CN113009465B - Robust adaptive pulse compression method based on two-time phase compensation - Google Patents

Robust adaptive pulse compression method based on two-time phase compensation Download PDF

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CN113009465B
CN113009465B CN202110242322.7A CN202110242322A CN113009465B CN 113009465 B CN113009465 B CN 113009465B CN 202110242322 A CN202110242322 A CN 202110242322A CN 113009465 B CN113009465 B CN 113009465B
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CN113009465A (en
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黄勇
裴家正
薛永华
宋伟健
王国庆
丁昊
夏沭涛
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Naval Aeronautical University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/10—Systems for measuring distance only using transmission of interrupted, pulse modulated waves
    • G01S13/26—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave
    • G01S13/28—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses
    • G01S13/282—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses using a frequency modulated carrier wave
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/2813—Means providing a modification of the radiation pattern for cancelling noise, clutter or interfering signals, e.g. side lobe suppression, side lobe blanking, null-steering arrays

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Abstract

The invention discloses a steady self-adaptive pulse compression method based on two-time phase compensation, which comprises the steps of firstly compensating phase mismatch caused by distance sampling mismatch, and then compensating phase mismatch caused by intra-pulse Doppler mismatch; and finally, realizing range sidelobe suppression by using a dimension reduction self-adaptive pulse compression method. According to the invention, through sequentially estimating the distance sampling mismatch amount and the Doppler mismatch amount, the phase mismatch caused by distance sampling mismatch and Doppler mismatch in the echo is compensated, and the problem that the self-adaptive pulse compression output distance side lobe is obviously increased caused by the phase mismatch is solved; meanwhile, aiming at the problem of mutual influence of multi-target distance side lobes in distance dimensional data, the invention describes the mutual influence degree of the multiple targets by constructing covariance matrixes among different matched filtering waveforms, and further inhibits the distance side lobes of the multiple targets by the inverse operation of the covariance matrixes.

Description

Robust adaptive pulse compression method based on two-time phase compensation
Technical Field
The invention relates to the field of radar signal processing, in particular to the field of adaptive pulse compression of radar signals, and particularly relates to a robust adaptive pulse compression method based on two-time phase compensation.
Background
With the wide application of radar technology, users have higher and higher requirements on performance indexes such as the acting distance, the distance resolution capability and the measurement precision of a radar system, and the pulse compression technology based on a large-time width-bandwidth product signal can simultaneously meet the requirements of the radar system on the detection distance and the distance resolution of the radar.
Conventional pulse compression techniques are typically implemented using Matched Filter (MF) filters. The matched filter is an optimal linear filter that maximizes the output signal-to-noise ratio under point target and white gaussian noise conditions. In practice, however, the output of the matched filter has the problem that strong object range sidelobes may obscure the adjacent weak object main lobe. Windowing pulse compression techniques can suppress part of the range side lobe energy of strong targets, but have limited effectiveness. The self-adaptive pulse compression method provides a good idea for solving the problem. The Adaptive Pulse Compression (APC) method based on iterative Minimum Mean Square Error (RMMSE) proposed by Blunt professor designs a corresponding Adaptive filter for each distance unit by using a target distance dimension power value and by reversingAnd good range sidelobe suppression performance can be obtained through multiple iterations. However, there may be a Doppler frequency f in the target echo pulsedThis will cause doppler mismatch between the complex amplitude of the target echo sampling point and the chirp waveform, which in turn causes phase mismatch between the two. Aiming at the condition of Doppler mismatch, Blunt professor provides a self-adaptive pulse compression method based on Doppler compensation, namely, self-adaptive pulse compression is carried out on the basis of estimating and compensating intra-pulse Doppler frequency, so that the problem of serious reduction of self-adaptive pulse compression performance caused by Doppler mismatch is avoided.
