CN106707280B - Synthetic aperture radar virtual base estimation method based on registration and curve matching - Google Patents

Synthetic aperture radar virtual base estimation method based on registration and curve matching Download PDF

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CN106707280B
CN106707280B CN201510787599.2A CN201510787599A CN106707280B CN 106707280 B CN106707280 B CN 106707280B CN 201510787599 A CN201510787599 A CN 201510787599A CN 106707280 B CN106707280 B CN 106707280B
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baseline
registration
synthetic aperture
aperture radar
value
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CN106707280A (en
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陈朝焰
赵元楠
陆加
吕瑞恒
胡珊
田野
陈德红
李晨
黄伟忠
杨革文
雷明兵
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Shanghai Institute of Electromechanical Engineering
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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
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques
    • G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
    • 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
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention discloses the polarization sensitive synthetic aperture radar system virtual base estimation methods based on registration and curve matching, comprising: Step 1: determining baseline search collection；Step 2: carrying out rough registration using Multichannel SAR data of the baseline value in search collection to input；Step 3: obtaining the relevance degree of the interchannel after rough registration；Step 4: the sample point using the relevance degree obtained carries out high order fitting, the curve of relationship between the description degree of correlation and baseline value is obtained；Step 5: finding the maximum value of fitting curve obtained, the corresponding baseline value of the maximum value is virtual base.The present invention provides the methods of reliable estimation polarization sensitive synthetic aperture radar system virtual base.

Description

Synthetic aperture radar effective baseline estimation method based on registration and curve fitting
Technical Field
The invention belongs to the field of physics, and particularly relates to a method for obtaining accurate baseline estimation by rough registration and curve fitting in the field of synthetic aperture radars.
Background
In the field of synthetic aperture radar, the estimation and the relocation of the moving target speed both need to utilize the information of a base line. In practice, the value of the baseline is usually an equivalent baseline value obtained by geometric equivalence. However, due to errors in the heading of the platform, errors in the antenna pattern, differences in the system functions between the channels, and the noise-to-noise ratio (CNR), etc., the equivalent baseline value will usually deviate from the effective baseline that is actually present in the system, and these errors will propagate into the velocity estimation and repositioning results of the moving target. For this reason, the problem of estimation of the effective baseline that is actually present in the system needs to be solved.
Currently, effective baseline estimation techniques in synthetic aperture radar systems are primarily accomplished by estimating the slope of the phase ramp Along Track Interference (ATI). Gierll proposes a method based ON Eigenvalue Decomposition (EDB) in the document "C.H. Gierll, 'Digital channel balancing of analog-track interferometric SAR data,' DRDC, Ottawa, ON, Canada, Tech. Rep.TM. 2003-024, Mar. 2003". The basic idea is to obtain an estimate of the linear interference phase slope in the range-doppler domain by eigenvalue decomposition of the sample covariance matrix and then estimate the effective baseline from the slope of the phase slope. In the method, in order to reduce the variance of the baseline estimation, the estimation of the sample covariance matrix needs to be carried out on all range gates, and the number of the range gates in the synthetic aperture radar data can easily reach thousands of orders of magnitude, so the algorithm is time-consuming. Furthermore, Chen et al in the documents "Z. -Y. Chen, T. Wang, and N. Ma, 'Accurate base estimation for synthetic aperture radio-ground and moving target indication systems based on-co-registration and media filtering,' IETRadar solar Navig., vol. 8, No. 6, pp. 607-. This method also obtains an accurate baseline estimate by estimating the slope of the phase ramp.
Although the two baseline estimation techniques based on estimating the slope of the phase slope can accurately estimate the effective baseline, these methods need to select phase samples located in the main beam of the antenna, and thus depend on the accuracy of doppler center frequency estimation. However, the estimation error of the doppler center frequency is usually in the order of one percent of the pulse repetition frequency, and different doppler center frequency estimation algorithms can be used to obtain different center frequency values. Thus, the baseline estimation techniques described above are not robust.
