Time information unknown high-speed target signal accumulation detection and parameter estimation method

Abstract

The invention discloses an accumulation detection and parameter estimation method for a high-speed target signal with unknown time information, which is applied to the field of radar signal processing and aims to solve the problems of poor accumulation detection performance, inaccurate parameter estimation and the like under the condition that the time information is unknown in the prior art. The method comprises the following steps: firstly, establishing a high-speed target echo signal model with unknown time information; thirdly, performing pulse compression on the echo signal and realizing coherent accumulation through RFT to obtain an initial radial distance coarse estimation value and an accurate estimation value of the radial speed; then, the pulse pressure echo signals are extracted based on the estimation parameters; then, SFT processing is carried out on the extracted signals, and estimated values of the starting time and the ending time are obtained; and finally, obtaining an accurate estimation value of the initial radial distance by using the obtained initial radial speed and the starting and ending time. And effective accumulation detection and high-precision parameter estimation of the target are realized through scaling Fourier transform.

Description

Technical Field

[0001] The invention belongs to the field of radar signal processing, and in particular relates to a target accumulation detection and parameter estimation technology. Background Art

[0002] During radar detection, the time when a target enters and leaves the radar detection area is often unknown. For example, in a non-cooperative battlefield environment, when an enemy moving target enters and leaves a certain airspace is information that we need to obtain through radar detection, and the time parameter information of these targets is often unknown before radar detection. However, current long-term coherent integration signal processing methods often assume that the time parameter information of the target is known. When the assumption is no longer valid, the long-term coherent integration signal processing method based on the known target time information is likely to suffer huge performance losses or even fail completely. Therefore, how to improve the radar's detection capability for high-speed targets with unknown time information has become an important research topic in the radar field.

[0003] Scholars at home and abroad have conducted research on the signal accumulation detection and parameter estimation methods of high-speed targets with unknown temporal information.

[0004] In order to achieve 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 speed targets, generalized RFT (GRFT) was further developed to obtain coherent accumulation of targets with high-order motion parameters. GRFT achieves coherent accumulation and parameter estimation through joint search in parameter space. However, the coherent accumulation methods mentioned above all assume that the entry time and exit time of the target are known. In real radar applications, the time when the moving target enters or leaves the radar coverage is often unknown. When the time information is unknown, the detection and estimation performance of the above algorithms will drop sharply.

[0005] In order to achieve effective accumulation and detection of echo signal energy between different motion modes, Li et al. proposed a long-term coherent integration method based on short-time GRFT (STGRFT). In view of the problem of unknown time information, Li et al. proposed a windowed Radon fractional Fourier transform (WRFRFT) to detect moving targets with partial dwell time within the 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 integration result of the WRFRFT method will be defocused in the end time dimension when dealing with high-speed uniform-speed 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 the target signal and accumulate its output peak value, thereby estimating the initial range, radial velocity, acceleration and entry time of the target. Then, the radar echo containing the target signal is extracted according to the estimated parameters, and the end time is estimated using WFRFT. However, this algorithm still has the problem of parameter estimation errors in the end time dimension when processing high-speed uniform speed targets with unknown time information.

[0006] In addition to the above-mentioned accumulation methods, other scholars have also conducted some related research. However, it should be pointed out that these current accumulation methods all have problems such as poor accumulation detection performance and inaccurate parameter estimation when time information is unknown. Summary of the invention

[0007] To solve the above technical problems, the present invention proposes a method for accumulating detection and parameter estimation of high-speed target signals with unknown time information based on RadonFourier Transform-Scaling Fourier Transform (RFT-SFT), which significantly improves the detection performance and parameter estimation accuracy of radar.

