CN106054186B - A kind of method for the type parameter for being used to estimate scattering center - Google Patents

A kind of method for the type parameter for being used to estimate scattering center Download PDF

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CN106054186B
CN106054186B CN201610344286.4A CN201610344286A CN106054186B CN 106054186 B CN106054186 B CN 106054186B CN 201610344286 A CN201610344286 A CN 201610344286A CN 106054186 B CN106054186 B CN 106054186B
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scattering center
frequency domain
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frequency
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CN106054186A (en
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邢笑宇
霍超颖
袁莉
任红梅
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Beijing Institute of Environmental Features
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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
    • G01S13/904—SAR modes
    • 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
    • G01S13/904—SAR modes
    • G01S13/9064—Inverse SAR [ISAR]

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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)
  • Ultra Sonic Daignosis Equipment (AREA)

Abstract

A kind of method for the type parameter for being used to estimate scattering center is disclosed, including：It is B by bandwidthzScatter echo data be divided into M frequency domain section, and to the data imaging of frequency domain section, to obtain M subgraph；Local peaking's point search is carried out to each subgraph, to obtain the information of the local peaking of subgraph point；Local peaking's point on M subgraph is contrasted, local peaking's point of same position will be occupied on M subgraph as scattering center；For each scattering center, using the natural logrithm of range coefficient modulus value of the scattering center on M subgraph as dependent variable, linear fit, and the estimate using the slope of matched curve as the type parameter of the scattering center are carried out by independent variable of the natural logrithm of the centre frequency of M subgraph.This method integrates several subgraphs and is scattered center type parameter Estimation, effectively eliminates the arbitrariness that SPLIT methods estimate type parameter, improves the estimated accuracy of scattering center type parameter.

