CN115825905A - Maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT - Google Patents
Maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT Download PDFInfo
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Abstract
The invention relates to the field of detection of maneuvering weak targets of synthetic broadband radars, in particular to a maneuvering weak target motion parameter estimation method based on angular-padded-GRFT. The maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT provided by the invention realizes long-time coherent accumulation motion parameter estimation of a weak target in a circular maneuvering scene. And provides a motion parameter compensation and target one-dimensional range profile focusing method on the basis. Compared with the method of stepped-GRFT and the like, the angular-stepped-GRFT can effectively improve the imaging capability of the frequency stepping radar to the maneuvering weak target.
Description
Technical Field
The invention relates to the field of detection of maneuvering weak targets of synthetic broadband radars, in particular to a maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT. The maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT provided by the invention realizes long-time coherent accumulation motion parameter estimation of a weak target in a circular maneuvering scene. And provides a motion parameter compensation and target one-dimensional range profile focusing method on the basis. Compared with the method of stepped-GRFT and the like, the angular-stepped-GRFT can effectively improve the imaging capability of the frequency stepping radar to the maneuvering weak target.
Background
Modern battlefield environment is increasingly complex, small RCS targets such as aircrafts and the like bring severe threats and challenges to radar detection, and meanwhile, part of small RCS targets also have strong maneuvering capability, so that the difficulty of radar detection is further increased. How to maintain high-precision measurement of the motion parameters of the small RCS maneuvering target is one of the problems to be solved urgently by modern radars.
Aiming at the problem of weak target motion parameter estimation, long-time accumulation of target energy can be realized by increasing observation time, and the effects of improving the signal-to-noise ratio of radar echo and improving the detection capability of a weak target are achieved. In 2011, j.xu et al (Xu J, yu J, peng Y N, et al, radon-Fourier Transform for Radar Target detection (i) T generalized discrete Filter tanttjtt. Tttt transformation on a space and tgetronic Systems,2011,47 (2) T1186-1202.) analyzed the relationship between the Target ARU phenomenon and each order of motion parameters, combined generalized Radon Transform and Fourier Transform, proposed a long-time coherent accumulation method based on generalized Radon-Fourier Transform (GRFT), and achieved a good detection effect. In 2021, J Guo et al (Liu Q, guo J, liang Z, et al. Motion Parameter Ttiming and HRRP Construction for High-Speed WeaT Targets located on Modified GRFT for Synthetic-Wireless radio With PRF junction TJT. TTTT Sensors Journal,2021,21 (20) T23234-23244.) combined GRFT and frequency step signal, proposed a Wideband coherent accumulation method based on nested-GRFT (concatenated generalized radio receiver Transform). The frequency stepping signal is an important high-resolution radar signal and is widely applied to the civil and military fields. It uses a series of carrier frequency step narrow-band pulses which are transmitted in sequence to obtain the distance high resolution capability by synthesizing the wide-band processing. The method realizes weak target detection and radial motion parameter estimation based on long-time coherent accumulation, researches a motion parameter compensation and target high-resolution range image focusing method on the basis, and effectively improves the detection and measurement capability of the broadband radar on the weak target.
However, the stepped-GRFT has a limitation in that only radially moving objects can be estimated. When a weak target is maneuvered, the stepped-GRFT cannot accurately estimate the motion parameters of the target, and further a correct one-dimensional distance image cannot be obtained. Aiming at the problem of detection and imaging of a frequency stepping radar on a maneuvering weak target, the invention provides an shaped-GRFT on the basis of a stepped-GRFT, can effectively solve the problem that the stepped-GRFT cannot accurately estimate the movement parameters of the maneuvering weak target, can realize correct movement compensation and one-dimensional range image focusing on the target by a coherent accumulation method based on the shaped-stepped-GRFT, and effectively improves the signal-to-noise ratio of signals after coherent accumulation processing.