[0008] The technical solution adopted by the present invention is: a method for accumulating detection and parameter estimation of high-speed target signals with unknown time information, comprising:

[0009] S1. Establishing a high-speed target echo signal model with unknown time information;

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

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

[0012] S4, using the search parameters set in step S3, performing RFT accumulation processing on the radar echo signal after pulse compression, obtaining the corresponding RFT accumulation output, and obtaining the estimated parameters through the peak position of the RFT accumulation output, wherein the estimated parameters include: a rough estimated value r' of the initial radial distance of the target signal and an accurate estimated value v' of the radial velocity;

[0013] S5, addressing and extracting the range-pulse number dimensional pulse compression signal according to the estimated parameters searched by S4;

[0014] S6. Performing a scaled Fourier transform on the extracted range-pulse number domain echo signal to obtain estimated values ​​of the start time and the end time;

[0015] S7. Obtain an accurate estimate of the radial distance based on the radial velocity, the estimated values ​​of the start time and the end time, and the rough estimate of the radial distance.

[0016] Beneficial effects of the present invention: The present invention is a method for accumulating detection and estimating parameters of high-speed target signals with unknown time information based on scaled Fourier transform (RFT-SFT), and studies the coherent accumulation and parameter estimation method of high-speed target echo signals when time information is unknown; first, a high-speed target echo signal model with unknown time information is established; then, the echo signal pulse is compressed and coherent accumulation is achieved through RFT to obtain a rough estimate of the initial radial distance and an accurate estimate of the radial velocity; then, the pulse compression echo signal is extracted based on the estimated parameters; then, the extracted signal is subjected to SFT processing to obtain an estimate of the start time and the end time; finally, the obtained initial radial velocity and start and end time are used to obtain an accurate estimate of the initial radial distance. Through scaled Fourier transform, effective accumulation detection and high-precision parameter estimation of the target are achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of an embodiment of the present invention;

[0018] Figure 2 It is a schematic diagram of pulse pressure echo;

[0019] Figure 3 It is the projection in the range-velocity domain after RFT processing;

[0020] Figure 4 is the extracted range unit-pulse number domain echo;

[0021] Figure 5 It is the output result of the start pulse-end pulse domain;

[0022] Figure 6 It is the distance-velocity domain projection corresponding to the proposed algorithm;

[0023] Figure 7 Output results for MTD;

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

[0025] Fig. 9 It is the end time-start time domain projection corresponding to the STGRFT algorithm;

[0026] Fig.10 It is the range-velocity domain projection corresponding to the EGRFT-WFRFT algorithm;

[0027] Fig.11 It is the starting time-velocity domain projection corresponding to the EGRFT-WFRFT algorithm;

[0028] Fig.12 EGRFT-WFRFT algorithm corresponding to the termination time estimate. DETAILED DESCRIPTION

[0029] To facilitate those skilled in the art to understand the technical content of the present invention, the present invention is further explained below with reference to the accompanying drawings.

[0030] The present invention is verified by using a Matlab simulation experiment method, and the correctness and effectiveness of the present invention are verified on the scientific computing software Matlab R2021b. The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0031] like Figure 1 As shown, the present invention proposes a method for accumulating and detecting high-speed target signals with unknown time information, which is specifically implemented through the following process:

[0032] Step 1, assume that [T0, T1] represents the radar observation period, during which the radar uses a linear frequency modulation signal as the transmission signal It can be expressed as:

[0033]

[0034] in, is a rectangular window function, corresponding to the rectangular window function in this embodiment It's fast time, T p is the pulse duration, γ is the linear frequency modulation signal LFM (Linear Frequency Modulation) rate, and f c is the carrier frequency. T0 and T1 represent the start time and end time of radar observation respectively.

[0035] The radar parameters used in this example are set as follows: carrier frequency fc = 0.6 GHz, bandwidth B = 10 MHz, sampling frequency f s = 50 MHz, pulse repetition frequency PRT is 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 Numeric Carrier frequency <![CDATA[f c ]]> 0.6GHz bandwidth B 10MHz Sampling frequency <![CDATA[f s ]]> 50MHz Pulse repetition frequency <![CDATA[f r ]]> 200Hz Pulse duration <![CDATA[T p ]]> 5us