The above adaptive pulse compression methods all assume that the target point is located on the sampling point, i.e. the distance sampling mismatch is not considered. The distance sampling mismatch is that when the radar performs distance dimensional sampling on a target echo pulse signal, a sampling point is not exactly located on a distance point where the target is located, so that the distance of the echo sampling point is different from the real distance of the target, and further, phase mismatch occurs between the complex amplitude of the echo sampling point and the complex amplitude of the real point of the target. This is a very common phenomenon. For a commonly used chirp signal, the range sampling mismatch will make it difficult for the echo to form a deep notch at the range side lobe during the adaptive pulse compression process, thereby causing a serious degradation of the adaptive pulse compression performance. In this regard, the teaching team of Blunt proposed an oversampling strategy in one range unit to suppress the effect of the range sampling mismatch, but oversampling would result in a large increase in memory and computation. However, the adaptive pulse compression method based on the linear constraint minimum variance criterion proposed by leixiou et al solves the problem of distance sampling mismatch by setting main lobe width and interference zero constraint conditions, but the algorithm needs to define the strength of a target in advance, which is difficult to operate quantitatively in practice. Moreover, the problem of adaptive pulse compression under the condition of simultaneous occurrence of Doppler mismatch and range sampling mismatch is not reported at present.
Disclosure of Invention
In order to solve the technical problem of adaptive pulse compression under the condition that Doppler mismatch and distance sampling mismatch occur simultaneously, the invention provides a robust adaptive pulse compression method based on two-time phase compensation, which comprises the steps of firstly compensating the phase mismatch caused by the distance sampling mismatch and then compensating the phase mismatch caused by intra-pulse Doppler mismatch; and finally, realizing range sidelobe suppression by using a dimension reduction self-adaptive pulse compression method.
In order to achieve the purpose, the invention adopts the technical scheme that:
a robust adaptive pulse compression method based on two-time phase compensation specifically comprises the following steps:
s1, performing matched filtering on the input distance dimension echo data by using a linear frequency modulation signal sequence, and finding a maximum value point in an envelope of an output result;
s2, estimating the distance sampling mismatch amount and the Doppler mismatch amount corresponding to the maximum point by using the distance dimension echo data corresponding to the maximum point, so as to construct a new matched filter subjected to distance sampling mismatch compensation and Doppler mismatch compensation, and storing the new matched filter in a new matched filter set;
s3, using all new matched filters in the new matched filter set to perform dimension reduction self-adaptive pulse compression processing on the input distance dimension echo data, and outputting a processing result zP；
S4, outputting the processing result zPSearching for a maximum point with a new SNR not less than a given threshold, repeating S2-S4 if such a maximum point exists, otherwise ending the process, and outputting zPIs the final processing result of the algorithm.
Preferably, the method for selecting the given threshold in S1 is as follows: the pulse compression waveform commonly used by radar is a chirp waveform, the average major-minor ratio of the waveform matching filter output is generally about 50dB, and therefore, the value interval of a given threshold is set as [48dB,52dB ].
Preferably, the distance sampling mismatch estimation in S2 specifically includes:
partitioning the linear frequency modulation signal sequence used for matched filtering in the S1 to construct a matched filter matrix; distance dimensional echo data corresponding to the maximum point in the matched filter matrix S2Performing product operation, dividing the two adjacent elements in the output vector, and averaging the quotient phases to obtain the equivalent mismatch phase estimation value caused by distance sampling mismatch and Doppler mismatch
Figure BDA0002962661210000031
By quantizing the sampling interval, the estimation value of the distance sampling mismatch amount can be obtained according to the equivalent mismatch phase estimation
Figure BDA0002962661210000032
Preferably, the estimation of the doppler mismatch amount in S2 specifically includes:
compensating the matched filter by using the estimation value of the distance sampling mismatch amount to obtain the matched filter subjected to distance sampling mismatch compensation; partitioning the matched filter to construct a matched filter matrix; the distance dimension echo data corresponding to the maximum point in the S2 and the matched filter matrix are subjected to product operation, then the two adjacent elements in the output vector are used for division, and the quotient phase is averaged, so that the equivalent mismatch phase estimation value caused by Doppler mismatch can be obtained
Figure BDA0002962661210000033
Thereby obtaining an estimate of the amount of Doppler mismatch
Figure BDA0002962661210000041
Preferably, the method for calculating the full vector w (l) in the dimension reduction adaptive pulse compression processing in S3 specifically includes:
the dimension reduction self-adaptive pulse compression processing comprises three times of iteration processing; in the third iteration, all the new matched filters with distance sampling mismatch compensation and doppler mismatch compensation in the new matched filter set described in S2 are used to solve the covariance matrix corresponding to each new matched filter, and then w (l) is calculated as follows,
Figure BDA0002962661210000042
wherein the content of the first and second substances,
Figure BDA0002962661210000043
the covariance matrix corresponding to the ith new matched filter; when a new matched filter is associated with a distance sample/,
Figure BDA0002962661210000044
is the new matched filter, otherwise
Figure BDA0002962661210000045
Is the matched filter described in S1.