Disclosure of Invention
The invention solves the problem that the estimation precision of the existing effective baseline estimation method depends on the estimation precision of Doppler center frequency, namely the problem that the baseline estimation technology is not stable; to solve the problems, the invention provides an effective baseline estimation method of a synthetic aperture radar system based on registration and curve fitting.
The method for estimating the effective baseline of the synthetic aperture radar system based on registration and curve fitting comprises the following steps:
step one, determining a baseline search set;
step two, carrying out coarse registration on the input multichannel synthetic aperture radar data;
step three, obtaining correlation values among channels after coarse registration;
step four, fitting a curve describing the relation between the correlation degree and a base line value by using the obtained sample points of the correlation degree value;
and step five, searching the maximum value of the curve obtained by fitting, wherein the base line value corresponding to the maximum value is the effective base line.
Further, the baseline corpus is initialized toWherein，，is an equivalent baseline value obtained by geometric equivalence. Here, the total deviation of the baseline estimation is assumedNot more than。
Further, the baseline corpus is:
wherein,
，
，
，
indicating that the rounding operation is performed to the nearest integer.
Further, the second step comprises:
step 2.1, transforming the input synthetic aperture radar data into a range-doppler domain,andrespectively, the range-doppler domain signals of the 1 st and 2 nd channels, wherein,represents the distance dimension time,Indicates the Doppler frequency,Indicates the effective baseline,Representing the flight speed of the synthetic aperture radar platform along the course;
step 2.2, taking the channel 1 as a reference, and utilizing a baseline search setThe values in (a) perform a coarse registration on channel 2, which may be described as:
wherein,indication interestBy usingTo pairThe output signal obtained by the coarse registration is carried out,。
further, the expression of the correlation value between channels after coarse registration is:
wherein,is a constant, and:
。
further, the fourth step includes: performing curve fitting by using the obtained correlation degree sample to obtain a function valueFitting correlation values in the sense of minimum mean square errorSaid fitting functionExpressed as:
，。
further, the fifth step includes:
step 5.1, utilizing the six-order polynomial obtained in the step fourCoefficient of (2)Construct a function of the correlation values with respect to the baseline value:
，
step 5.2, correlation functionThe maximum value of (a) is the effective baseline:
。
compared with the prior art, the invention has the following advantages:
firstly, the cross-correlation characteristic information among channels is fully utilized, the problem of instability in Doppler center frequency estimation is solved, and therefore a stable effective baseline estimation value can be obtained;
secondly, the sample points of the correlation degrees at different baseline values are obtained by adopting a baseline search coarse registration mode, and the method is simple in flow design;
thirdly, the method completes the estimation of the function of the correlation degree relative to the baseline value by using a curve fitting mode, and has the advantages of high speed and high precision.
Drawings
Fig. 1 is an operation flowchart of an effective baseline estimation method of a synthetic aperture radar system based on registration and curve fitting according to an embodiment of the present invention.
Fig. 2 is a comparison diagram of a fitted curve obtained by the method for estimating an effective baseline of a synthetic aperture radar system based on registration and curve fitting according to an embodiment of the present invention and an original sample point.
Fig. 3 is a graph comparing the performance of the registration and curve fitting based synthetic aperture radar system effective baseline estimation method with the EDB method (eigenvalue decomposition based method) and the CMB method (registration and median filtering based method) provided by the embodiment of the present invention.
Detailed Description
The invention is further illustrated below with reference to the figures and examples. For the baseline estimation of the multi-channel system, without loss of generality, the embodiment of the present invention is schematically illustrated by taking the estimation of the effective baseline between the channel 1 and the channel 2 as an example, and the effective baselines between other channels can be estimated by the same method.
Referring to fig. 1, multi-channel data of a synthetic aperture radar is first input and transformed into a range-doppler domain. The range-Doppler domain signals of channel 1 and channel 2 are recorded asAndthen it can be correlated with the following equation:
wherein,representing a distance dimension time;
representing the azimuth dimension frequency, i.e., the doppler frequency;
represents a valid baseline;
representing the speed of flight of the synthetic aperture radar platform along the heading.