[0038] The signal-to-noise ratio after pulse compression is SNR = 7 dB. The target parameters are set as follows: the initial distance of the target is r = 200010 m, and the radial velocity v = 60 m / s. The target time parameters are set as follows: the starting time η0 when the target enters the radar detection area is 0.505 s, the ending time η1 is 3 s, and the corresponding starting pulse N1 = 101, 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 Numeric Initial distance r 200010m Radial velocity v 60m / s Start pulse <![CDATA[N1]]> 101 Termination pulse <![CDATA[N2]]> 600 Start time <![CDATA[η0]]> 0.505s End time <![CDATA[η1]]> 3s

[0041] During the radar observation period, assume 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] where R0 is 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, perform pulse compression processing on the radar echo signal during the observation time to obtain the pulse-compressed echo signal

[0045]

[0046] where

[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. Denotes the variance as δ 2 Additive complex Gaussian white noise.

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

[0050] Step 3: Determine the search interval and search step size of the search parameters within the segment. Determine the distance search interval [r min ,r max ], speed search interval [v min ,v max ], where r min is the minimum possible moving distance of the target, r max is the maximum possible movement distance of the target, v min is the minimum possible speed of the target, v max is the maximum possible speed of the target. Based on the radar system parameters, the search steps of the initial radial distance and radial speed are determined to be △r=c / 2B and △v=λ / 2(T1-T0) respectively. It can be obtained that the number of search units for the distance is N r =ceil((r max -r min ) / △r), 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 motion trajectory to be searched according to the search parameter combination (r, v), perform RFT (Radon Fourier Transform) accumulation processing on the radar echo after pulse compression, and obtain the corresponding RFT accumulation output:

[0052]

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

[0054]

[0055] Figure 3 This is the output result in the range-velocity domain after RFT algorithm processing. 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 since the start and end times are unknown, 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 end time search interval [η 1min ,η 1max ], based on the radar system parameters, the search step size of the start time and the end time is determined to be △η=PRT, where PRT (Pulse repetition time) is the radar pulse repetition time. It can be seen that the search number of the start time Number of searches by end time Where ceil(·) represents the rounding up operation.

[0057] [η 0min ,η 0max ] and [η 1min ,η 1max ] is set based on the observation period, that is, [η 0min ,η 0max ] and [η 1min ,η 1max ] should be within the observation period.

[0058] According to the estimated parameters (r′, v′) obtained in step 4, the corresponding pulse delay τ is calculated.

[0059] τ=[2(v′t m +r′) / c]

[0060] The pulse pressure signal obtained in step 2 is extracted using the pulse delay τ to obtain:

[0061] S(t m )=s(t m ,τ)

[0062] According to the RFT peak position, the extracted echo sequence can be expressed as:

[0063]

[0064] Figure 4 is the extracted distance unit-pulse number signal. It can be seen that the target echo in the slow time domain is only at t b -t e The memory is there, the rest is just noise.

[0065] Step 6: Search the target start time η0 and end time η1, and calculate S(t m ) Perform Scaling Fourier Transform (SFT) to obtain the estimated values ​​of the start time and end time (η0′, η1′):

[0066]

[0067] in, is the scaling window function, is the scaling coefficient, is a rectangular window function.

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

[0069] Figure 5 This is the output result of the start pulse-end pulse domain after SFT, from which the estimated values ​​of the 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, correcting the radial distance estimate based on the estimated values ​​of radial velocity, start time and end time.

[0071]

[0072] Right now:

[0073]

[0074] Among them, * represents multiplication operation, represents the estimated value of the starting distance, represents the estimated value of speed, Indicates the estimated value of the start time;

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

[0076] Figure 7 This is the output result of the moving target detection algorithm MTD (Moving Target Detection). It can be seen that due to the existence of range migration, MTD cannot achieve echo accumulation and focusing and target parameter estimation.

[0077] Figure 8 , Fig. 9 The projection diagrams in the distance-velocity domain and the projection diagrams in the end time-start time domain corresponding to the STGRFT algorithm are shown in Table 1. It can be seen that although the STGRFT algorithm can accurately estimate the initial radial distance, radial velocity and start time of high-speed targets with unknown time information, the method does not perform scaling processing, so there is an error in estimating the end time of uniform-speed targets under the influence of noise.