The invention has the beneficial effects that:
(1) the invention compensates the phase mismatch caused by the distance sampling mismatch and the Doppler mismatch in the echo by sequentially estimating the distance sampling mismatch amount and the Doppler mismatch amount, and solves the problem that the self-adaptive pulse compression output distance side lobe is obviously increased caused by the phase mismatch.
(2) Aiming at the problem of mutual influence of multi-target distance side lobes in distance dimensional data, the mutual influence degree of the multiple targets is described by constructing covariance matrixes among different matched filtering waveforms, and further the distance side lobes of the multiple targets are restrained by means of covariance matrix inversion operation.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flow chart of a robust adaptive pulse compression method based on two-time phase compensation according to the present invention.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example 1
This embodiment 1 provides a robust adaptive pulse compression method based on two phase compensations, which specifically includes the following steps:
s1, carrying out matched filtering on the input radar distance dimension echo data y by using the linear frequency modulation signal sequence S transmitted by the matched filter, and outputting a processing result z0Finding the maximum value point of the envelope of the processing result; meanwhile, recording the number of times of the cyclic treatment (P is 0);
wherein, the transmitted chirp signal waveform obtains a chirp signal sequence under a 1-time bandwidth sampling condition, which is recorded as s:
Figure BDA0002962661210000051
where N is the number of sampling points in a pulse, ξ is the chirp rate, T issIs the intra-pulse sampling interval.
S2, aiming at the envelope maximum value point with the signal-to-noise-plus-noise ratio not less than 50dB, estimating the distance sampling mismatch quantity, and then, compensating the phase mismatch caused by the distance sampling mismatch in the linear frequency modulation signal sequence to construct a matched filter subjected to distance sampling compensation;
s21, searching an envelope maximum value point with the signal-to-noise-ratio not less than 50dB from the processing result;
for the P-th cycle, if the SNR corresponding to the envelope maximum point is less than 50dB and P is 0, then the calculation is carried outAfter the method is finished, outputting a processing result z0(ii) a If the signal-to-noise-and-noise ratio corresponding to the envelope maximum point is less than 50dB and P>0, the algorithm is ended, and a processing result z is outputP；
If the signal-to-noise-and-noise ratio corresponding to the envelope maximum point is not less than 50dB, the distance position corresponding to the envelope maximum point is given as P +1 and is marked as aPAnd a isPStoring the data into the set A and simultaneously extracting a in the input distance dimension echo data yPAll sampling points in the corresponding echo pulse are recorded as:
y(aP)＝[y(aP),y(aP+1),＝,y(aP+N-1)]T
where the superscript T represents the transpose of the vector or matrix.
S22, aiming at the envelope maximum value point with the signal-to-noise-plus-noise ratio not less than 50dB, estimating the distance sampling mismatch quantity, and then, compensating the phase mismatch caused by the distance sampling mismatch in the linear frequency modulation signal sequence to construct a matched filter subjected to distance sampling compensation;
and partitioning the linear frequency modulation signal sequence s to construct a matched filter matrix. Matching the matched filter matrix with y (a)P) Performing product operation, estimating the amount of mismatching of distance samples by using the product result, compensating the phase mismatching caused by the mismatching of distance samples in s, and constructing a matched filter subjected to the mismatching compensation of distance samples
Figure BDA0002962661210000061
The method specifically comprises the following steps: first, for the P-th cycle, the chirp sequence s is divided into M +1 blocks, M being N/2, to construct a matched filter matrix DMF。
Figure BDA0002962661210000062
Wherein the content of the first and second substances,
Figure BDA0002962661210000063
is the m +1 th block of sVector, M is more than or equal to 0 and less than or equal to M; the superscript H denotes the conjugate transpose of the vector or matrix.