Therefore, on the basis of a frequency stepping radar system, the research on the method for estimating the motion parameters of the maneuvering weak target has important practical significance and application value.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method comprises the steps of firstly carrying out pulse compression on a target baseband echo, compensating a phase item, then searching a target motion parameter in a three-dimensional parameter space, and finally carrying out motion compensation on the maneuvering weak target in a frequency domain according to a target motion parameter estimation result so as to achieve the effect of one-dimensional range image focusing.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a method for estimating the motion parameters of a maneuvering weak target based on angular-stepped-GRFT comprises the following steps:
performing down-conversion on a target radar echo to obtain a target baseband echo, and performing pulse compression on the obtained target baseband echo to obtain a pulse-compressed target baseband echo;
step two, constructing a phase compensation factor, and compensating the phase item of the target baseband echo after the pulse compression obtained in the step one by using the constructed phase compensation factor, wherein the constructed phase compensation factor comprises target motionThe target motion parameter comprises the distance R between the initial position of the target and the radar 0 A target initial velocity v and a target dynamic angular velocity omega;
and step three, performing traversal search on the target motion parameters in the phase compensation factors constructed in the step two to obtain an accumulation result matrix, wherein if and only if the searched target motion parameters are equal to the target actual motion parameters, a peak value appears in the accumulation result matrix, and the target motion parameters corresponding to the peak value are accurate estimation results of the target motion parameters.
Step four, evaluating the accuracy of the estimated value of the target motion parameter, wherein the method comprises the following steps: converting the target baseband echo after pulse compression obtained in the first step to a frequency domain by using the accurate estimation result of the target motion parameter obtained in the third step, performing motion compensation, synthesizing a broadband by the frequency domain target baseband echo after the motion compensation through a frequency spectrum splicing method, and obtaining a one-dimensional range profile of each frame of signal;
in the first step, the target radar echo is
Wherein N = (M-1) N + □ is the sub-pulse number, M is the frame number, M =1,2,.. The M, M is the frame number of the target baseband echo, N is the number of sub-pulses in each frame signal, h is the number of sub-pulses in the frame, t is the number of sub-pulses in the frame, and p indicating fast time, T p Is the pulse width and defines
Then the
Is the chirp slope, f □ ＝f 0 + □ Δ f is the carrier frequency of each sub-pulse, □ =0,1 0 Is the initial carrier frequency, Δ f is the frequency step interval; b is the sub-pulse bandwidth of the frequency stepping signal;
in the first step, the target baseband echo is:
wherein R is n Is the instantaneous radial distance of the target;
if a point target is maneuvered at the moment t =0, the initial radial distance is R 0 The speed is v, and the initial speed direction is radial; the target performs turning maneuver, the turning angular velocity is omega, and the velocity is not changed when the target maneuvers;
t belongs to [0, MN PRT), PRT is pulse repetition interval, and when the target moves towards the radar direction
K R The complex amplitude of the target echo is shown, and c is the speed of light;
in the first step, the target baseband echo s after pulse compression Rm (n,t p ) Comprises the following steps:
in the second step, the method for constructing the phase compensation factor comprises the following steps:
let R be the target slant distance, R = ct p /2, mixing the product obtained in the first stepRewriting of the target baseband echo after pulse compression to
Wherein, K Rm ＝K R T p B is the complex scattering coefficient of the target, and in practical application, K Rm Is fluctuating and brings about phase noise, for simplicity, it is assumed here that K Rm Is a constant number of times, and is,
for narrow-band distance resolution of frequency step signal and effective coherent accumulation of multi-frame signal, the phase term in the above formula is needed
Compensation is carried out with a corresponding phase compensation factor of
In the third step, the accumulation result matrix G is:
for the motion parameters of the target: r 0 And v and omega are subjected to traversal search, if and only if the search parameter set is equal to the actual target motion parameter, the output of G is maximum, and the peak value detection is carried out on the accumulation result matrix, so that the accurate estimation result of the target motion parameter can be obtained. Considering the traversal of angular velocity, different from the stepped-GRFT which only traverses the radial motion parameters, the algorithm for detecting the maneuvering weak target aiming at the frequency stepping signal defined by the formula is called angular-stepped-GRFT algorithm;
in the fourth step, the frequency domain target baseband echo S after motion compensation is carried out Rm2 (n, f) is:
wherein f E [ -f s /2,f s /2]For fast time frequency, S Rm (n, f) is target baseband echo s after pulse compression Rm (n,t p ) And performing fast time Fourier transform to a frequency domain to obtain the target.
Advantageous effects
The maneuvering weak target motion parameter estimation method based on angular-stepped-GRFT provided by the invention realizes the long-time coherent accumulation motion parameter estimation of a weak target in a circular maneuvering scene. And provides a motion parameter compensation and target one-dimensional range profile focusing method on the basis. Compared with the method of stepped-GRFT and the like, the angular-stepped-GRFT can effectively improve the imaging capability of the frequency stepping radar to the maneuvering weak target.