Subject to various error sources, effective baselinesWill deviate from the equivalent baseline obtained by geometric equivalenceHowever, total deviationIs not greater thanThus, the baseline search interval used for coarse registration can be initialized toWherein the smallest possible baseline valueMaximum possible baseline value。
To estimate effective baselinesThe following input parameters are initialized:
1) equivalent base line. The equivalent base line is obtained by geometric equivalence. For example, for transmitting multiple signals with one antenna at intervals along the heading ofIn the case of simultaneous reception by the antennas,。
2) decimal point number to which baseline value at initial sample point is accurate. For example, ifThe baseline value at the initial sample point is accurate tom is also 1 cm.
3) Decimal point number required for baseline estimation. For example, ifThe baseline estimation needs to be accuratem。
The method for estimating the effective baseline of the synthetic aperture radar system based on registration and curve fitting, provided by the embodiment of the invention, comprises the following steps:
and step 1, generating a baseline search set. Baseline corpus
Wherein,
，
，
，
indicating that the rounding operation is performed to the nearest integer.
And 2, coarse registration. Channel 1 is a reference channel and a baseline search set is utilized with channel 1 as a referenceThe values in (a) perform a coarse registration on channel 2, which may be described as:
wherein,representation utilizationTo pairThe output signal obtained by the coarse registration is carried out,。
and step 3, obtaining a correlation value. The correlation between the reference channel 1 and the coarsely registered channel 2 is characterized by a correlation. The expression for calculating the correlation is as follows:
wherein,is a constant, and:
and 4, fitting a curve. The obtained sample values about the correlation degree are used for carrying out six-order curve fitting according to the following formula, so that a six-order polynomial can be obtainedCoefficient of (2)The coefficient making a function of valueCan be used for measuring the correlation value in the sense of minimum mean square errorAnd (3) fitting:
，
and 5, estimating an effective baseline. Coefficient of utilizationCompletion of correlation functionEstimation of (2):
，
the effective baseline corresponding to the maximum correlation value is the effective baseline actually existing in the system:
the effects of the present invention can be further verified by the following experiments. The measured synthetic aperture radar data used in the experiment is from a certain airborne experiment. In order to detect the ground moving target, the antennas of the experimental system are arranged along the course direction. The radar parameters are as follows: the carrier frequency is 9 GHz, the pulse repetition frequency is 840 Hz, the Doppler bandwidth is 530 Hz, the Doppler center frequency is-90 Hz, the platform speed is 106 m/s, and the antenna sub-aperture interval is 0.4 m.
FIG. 2 is the results of curve fitting of the present invention. The star points in the graph are sample values of the correlation obtained after traversing the baseline search set in step three, and the black solid line is the result of curve fitting by using the sample values. The maximum value of the fitted correlation value curve corresponds to a baseline value of 0.1652 m. Correlation values obtained by coarse registration using the baseline values and the baseline values obtained using the EDB method and the CMB method are shown in table 1. It can be seen that the process of the invention performed better than the EDB process and the CMB process.
TABLE 1
Base line value (m) Correlation value
Nominal value (base line equivalent) 0.2000 0.9477
EDB process 0.1639 0.9681
CMB method 0.1645 0.9682
The method of the invention 0.1652 0.9682
FIG. 3 is a graph comparing the baseline estimation performance of the method of the present invention with the EDB method and the CMB method. The doppler center frequency values in this experiment were obtained by the classical Correlated Doppler Estimation (CDE) algorithm. However, the estimation accuracy of the current doppler center frequency estimation algorithm is about one percent of the pulse repetition frequency, so the true doppler center frequency of the experiment may exist in the range of [ -100 Hz, -80 Hz ]. As can be seen from the figure, the existing EDB method and CMB method both vary with the change of the estimated value of the doppler center frequency, and thus the robustness of both methods cannot be guaranteed. The method of the invention is irrelevant to the Doppler center frequency estimated value, and can obtain a steady baseline estimated value.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.