Then, the matched filter matrix D is processedMFAnd y (a)P) Performing product operation to obtain M +1 dimensional vector g (a)P)＝DMFy(aP)。
Since it is for large targets with signal-to-noise-and-noise ratios greater than 50dB, range position aPCorresponding y (a)P) All sampling points y (a)P),y(aP+1),…,y(aPThe amplitude of + N-1) may be determined by the amplitude of the large target
Figure BDA0002962661210000071
To approximate. Thus, y (a)P) Can be rewritten as:
Figure BDA0002962661210000072
where Δ t represents the distance sample mismatch, fdIndicating doppler mismatch.
Thus, g (a) can be obtainedP)＝[g(0)(aP),g(1)(aP),…,g(m)(aP),…,g(M)(aP)]TThe m +1 th element of (b) is:
Figure BDA0002962661210000073
mixing g (a)P) Dividing the two adjacent elements, averaging the phases to obtain the equivalent mismatch phase caused by distance sampling mismatch and Doppler mismatch, and recording as
Figure BDA0002962661210000074
Figure BDA0002962661210000075
Wherein angle [. cndot.) represents solving a phase angle function.
Spacing the samples by TsDivided into q portions on average, each portion having a time span of Δ T ═ TsAnd/q, the distance sampling mismatching degree delta T can be quantized by utilizing delta T. Then consider ξ Δ t > fdBy using
Figure BDA0002962661210000076
Obtaining an estimate of the amount of distance sampling mismatch
Figure BDA0002962661210000077
Figure BDA0002962661210000078
In the formula (I), the compound is shown in the specification,
Figure BDA0002962661210000079
indicating a rounding down operation.
Using estimated values of mismatching quantities for distance sampling
Figure BDA00029626612100000710
Compensating the phase mismatch in s due to the mismatch of the distance samples to obtain a matched filter compensated for the mismatch of the distance samples, which is recorded as
Figure BDA0002962661210000081
Figure BDA0002962661210000082
S3, estimating Doppler mismatch quantity, compensating phase mismatch caused by Doppler mismatch on the basis of the matched filter which is constructed in the step S2 and subjected to distance sampling mismatch compensation, and forming a new matched filter set B which is subjected to distance sampling mismatch compensation and Doppler mismatch compensation;
constructed for step S2
Figure BDA0002962661210000083
And partitioning to obtain a new matched filter matrix. Matching the matched filter matrix with y (a)P) Performing multiplication operation, and estimating Doppler mismatch amount by using the multiplication result for compensation
Figure BDA0002962661210000084
Constructing a new matched filter due to phase mismatch caused by Doppler mismatch, and storing the matched filter in a new matched filter set B subjected to distance sampling mismatch compensation and Doppler mismatch compensation;
the method specifically comprises the following steps:
for the P-th cycle, the
Figure BDA0002962661210000085
Divided into M +1 blocks, M being N/2, to construct a matched filter matrix EMF。
Figure BDA0002962661210000086
Wherein the content of the first and second substances,
Figure BDA0002962661210000087
is composed of
Figure BDA0002962661210000088
M is more than or equal to 0 and less than or equal to M.
Using a matched filter matrix EMFFor y (a)P) Performing product operation to obtain M +1 dimensional vector h (a)P)＝EMFy(aP)。
H (a)P) Dividing the two adjacent elements, averaging the phases to obtain the equivalent mismatch phase caused by Doppler mismatch, and recording as
Figure BDA0002962661210000089
Figure BDA00029626612100000810
Wherein h is(m)(aP) Is h (a)p) The (m +1) th element of (2) can be represented as:
Figure BDA0002962661210000091
due to the fact that
Figure BDA0002962661210000092
By using
Figure BDA0002962661210000093
Estimating the amount of doppler mismatch
Figure BDA0002962661210000094
Using estimated values of Doppler mismatch
Figure BDA0002962661210000095
Compensation
Figure BDA0002962661210000096
The phase mismatch due to the doppler mismatch is minimized to obtain a new matched filter, denoted as
Figure BDA0002962661210000097
Figure BDA0002962661210000098
And will be
Figure BDA0002962661210000099
Storing in a new matched filter set B after distance sampling mismatch compensation and Doppler mismatch compensation, and the one in B
Figure BDA00029626612100000910
And a in the set APAnd correspond to each other.