Description

Method for estimating type parameters of scattering center
Technical Field
The invention relates to the field of target identification of ISAR (inverse synthetic aperture radar) images, in particular to a method for estimating type parameters of scattering centers.
Background
The type parameter a of the scattering center is an important criterion for distinguishing different scattering structures. In the prior art, the SPLIT (sub-band splicing) algorithm is usually used to estimate the type parameters of the scattering center. The SPLIT algorithm considers the amplitude coefficient modulus A and the center frequency f of the scattering center c Is proportional to the alpha power of (i.e.That is, the SPLIT algorithm considers ln (| A |) and ln (| f |) c |) in an exact linear relationship. Therefore, according to the SPLIT algorithm, only two-dimensional loop in broadband is neededArbitrarily intercepting two sections of frequency domain data with enough bandwidth from the wave data, and obtaining the amplitude coefficient modulus | A of a single scattering center corresponding to the two sections of frequency domain data 1 |、|A 2 And center frequency f corresponding to two sections of frequency domain data c1 、f c2 The scattering center type parameter can be estimated by formula 1.
However, in practical situations, since other adjacent scattering centers may affect the estimation of the type parameter of the scattering center to be measured, ln (| a |) and ln (| f |) c |) no longer present an accurate linear relationship. Therefore, the SPLIT algorithm is adopted to estimate that certain deviation exists in the type parameters of the scattering center.
In view of the shortcomings of the SPLIT algorithm, there is a need in the art for a method that can improve the accuracy of scattering center type parameter estimation.
Disclosure of Invention
The invention aims to provide a method for estimating type parameters of a scattering center, which is used for improving a SPLIT algorithm and improving the estimation precision of the type parameters of the scattering center.
The invention provides a method for estimating type parameters of a scattering center, which comprises the following steps:
s1, setting the bandwidth as B z The scattered echo data are divided into M frequency domain intervals, and the data of the frequency domain intervals are imaged to obtain M sub-images; wherein, the center frequency of the ith frequency domain interval is f i I =1,2,3 \ 8230M, M being an integer greater than 1;
s2, searching local peak points of each sub-image to obtain the position and amplitude coefficient module value information of the local peak points on the sub-image;
s3, comparing the local peak points on the M sub-images, and taking the local peak points occupying the same positions on the M sub-images as scattering centers of the target;
and S4, for each scattering center, performing linear fitting by taking the natural logarithm of the amplitude coefficient modulus of the scattering center on the M sub-images as a dependent variable and taking the natural logarithm of the central frequency of the M sub-images as an independent variable, and taking the slope of a fitting curve as an estimated value of the type parameter of the scattering center.
Preferably, the local peak point search specifically includes: comparing the pixel value of any pixel point on the subimage with the pixel values of 8 adjacent pixel points in the neighborhood of the pixel point, and if the pixel value of the pixel point is greater than the pixel value of the pixel point in the neighborhood, the pixel point is a local peak point.
Preferably, the center frequency f of the ith frequency domain interval i Satisfies the following conditions:
f i ＝f 1 +(i-1)*Δf；
in the formula (f) 1 Is the center frequency, f, of the first frequency domain interval i Is the center frequency of the ith frequency domain interval, and Δ f is the step value of the center frequency of the adjacent frequency domain interval.
Preferably, the sub-bandwidths of the M frequency-domain intervals are all B, and B < B z 。
Preferably, M satisfies:
preferably, B satisfies:
preferably, Δ f satisfies:
preferably, the imaging of the data of the frequency domain interval specifically includes: and imaging the data of the frequency domain interval through a filtering-inverse projection algorithm to obtain M sub-images.
According to the technical scheme, the scattering echo data are divided into M frequency domain intervals, and the data of the frequency domain intervals are imaged to obtain M sub-images; determining a scattering center of the target by searching local peak points of the M sub-images and comparing the local peak points on the M sub-images; then, for each scattering center, linear fitting is performed by taking the natural logarithm of the amplitude of the scattering center on the M sub-images as a dependent variable and taking the natural logarithm of the center frequency of the M sub-images as an independent variable, and the slope of a fitting curve is taken as an estimated value of the type parameter of the scattering center. The method integrates a plurality of sub-images and estimates the type parameters of the scattering center through linear fitting, thereby effectively improving the estimation precision of the type parameters of the scattering center.
Drawings
The features and advantages of the present invention will become more readily appreciated from the detailed description section provided below with reference to the accompanying drawings, in which:
fig. 1 (a) shows ln (| a |) and ln (| f |) corresponding to a scattering center of α = -0.5 when scattering center interference exists at Δ r = δ r c |) a relationship curve between;
fig. 1 (b) shows ln (| a |) and ln (| f |) corresponding to a scattering center of α = -0.5 when scattering center interference exists at Δ r =2 δ r c |) a relationship curve between;
fig. 1 (c) shows ln (| a |) and ln (| f |) corresponding to a scattering center of α = -0.5 when scattering center interference exists at Δ r =5 δ r c |) a relationship curve between;
fig. 2 is a flow chart of a method for estimating a type parameter of a scattering center according to an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The description of the exemplary embodiments is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Since the SPLIT method considers ln (| A |) and ln (| f |) c |)), the dependency relationship between the sub-bands is completely linear, so the method has an arbitrary property when selecting the sub-bands, i.e. two sub-bands with unequal center frequencies can be selected arbitrarily. However, in practical situations, since other adjacent scattering centers may interfere with the estimation of the type parameter of the scattering center to be measured, ln (| a |) and ln (| f |) are caused c |) no longer exhibit a completely linear relationship.
FIG. 1 shows ln (| A |) and ln (| f |) corresponding to a scattering center with a type parameter of-0.5 in the presence of other scattering center interference at different distances Δ r c | in the same direction). Wherein, Δ r is the distance between the adjacent interference scattering center and the scattering center to be estimated, and δ r is a distance resolution unit. The solid lines in FIG. 1 are ln (| A |) and ln (| f |) c |)), the broken line in fig. 1 is a straight line passing through both end points of the solid line. As can be seen from fig. 1 (a), 1 (b), and 1 (c), ln (| a |) and ln (| f) c |) are not completely linear, but show a proportional relationship of fluctuation. Moreover, the fluctuation increases as the distance between adjacent scattering centers decreases. At this time, if the SPLIT method is adopted, that is, data of two sub-bands are arbitrarily selected to perform scattering center type parameter estimation, the estimation of the type parameter α is also arbitrary. For example, in FIG. 1 (a), the slope of the straight line passing through the two end points of the solid line is-0.66; in FIG. 1 (b), the slope of the line passing through the ends of the solid line is-0.69; in FIG. 1 (c), the slope of the straight line passing through the both ends of the solid line is-0.67. If we select another two points on the solid line on fig. 1 (a), 1 (b) and 1 (c), the slope of the straight line determined by the two points changes again. That is, the result of estimating the type parameter α by the SPLIT method has an arbitrary property. In addition, the SPLIT method only selects data of two sub-bands for parameter estimation, and if the amplitude error of the scattering center corresponding to one sub-band is large, adverse effects are brought to the estimation of the scattering center type parameters.