Drawings
FIG. 1 shows the estimation result of the stepped-RFT parameter;
FIG. 2 is a superimposed one-dimensional distance image of spread-RFT phase-coherent;
FIG. 3 is the Steppled-GRFT parameter estimation (distance-velocity plane);
FIG. 4 is a Steppled-GRFT parameter estimation (acceleration-velocity plane);
FIG. 5 is a one-dimensional range image correlation accumulation result of a stepped-GRFT target;
FIG. 6 is the angular-stepped-GRFT parameter estimation (range-velocity plane);
FIG. 7 is the angular-stepped-GRFT parameter estimation (acceleration-velocity plane);
FIG. 8 is a diagram of coherent accumulation of angular-stepped-GRFT target one-dimensional range profile;
FIG. 9 is a one-dimensional range image coherent accumulation of angular-stepped-GRFT targets (close-up view).
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
A method for estimating the motion parameters of a maneuvering weak target based on angular-stepped-GRFT comprises the following specific steps:
step one, pulse compression.
The frequency stepping radar transmission signal can be expressed as
Where N = (M-1) N + h is the sub-pulse number, M is the frame number, M =1,2. N is the number of the sub-pulses in each frame signal, and h is the serial number of the sub-pulses in the frame. t is t p Indicating fast time, T p Is the pulse width and defines
Is the chirp rate. f. of h ＝f 0 + h Δ f is the carrier frequency of each sub-pulse, h =0,1,. Ang., N-1,f 0 For the initial carrier frequency, Δ f is the frequency step interval.
If a point target is maneuvered at the moment t =0, the initial radial distance is R 0 The speed is v, and the initial speed direction is radial; the target performs a cornering maneuver with a cornering angular velocity ω. Assuming that the speed of the target does not change during maneuvering, the instantaneous radial distance of the target can be expressed as
Wherein, t belongs to [0, MN PRT), PRT is pulse repetition interval. The present invention only discusses the case where the target radial velocity is positive, i.e. the target moves towards the radar direction, when this is the case
Based on the stop-and-go model, the baseband echo obtained by down-converting the target echo is:
wherein, K R The complex amplitude of the target echo, and c the speed of light. The target baseband echo is subjected to pulse compression to obtain a range profile of
Wherein, B is the sub-pulse bandwidth of the frequency stepping signal.
And step two, phase compensation.
Let R be the target slant distance, R = ct p /2, the range image after pulse compression of the target baseband echo can be written as
Wherein, K Rm ＝K R T p And B is the complex scattering coefficient of the target. In practical application, K Rm Is undulating and can introduce phase noise. For simplicity, assume here that K Rm Is a constant.
Narrow-band range resolution for the frequency-stepped signal. For realizing effective coherent accumulation of multi-frame signals, the phase term in the above formula is needed
Compensation is performed by a corresponding phase compensation factor of
And step three, parameter estimation.
Through the first step and the second step, the coherent accumulation algorithm for detecting the maneuvering weak target by aiming at the frequency stepping signal can be obtained
For the motion parameters of the target: r 0 V, ω, the output of G is maximized if and only if the set of search parameters is equal to the target actual motion parameters. And performing peak value detection on the accumulation result matrix to obtain an accurate estimation result of the target motion parameter. Considering the traversal of angular velocity, the algorithm for detecting the maneuvering weak target aiming at the frequency stepping signal defined by the above formula is called angular-stepped-GRFT algorithm, which is different from the stepped-GRFT algorithm only traversing the radial motion parameter.
And step four, motion compensation and focusing.
According to the motion parameter estimation result of angular-stepped-GRFT, motion compensation is carried out on the maneuvering weak target in the frequency domain
Wherein f E [ -f s /2,f s /2]For fast time frequency, S Rm (n, f) obtaining the base band signal by performing fast time Fourier transform to a frequency domain after pulse pressure of the base band signal:
After the motion compensation based on angular-stepped-GRFT, synthesizing a broadband through a frequency spectrum splicing method to obtain a one-dimensional distance image of each frame signal. As the target is a weak target and has the characteristic of low signal-to-noise ratio, the one-dimensional range profile of the M frame signals is summed in a slow time dimension to obtain the one-dimensional range profile after coherent accumulation, namely the focusing of the maneuvering weak target one-dimensional range profile is realized.