And S4, performing dimension reduction self-adaptive pulse compression processing on the input distance dimension echo data by using the new matched filter set B, and searching a new envelope maximum value point in the output processing result.
And performing dimension reduction adaptive pulse compression processing based on a minimum variance distortionless response principle on the input distance dimension echo data y by using all the new matched filters subjected to the distance sampling mismatch compensation and the doppler mismatch compensation in the new matched filter set B output in the step S3. The process involves 3 loop iterations.
When r is 0, in I
Figure BDA00029626612100000911
Respectively performing matched filtering with the input distance dimension echo data y, and performing modular squaring on the filtering result to obtain the power value
Figure BDA00029626612100000912
Figure BDA00029626612100000913
Wherein y (l) ═ y (l), y (l +1), …, y (l + N-1)]T；
When r is 1 and 2, firstly
Figure BDA00029626612100000914
And C blocks are divided, wherein C is an integer which is more than 1 and less than N, and N can be divided.
Figure BDA00029626612100000915
The C (C is 1, …, C) th block
Figure BDA00029626612100000916
Is a vector of length K-N/C, expressed as:
Figure BDA00029626612100000917
for distance position l, (r-1) (N-1)<l<Computing a covariance matrix by | | | - (r-1) (N-1) | | | y | | | representing the length of y
Figure BDA0002962661210000101
Figure BDA0002962661210000102
Wherein the content of the first and second substances,
Figure BDA0002962661210000103
the c sub-array of
Figure BDA0002962661210000104
Comprises the following steps:
Figure BDA0002962661210000105
in the above formula
Figure BDA0002962661210000106
So as to make
Figure BDA0002962661210000107
K-dimensional vector obtained for base shift:
Figure BDA0002962661210000108
if K < N + cK or K > (c-1) K during the shift process is such that one or more of the index values of (c-1) K-K, (c-1) K-K +1, (c-1) K-K +2, (c-1) K-K +3, …, cK-K-1 is less than 0 or greater than N-1, then it is desirable that
Figure BDA0002962661210000109
The element of the corresponding position in (1) is replaced with 0.
The estimated value of the distance dimension echo power value output by the r iteration is calculated by the following formula,
Figure BDA00029626612100001010
traverse all l, (r-1) (N-1)<l<Y | - (r-1) (N-1), and all i, i ═ 1,2, …, P, calculated
Figure BDA00029626612100001011
When r is 3, the same calculation method as in the case of r 1 and 2 is used for calculation
Figure BDA00029626612100001012
Further, a weight vector w (l) is calculated,
Figure BDA00029626612100001013
wherein, when l ═ aiWhen being e.g. A, then
Figure BDA00029626612100001014
By using
Figure BDA00029626612100001015
Substituting calculation, otherwise
Figure BDA00029626612100001016
Substituting s for the calculation. I is unit matrix, noise variance
Figure BDA0002962661210000111
May be given by a radar system.
Calculating zP(l)＝wH(l) y (l), go through all l, (r-1) (N-1)<l<The final output result z of the dimension reduction self-adaptive pulse compression is obtained by | | | y | - (r-1) (N-1)P＝[zP((r-1)(N-1)+1)，…，zP(||y||-(r-1)(N-1)-1)]T。
S5, output z to step S4PTaking the envelope to obtain | zPI, and i zPI search for a new envelope maximum point, where "new" means that a new search is madeIs not in set a; then, the process proceeds to step S2.