[0078] Fig.10 , Fig.11 , Fig.12 The distance-velocity domain projection diagram, start time-velocity domain projection diagram and end time estimation diagram corresponding to the EGRFT-WFRFT algorithm are shown in Figure 2. It can be seen that EGRFT-WFRFT can accurately estimate the initial radial distance, radial velocity and start time of high-speed targets with unknown time information, but since this method does not perform scaling processing, there is an error in the estimation of the end time of uniform-speed targets under the influence of noise.

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

[0080] Table 3 Estimated values ​​of termination pulse numbers by different methods

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

[0082] In summary, the method of the present invention can achieve effective detection of high-speed targets when time information is unknown, and achieve accurate estimation of target motion parameters and time parameters.

[0083] 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 should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. For those skilled in the art, the present invention may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for accumulating detection and parameter estimation of high-speed target signals with unknown temporal information, characterized in that: include: S1. Establishing a high-speed target echo signal model with unknown time information; S2, performing pulse compression on the received echo signal to obtain a pulse compression echo signal; S3, determining the search range and search step of the search parameter; S4, using the search parameters set in step S3, performing RFT accumulation processing on the radar echo signal after pulse compression, obtaining a corresponding RFT accumulation output, and obtaining estimated parameters through the peak position of the RFT accumulation output, wherein the estimated parameters include: a rough estimate of the initial radial distance of the target signal and an accurate estimate of the radial velocity; S5, addressing and extracting the range-pulse number dimensional pulse compression signal according to the estimated parameters searched by S4; S6. Performing a scaled Fourier transform on the extracted range-pulse number domain echo signal to obtain estimated values ​​of the start time and the end time; S7. Obtain an accurate estimate of the radial distance based on the radial velocity, the estimated values ​​of the start time and the end time, and the rough estimate of the radial distance.

2. The method for accumulating detection and parameter estimation of high-speed target signals with unknown time information according to claim 1 is characterized in that: The time information unknown high-speed target echo signal model in step S1 is expressed as: in is the rectangular window function, It's fast time, T p is the pulse duration, γ is the LFM rate, f c is the carrier frequency.

3. The method for accumulating detection and parameter estimation of high-speed target signals with unknown time information according to claim 2 is characterized in that: The pulse pressure echo signal in step S2 is expressed as: in, λ and c are wavelength and speed of light respectively, Β is bandwidth, σ represents the amplitude of compressed signal, represents additive complex white Gaussian noise.

4. The method for accumulating detection and parameter estimation of high-speed target signals with unknown time information according to claim 3 is characterized in that: The RFT accumulation output in step S4 is expressed as:

5. The method for accumulating detection and parameter estimation of high-speed target signals with unknown time information according to claim 4 is characterized in that: Step S5 specifically includes the following sub-steps: S51, calculate the corresponding pulse delay τ according to the estimated parameters (r′, v′) searched and obtained in step S4: τ=[2(v′t m +r′) / c] S52, extracting the pulse pressure echo signal using the pulse delay τ to obtain: S(t m )=s(t m ,τ) S53, according to the peak position of the RFT accumulation output in step S4, extract the echo sequence from the echo signal extracted in step S52, and the extracted echo sequence is expressed as:

6. The method for accumulating 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: S61, perform scaled Fourier transform on the extracted range-pulse number domain echo signal, and the obtained result is expressed as: Among them, H η0,η1 (t m ) is the scaling window function; S62. According to SFT v (η0,η1,t m ) to obtain the estimated values ​​N′1 and N′2 of the start pulse and the end pulse; S63. Calculate the estimated values ​​of the start time and the end time according to N′1 and N′2. The calculation formula is: η0′=N1*PRI, η1′=N2*PRI, where η0′ and η1′ represent the estimated values ​​of the start time and the end time respectively.

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