The following examples are given to illustrate the inventive process:
the verification conditions of the examples given in the present invention are shown in table 1:
table 1 example verification conditions
Stepped-RFT is a distance-speed two-dimensional parameter search algorithm for a radial moving target under a frequency stepping radar system. When the spread-RFT is used, the speed searching range is set to be 100 m/s-300 m/s. The parameter estimation result obtained by using the stepped-RFT algorithm is shown in figure 1, the target initial radial distance is estimated to be 60.93Tm, and the error is 0.93Tm; the target speed is estimated to be 121.713m/s with an error of 78.287m/s. Fig. 2 shows a target one-dimensional range profile obtained after motion compensation, synthesis wideband processing and coherent integration. It can be seen that accurate estimation and compensation of the motion parameters of the maneuvering weak target cannot be realized by using the stepped-RFT algorithm, and the target is submerged in noise and cannot be correctly focused by the one-dimensional distance image of the target obtained after coherent accumulation.
Stepped-GRFT is a search algorithm aiming at the distance-speed-high-order acceleration of a radial moving target under a frequency stepping radar system. The invention selects three-dimensional stepped-GRFT (distance-speed-acceleration three-dimensional search) with the same dimension as the angular-stepped-GRFT search to simulate. When three-dimensional stepped-GRFT is used, the speed search range is set to be 100-300 m/s, and the acceleration search range is set to be 0-16 m/s 2 And ensures that the acceleration search range covers the variation range of the radial acceleration during the target maneuver. Fig. 3 and 4 show the results of estimating the initial radial distance, initial velocity and acceleration of the target using three-dimensional stepped-GRFT. The target initial radial distance was estimated to be 62.28Tm with an error of 2.28Tm; the target speed is estimated to be 250.934m/s, and the error is 50.934m/s; the target acceleration is estimated to be 1.2366m/s 2 . Fig. 5 shows a target one-dimensional range profile obtained after motion compensation, synthesized wideband processing, and coherent accumulation. It can be seen that the three-dimensional stepped-GRFT algorithm cannot be used for accurately estimating and compensating the motion parameters of the maneuvering weak target, the coherent accumulation is carried out to obtain a one-dimensional distance image of the target, the target is submerged in noise, and the one-dimensional distance image cannot be correctly focused. The three-dimensional stepped-GRFT approaches the motion parameters of the target through distance-speed-acceleration parameter search, however, when the target maneuvers, the radial acceleration changes, so that the motion compensation based on the three-dimensional stepped-GRFT is not in place, and further the focusing of a one-dimensional range image cannot be realized. When higher-order acceleration is selected to carry out stepped-GRFT parameter search, although the error of motion parameter estimation can be reduced, and the estimation result is closer to the actual motion state of the target, the fact that the target motion state is described by using the higher-order radial acceleration means four-dimensional search or even more-dimensional search, and compared with three-dimensional search, the method brings great calculation burden and has no realizability.
When the angular-stepped GRFT provided by the invention is used for parameter estimation, the speed search range is set to be 100-300 m/s, and the angular speed search range is set to be 0-0.3 rad/s. In contrast, fig. 6 and 7 show the estimation results of the initial distance, initial velocity and angular velocity of the target based on angular-stepped-GRFT. The target initial distance is estimated to be 60Tm with an error of 0; the initial velocity is estimated to be 199.994m/s, and the error is 0.006m/s; the angular velocity is estimated to be 0.19994rad/s with an error of 6X 10 -5 rad/s. FIGS. 8 and 9 show the coherent accumulation results of the target one-dimensional range images obtained by the angular-stepped-GRFT algorithm of the present invention. The peak value of the target can be clearly observed from the coherent accumulation result, and the initial distance is estimated to be 60Tm and is consistent with the simulation condition. Obviously, when the frequency stepping signals are used for measuring the motion parameters of the maneuvering weak target, the target motion parameter estimation and one-dimensional range image focusing algorithm based on angular-stepped-GRFT has better performance.