In conclusion, the invention compensates the phase mismatch caused by the distance sampling mismatch and the Doppler mismatch in the echo by sequentially estimating the distance sampling mismatch amount and the Doppler mismatch amount, and solves the problem that the self-adaptive pulse compression output distance side lobe is obviously increased caused by the phase mismatch; meanwhile, aiming at the problem of mutual influence of multi-target distance side lobes in distance dimensional data, the invention describes the mutual influence degree of the multiple targets by constructing covariance matrixes among different matched filtering waveforms, and further inhibits the distance side lobes of the multiple targets by the inverse operation of the covariance matrixes.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.

Claims (3)

1. A robust adaptive pulse compression method based on two-time phase compensation is characterized in that:
s1, performing matched filtering on the input distance dimension echo data, and searching a maximum value point with a signal-to-noise ratio not less than a given threshold in an output result of the matched filtering;
s2, estimating the distance sampling mismatch amount and the Doppler mismatch amount corresponding to the maximum point by using the distance dimension echo data corresponding to the maximum point, so as to construct a new matched filter which is subjected to distance sampling mismatch compensation and Doppler mismatch compensation, and storing the new matched filter into a new matched filter set;
the distance sampling mismatching estimation specifically comprises: partitioning the linear frequency modulation signal sequence used for matched filtering in the S1 to construct a matched filter matrix; the matched filter matrix is multiplied by the distance dimension echo data corresponding to the maximum point in S2, then the two adjacent elements in the output vector are used for division, and the quotient phase is averaged to obtain the distance sampling mismatch and Doppler mismatch guideEquivalent mismatch phase estimation
Figure FDA0003581054640000011
Then, the sampling interval is quantized to obtain the estimated value of the distance sampling mismatching amount
Figure FDA0003581054640000012
Where ξ is the chirp rate, T, of the chirp signalsFor intra-pulse sampling intervals, the sampling interval TsDivided into q portions on average, each portion having a time span of Δ T ═ Ts/q；
The doppler mismatch amount estimation specifically is: compensating the matched filter by using the estimation value of the distance sampling mismatch amount to obtain the matched filter subjected to distance sampling mismatch compensation; partitioning the matched filter to construct a matched filter matrix; performing product operation on the matched filter matrix and distance dimension echo data corresponding to the maximum point in S2, then dividing the distance dimension echo data by using front and back adjacent elements in an output vector, and averaging the quotient phases to obtain an equivalent mismatch phase estimation value caused by Doppler mismatch
Figure FDA0003581054640000013
Thereby obtaining an estimate of the amount of Doppler mismatch
Figure FDA0003581054640000014
S3, using all new matched filters in the new matched filter set to perform dimension reduction self-adaptive pulse compression processing on the input distance dimension echo data, searching a new maximum point with a signal-to-noise-plus-noise ratio not less than a given threshold in the output result, repeating S2 and S3 if the maximum point exists, otherwise, ending the processing process, and outputting the dimension reduction self-adaptive pulse compression processing result as the final processing result of the algorithm.
2. The robust adaptive pulse compression method based on two-time phase compensation according to claim 1, wherein the selection method of the given threshold in S1 is specifically: the value interval of the given threshold is set as [48dB,52dB ].
3. A robust adaptive pulse compression method based on two-time phase compensation according to claim 1, wherein the method for calculating the weight vector w (l) in the dimension-reduced adaptive pulse compression process in S3 specifically comprises:
in the third iteration, all the new matched filters with distance sampling mismatch compensation and doppler mismatch compensation in the new matched filter set described in S2 are used to solve the covariance matrix corresponding to each new matched filter, and then w (l) is calculated as follows,
Figure FDA0003581054640000021
wherein the content of the first and second substances,
Figure FDA0003581054640000022
for the noise variance, given by the radar system, σnIs that
Figure FDA0003581054640000023
The square of (a), representing the noise standard deviation;Iis a matched filter set obtained after distance sampling mismatch compensation and Doppler mismatch compensation, and is e toI(ii) a I is a unit array;
Figure FDA0003581054640000024
the covariance matrix corresponding to the ith new matched filter; when a new matched filter is associated with a distance sample/,
Figure FDA0003581054640000025
is the new matched filter, otherwise
Figure FDA0003581054640000026
That is, as described in S1And a matched filter.
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