Claims (7)

1. The method for estimating the effective baseline of the synthetic aperture radar system based on registration and curve fitting is characterized by comprising the following steps:
step one, determining a baseline search set;
step two, carrying out coarse registration on the input multichannel synthetic aperture radar data;
step three, obtaining correlation values among channels after coarse registration;
step four, fitting a curve describing the relation between the correlation degree and a base line value by using the obtained sample points of the correlation degree value;
and step five, searching the maximum value of the curve obtained by fitting, wherein the base line value corresponding to the maximum value is the effective base line.
2. The method for effective baseline estimation of a synthetic aperture radar system based on registration and curve fitting of claim 1, wherein the initialization range of the baseline search set is ΩT＝[Bmin，Bmax]In which B ismin＝0.5Bequ，Bmax＝1.5Bequ，BequIs an equivalent baseline.
3. The method for registration and curve fitting based effective baseline estimation of a synthetic aperture radar system of claim 1, wherein the baseline search set is ΩS＝[B1，…，BN]Wherein B isi＝[round(Bmin·10x)+i-1]·10-x，i＝1，…，N，N＝round(Bmax·10x)-round(Bmin·10x) +1, round (·) denotes rounding to the nearest integer, where BminMinimum possible baseline value, BmaxMaximum possible baseline value, BiFor elements in the baseline search set, x is an integer.
4. The method for estimating an effective baseline of a synthetic aperture radar system based on registration and curve fitting according to claim 1, wherein the second step comprises:
step 2.1, transforming the input synthetic aperture radar data into a range-Doppler domain, Z1(tr，fa) And Z2(tr，fa) Respectively representing the range-Doppler-domain signals of the 1 st and 2 nd channels, wherein trRepresenting the distance dimension time, faIndicates the Doppler frequency, BeffDenotes the effective Baseline, vpRepresenting the flight speed of the synthetic aperture radar platform along the course;
step 2.2 based on channel 1Quasi, using the baseline search set omegasThe values in (a) perform a coarse registration on channel 2, which may be described as:
wherein,represents the utilization of BiTo Z2The output signal resulting from the coarse registration, i 1, …, N.
5. The method for estimating an effective baseline of a synthetic aperture radar system based on registration and curve fitting according to claim 1, wherein the expression of the correlation value between channels after coarse registration is as follows:
wherein K is a constant, and:
Z1(tr，fa) And Z2(tγ，fa) Respectively representing the range-Doppler-domain signals of the 1 st and 2 nd channels, wherein trRepresenting the distance dimension time, faIndicates the Doppler frequency,Represents the utilization of BiTo Z2The output signal resulting from the coarse registration, i 1, …, N.
6. Registration and curve fitting based synthetic aperture radar system validation according to claim 1The baseline estimation method, wherein said step four comprises: performing curve fitting by using the obtained correlation degree sample to obtain a function value f (B)i) Can fit the correlation value | sigma (B) in the sense of least mean square errori) L, the fitting function f (B)i) Expressed as:
wherein, a0，a1，…，a6As a fitting function f (B)i) Coefficient of (a), omegaSAs a baseline corpus, BiElements in the set are searched for a baseline.
7. The method for estimating an effective baseline of a synthetic aperture radar system based on registration and curve fitting according to claim 6, wherein the step five comprises:
step 5.1, utilizing the fitting function f (B) obtained in the step fouri) Coefficient a of0，a1，…，a6Construct a function of the correlation values with respect to the baseline value:
|ρ(B)|＝a0+a1B+a2B2+a3B3+a4B4+a5B5+a6B6，B∈ΩT
step 5.2, the baseline value corresponding to the maximum value of the correlation function | ρ (B) | is the effective baseline:
wherein omegaTIs the initialization scope of the baseline corpus.
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