The results show that after the method provided by the invention is adopted for parameter estimation and motion compensation, the accurate estimation of the target motion parameters and the focusing of the one-dimensional distance image under the weak target circular maneuver scene are realized, and the superiority of the method is shown compared with the conventional methods of clamped-RFT and clamped-GRFT. In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A method for estimating motion parameters of a maneuvering weak target based on angular-contained-GRFT is characterized by comprising the following steps:
step one, performing down-conversion on a target radar echo to obtain a target baseband echo, and performing pulse compression on the obtained target baseband echo to obtain a target baseband echo after pulse compression;
step two, constructing a phase compensation factor, and compensating the phase term of the target baseband echo after the pulse compression obtained in the step one by using the constructed phase compensation factor;
and step three, performing traversal search on the target motion parameters in the phase compensation factors constructed in the step two to obtain an accumulation result matrix, wherein if and only if the searched target motion parameters are equal to the target actual motion parameters, a peak value appears in the accumulation result matrix, and the target motion parameters corresponding to the peak value are accurate estimation results of the target motion parameters.
2. The method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 1, wherein:
in the first step, the target radar echo is
Wherein N = (M-1) N + □ is the sub-pulse number, M is the frame number, M =1,2,.. The M, M is the frame number of the target baseband echo, N is the number of sub-pulses in each frame signal, h is the sub-pulseSequence numbers, t, flushed in frames p Indicating fast time, T p Is the pulse width and defines
Then
Is the chirp slope, f □ ＝f 0 + □ Δ f is the carrier frequency of each sub-pulse, □ =0,1 0 Is the initial carrier frequency, Δ f is the frequency step interval; and B is the sub-pulse bandwidth of the frequency stepping signal.
3. The method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 2, characterized in that:
in the first step, the target baseband echo is:
wherein R is n Is the instantaneous radial distance of the target;
if a point target is maneuvered at the moment t =0, the initial radial distance of the point target is R 0 The speed is v, and the initial speed direction is radial; the target performs turning maneuver, the turning angle speed is omega, and the speed is not changed when the target maneuvers;
t belongs to [0, MN is PRT), PRT is pulse repetition interval, and when the target moves towards the radar direction
K R The complex amplitude of the target echo, c is the speed of light.
4. The method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in any one of claims 1 to 3, characterized in that:
in the first step, the target baseband echo s after pulse compression Rm (n,t p ) Comprises the following steps:
5. the method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 1, wherein:
in the second step, the method for constructing the phase compensation factor comprises the following steps:
let R be the target slope distance, R = ct p Rewriting the target baseband echo after pulse compression obtained in the step one into
Wherein, K Rm ＝K R T p B is the complex scattering coefficient of the target, K Rm Is a constant number of times, and is,
for narrow band range resolution of frequency step signal, for phase terms
Compensation is performed by a corresponding phase compensation factor of
6. The method for estimating the motion parameters of the maneuvering weak target based on angular-contained-GRFT as claimed in claim 1, characterized in that:
in the second step, the constructed phase compensation factor includes a target motion parameter, and the target motion parameter includes a distance R between a target initial position and the radar 0 A target initial velocity v and a target dynamic angular velocity ω.
7. The method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 1, wherein:
in the third step, the accumulation result matrix G is:
8. the method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 1, wherein:
in the fourth step, the frequency domain target baseband echo S after motion compensation is carried out Rm2 (n, f) is:
wherein f E [ -f s /2,f s /2]For fast time frequency, S Rm (n, f) is a target baseband echo s after pulse compression Rm (n,t p ) And performing fast time Fourier transform to a frequency domain to obtain the target.
9. The method for estimating the motion parameters of the maneuvering weak target based on angular-stepped-GRFT as claimed in claim 1, wherein:
the accuracy of the estimated value of the target motion parameter is evaluated by the following method: and D, converting the pulse-compressed target baseband echo obtained in the step one to a frequency domain by using the accurate estimation result of the target motion parameter obtained in the step three, performing motion compensation, synthesizing a broadband by using the frequency domain target baseband echo subjected to the motion compensation through a frequency spectrum splicing method to obtain a one-dimensional range profile of each frame of signal, summing the one-dimensional range profiles of each frame of signal in a slow time dimension to obtain a one-dimensional range profile after coherent accumulation, realizing the focusing of the one-dimensional range profile of the maneuvering weak target, and obtaining the accuracy of the estimated value of the target motion parameter according to the error between the one-dimensional range of the peak value of the focusing result and the target range set by the simulation parameter.
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