The radar system parameters are shown in Table 1.

[0036] Table 1 Radar system parameters

[0037] Parameter Symbol Value Carrier frequency f c ]]> 0.6 GHz Bandwidth B 10 MHz Sampling frequency f s ]]> 50 MHz Pulse repetition frequency f r ]]> 200 Hz Pulse duration [TECHNICAL FIELD] p ]] 5 us

[0038] The post-pulse signal-to-noise ratio is SNR = 7 dB. The target parameters are set as: the initial distance of the target r = 200010 m, the radial velocity v = 60 m / s. The target time parameters are set as: the starting time of the target entering the radar detection area η0= 0.505 s, the ending time η1= 3 s, which correspond to the starting pulse N1= 101 and the ending pulse N2= 600. The motion parameters and time parameters of the target are shown in Table 2.

[0039] Table 2 Target motion parameters and time parameters

[0040] Parameter Symbol Value Initial distance r 200010m Radial velocity v 60 m / s Start pulse [N1] 101 End pulse [N2] 600 Start time [eta0] 0.505s End time [eta1] 3s

[0041] During the radar observation period, it is assumed that the target enters the radar detection area at time T b and leaves the detection area at time T e , then the radial distance of the target can be expressed as:

[0042] R(t m ) = R0+ V(t m -T b ), t m ∈ [T b , T e ]

[0043] wherein R0is the initial distance between the target and the radar at time T b , V is the initial radial velocity of the target, T b and T e (T0< T b < T e < T1) are assumed to be unknown.

[0044] Step 2, pulse compression processing is performed on the radar echo signal in the observation time to obtain the pulse compression echo signal

[0045]

[0046] wherein

[0047]

[0048] λ and c are the wavelength and speed of light, respectively. Β is the bandwidth, and σ represents the amplitude of the compressed signal. The variance is represented by δ 2 Additive complex Gaussian white noise.

[0049] Figure 2 This is a schematic diagram of a pulse compression echo signal. It can be seen that due to the target t... b Enter the detection area at any time, t e Leaving the detection area, the target echo only occurs in the slow time domain at time t. b -t e The memory exists.

[0050] Step 3: Determine the search interval and search step size for the search parameters within the segment. Based on prior information such as the radar detection area and the velocity range of high-speed targets, determine the range search interval [r] of the target signal. min ,r max ], speed search interval [v min ,v max ], where r min r is the minimum possible distance the target can move. max v is the maximum possible distance the target can travel. min v is the minimum possible velocity of the target. max Let be the maximum possible velocity of the target. Based on the radar system parameters, the initial search step sizes for radial range and radial velocity are determined to be Δr = c / 2B and Δv = λ / 2(T1-T0), respectively. Therefore, the number of search units for range is N. r =ceil((r max -r min The number of speed searches is N. v =ceil((v max -v min ) / △v), where ceil(·) represents the rounding up operation.

[0051] Step 4: Determine the target trajectory based on the search parameter combination (r,v), and perform RFT (Radon Fourier Transform) accumulation processing on the pulse-compressed radar echo to obtain the corresponding RFT accumulation output:

[0052]

[0053] By accumulating the peak positions of the output using RFT, a coarse estimate of the initial radial distance and an accurate estimate of the radial velocity (r′, v′) of the target signal are obtained:

[0054]

[0055] Figure 3 The output of the range-velocity domain after RFT algorithm processing shows that the target achieves accumulation focusing at (199.98km, 60m / s). It can be seen that RFT processing can correctly estimate the initial radial velocity of the target, but due to the unknown start and end times, there is an error in its initial radial distance.

[0056] Step 5, determine the target signal start time search interval [η] 0min ,η 0max ] and the search interval for termination time [η 1min ,η 1max Based on the radar system parameters, the search step size for the start and end times is determined to be Δη = PRT, where PRT (Pulse repetition time) is the radar pulse repetition time. Therefore, the number of searches at the start time... Number of searches at termination time The ceil(·) function represents the rounding up operation.

[0057] [η 0min ,η 0max ] and [η 1min ,η 1max Based on the observation period setting, i.e., [η] 0min ,η 0max ] and [η 1min ,η 1max The specific value should be within the observation period.

[0058] The estimated parameters (r′, v′) obtained in step 4 are used to calculate the corresponding pulse delay τ.

[0059] τ=[2(v′t m +r′) / c]

[0060] By using the pulse delay τ to extract the pulse compression signal obtained in step 2, we get:

[0061] S(t m )=s(t m ,τ)

[0062] Based on the peak position of RFT, the extracted echo sequence can be represented as:

[0063]

[0064] Figure 4 From the extracted range cell-pulse number signal, it can be seen that the target echo only occurs in the slow time domain at t. b -t e The internal memory exists, while the rest only contains noise.

[0065] Step 6: Search for the target start time η0 and end time η1, and then perform a search on S(t). m Perform a Scaling Fourier Transform (SFT) to obtain estimates of the start and end times (η0′, η1′):

[0066]

[0067] in, For scaling window functions, These are the scaling coefficients. This is a rectangular window function.

[0068] According to SFT v (η0,η1,t m The maximum value of ) is used to obtain the estimated values ​​N′1 and N′2 of the start pulse and the end pulse. Based on the estimated values ​​of the start pulse and the end pulse, the estimated values ​​of the start time and the end time are calculated. The calculation formula is: η0′=N1*PRI, η1′=N2*PRI.

[0069] Figure 5 The output of the start pulse-end pulse domain after SFT is given, from which the estimated values ​​of start time and end time can be calculated: η0′=N1′*PRI=101*5e-3=0.505s, η1′=N2′*PRI=600*5e-3=3s.

[0070] Step 7: Correct the radial distance estimate based on the estimated values ​​of radial velocity, start time, and end time.

[0071]

[0072] Right now:

[0073]

[0074] Where * represents multiplication. This represents an estimated starting distance. This represents the speed estimate. Indicates an estimated start time;

[0075] Figure 6 This is the output result in the distance-velocity domain after processing by the RFT-SFT algorithm.

[0076] Figure 7 The output of the Moving Target Detection (MTD) algorithm shows that due to distance migration, MTD cannot achieve echo accumulation and focusing or target parameter estimation.

[0077] Figure 8 , Figure 9 The figures show the distance-velocity domain projection and the termination-start time domain projection for the STGRFT algorithm. It can be seen that while the STGRFT algorithm can accurately estimate the initial radial distance, radial velocity, and start time of a high-speed target with unknown time information, its estimation of the termination time of a uniformly moving target is inaccurate due to the lack of scaling, especially under noise conditions.

[0078] Figure 10 , Figure 11 , Figure 12 The images show the distance-velocity domain projection, start-time-velocity domain projection, and termination time estimation diagrams corresponding to the EGRFT-WFRFT algorithm. It can be seen that EGRFT-WFRFT can accurately estimate the initial radial distance, radial velocity, and start time of a high-speed target with unknown time information. However, because this method does not perform scaling, its estimation of the termination time of a uniformly moving target has errors under the influence of noise.

[0079] Table 3 shows the estimated termination pulse values ​​for different methods. It can be seen that the method proposed in this invention can accurately estimate the termination time parameters of high-speed targets with unknown time information.

[0080] Table 3. Estimated number of termination pulses using different methods

[0081] Method RFT-SFT MTD STGRFT EGRFT-WFRFT True value Value 600 ～ 636 648 600

[0082] In summary, the method of the present invention can effectively detect high-speed targets when time information is unknown, and accurately estimate the target's motion parameters and time parameters.

[0083] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of the claims of the invention.

Claims

1. A method for high-speed target signal accumulation detection and parameter estimation with unknown time information, characterized in that, include: S1. Establish a model for the echo signal of a high-speed target with unknown time information; S2. Perform pulse compression on the received echo signal to obtain a pulse-compressed echo signal; S3. Determine the search range and search step size for the search parameters; S4. Using the search parameters set in step S3, perform RFT accumulation processing on the pulse-compressed radar echo signal to obtain the corresponding RFT accumulation output. Obtain the estimated parameters through the peak position of the RFT accumulation output. The estimated parameters include: the initial coarse estimate of the radial distance of the target signal and the accurate estimate of the radial velocity. S5. Address and extract the distance-pulse multidimensional pulse compression signal according to the estimated parameters obtained from S4; S6. Perform a scaled Fourier transform on the extracted distance-pulse number domain echo signal to obtain the estimated values ​​of the start time and the end time. S7. Based on the estimated values ​​of radial velocity, start time, and end time, as well as the coarse estimate of radial distance, obtain the precise estimate of radial distance.

2. The method for accumulation detection and parameter estimation of high-speed target signals with unknown time information according to claim 1, characterized in that, The high-speed target echo signal model with unknown time information in step S1 is represented as follows: ； in It is a rectangular window function. It's a fast time. γ is the pulse duration, and γ is the LFM rate. It is the carrier frequency.

3. The method for accumulation detection and parameter estimation of high-speed target signals with unknown time information according to claim 2, characterized in that, The pulse compression echo signal in step S2 is represented as follows: ； in, , This indicates the time when the target enters the radar detection area. Indicates the time it takes for the target to leave the radar detection area. and These are wavelength and speed of light, respectively. It's bandwidth. Indicates the amplitude of the compressed signal. Indicates the radial distance of the target. This represents additive complex Gaussian white noise.

4. The method for accumulation detection and parameter estimation of high-speed target signals with unknown time information according to claim 3, characterized in that, The accumulated RFT output in step S4 is represented as follows: ； By accumulating the peak positions of the output using RFT, a coarse estimate of the initial radial distance and an accurate estimate of the radial velocity of the target signal are obtained. .

5. The method for detecting and estimating parameters of high-speed target signals with unknown time information according to claim 4, characterized in that, Step S5 specifically includes the following sub-steps: S51. Estimated parameters obtained from step S4 Achieve corresponding pulse delay Calculation: ； S52, Utilizing pulse delay Extracting the pulse compression echo signal yields: ； S53. Based on the peak position of the RFT accumulated output in step S4, extract the echo sequence from the echo signal extracted in step S52. The extracted echo sequence is represented as follows: 。 6. The method for accumulation detection and parameter estimation of high-speed target signals with unknown time information according to claim 5, characterized in that, The implementation process of step S6 is as follows: S61. Perform a scaled Fourier transform on the extracted distance-pulse number domain echo signal. The result is expressed as follows: ； in, For scaling window functions; S62, according to The maximum value yields estimates for the start and end pulses. , ; S63, according to , The estimated start and end times are calculated using the following formula: , ,in, , These represent the estimated start and end times, respectively.

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