Aiming at the defects of the SPLIT method, the inventor of the present application thinks that the broadband echo data can be divided into a plurality of frequency domain sections, and then the data of the plurality of frequency domain sections are integrated to perform the type parameter estimation of the scattering center, so as to eliminate the randomness of the type parameter estimation in the SPLIT method. Further, the inventors of the present application have found that although interference of adjacent scattering centers may cause ln (| a |) to be interfered with ln (| f) c |) exhibit non-linear changes, but the general trend of the changes still roughly conforms toThe change rule of (2). Therefore, the inventors of the present application have conceived that ln (| a |) and ln (| f) can be paired according to data of a multi-frequency domain section c |) and taking the slope of a fitting curve as an estimated value of the type parameter of the scattering center to further improve the accuracy of the estimation of the type parameter.
The technical solution in the embodiment of the present invention is described in detail below with reference to fig. 2. Fig. 2 is a flowchart of a method for estimating a type parameter of a scattering center in an embodiment of the present invention. As can be seen from fig. 2, the method starts in step S1.
Step S1, setting the bandwidth as B z The scattered echo data are divided into M frequency domain intervals, and the data of the frequency domain intervals are imaged to obtain M sub-images; wherein, the center frequency of the ith frequency domain interval is f i And i =1,2,3 \8230Mis an integer more than 1.
Specifically, in step S1, the acquired scattered echo data may be divided into M frequency domain intervals with the same sub-bandwidth. Wherein, the sub-bandwidth of each frequency domain interval is B. And, the center frequencies of the M frequency domain intervals satisfy:
f i ＝f 1 + (i-1) ×. Δ f equation 2
In the formula 2, f 1 Is the center frequency, f, of the first frequency domain interval i Is the center frequency of the ith frequency domain interval, and Δ f is the step value of the center frequency of the adjacent frequency domain interval.
And, the number M of frequency domain intervals satisfies:
in specific implementation, the values of Δ f and B can be determined according to actual needs. For example, Δ f may be 0.1B, B may be 0.1B z . By adopting the division mode, the scattered echo data can be divided into a plurality of frequency domain intervals with the same sub-bandwidth, and the values of the central frequencies corresponding to the frequency domain intervals are uniform. Therefore, limited scattering echo data can be fully utilized, the sample size of the sub-images is increased, and the estimation accuracy of the scattering center type parameters is indirectly improved through uniform division of the data.
After the M frequency domain intervals are obtained through the above division method, data of the M frequency domain intervals can be imaged according to a certain imaging algorithm, so as to obtain M sub-images. For example, we can image by a filter-backprojection algorithm.
It should be noted that the above division of the scattered echo data is only a preferred embodiment, and not the only embodiment of the present invention. In particular, the scatter echo data can be divided in various ways. For example, the scattering echo data may be divided into M frequency domain intervals with the same sub-bandwidth, or the scattering echo data may be divided into M frequency domain intervals with different sub-bandwidths. For another example, when the scattered echo data is divided into M frequency domain bins, two or more adjacent frequency domain bins may have a portion overlapping each other, or any two frequency domain bins may not have a portion overlapping each other. The division of the frequency domain interval in any way is within the scope of the present invention as long as the implementation of the present invention is not affected.
S2, searching local peak points of each sub-image to obtain the position and amplitude coefficient module value information of the local peak points on the sub-image.
In step S2, the local peak point search is specifically performed by: and comparing the pixel value of any pixel point on the sub-image with the pixel values of 8 adjacent pixel points in the neighborhood of the pixel value. Wherein the pixel points and 8 adjacent pixel points form a nine-square grid structure. And if the pixel value of the pixel point is larger than that of the adjacent pixel point, the pixel point is a local peak point. Otherwise, the pixel point is not a local peak point. And after searching the local peak point of each sub-image, acquiring the local peak point information on the sub-image. E.g. with a centre frequency f 1 Has L on the first sub-picture 1 Local peak points, and the position of each peak point is recorded as r1j, and the amplitude coefficient modulus of each peak point is | A 1j L, wherein j =1,2,3 \ 8230l 1 . Center frequency of f 2 Is present on the second sub-picture of 2 Each local peak point, and the position of each peak point is recorded as r2k, and the amplitude coefficient modulus of each peak point isWherein k =1,2,3 \ 8230l 2 . Center frequency of f M Has L on the Mth sub-image M Local peak points, and the position of each peak point is recorded as rMq, and the amplitude coefficient modulus of each peak point is | A Mq L, wherein q =1,2,3 \ 8230l M . It should be noted that the number of local peak points in each sub-image is determined according to the actual local peak point search result, and the number of local peak points in different sub-images may be equal or different.
And S3, comparing the local peak points on the M sub-images, and taking the local peak points occupying the same position on the M sub-images as the scattering center of the target.
Specifically, in step S3, the positions of the local peak points on the M acquired sub-images are compared, and the local peak points occupying the same position on the M sub-images are used as the scattering centers of the target. Wherein the number of scattering centers of the target is L, and the position of each scattering center is recorded as R p And, the position is R p Amplitude coefficient modulus of scattering center on ith sub-imageIs recorded as | A' pi L. the method is used for the preparation of the medicament. Wherein, p =1,2,3 \8230L, i =1,2,3 \8230M. By comparing the positions of the local peak points on the plurality of sub-images and determining the scattering center by the target, the situation that background interference is mistaken for the scattering center is effectively avoided, and the estimation accuracy of the scattering center type parameters is indirectly improved.
And S4, for each scattering center, performing linear fitting by taking the natural logarithm of the amplitude coefficient modulus of the scattering center on the M sub-images as a dependent variable and taking the natural logarithm of the central frequency of the M sub-images as an independent variable, and taking the slope of a fitting curve as an estimated value of the type parameter of the scattering center.
Specifically, in step S4, for L scattering centers, a linear fitting is performed, respectively, to determine an estimated value of the type parameter of each scattering center. For example, for a position R 1 The first scattering center of (1), we model the magnitude coefficient of the scattering center over M sub-images | A' 11 |、|A′ 12 |、|A′ 13 |、…|A′ 1M Taking absolute logarithm respectively to obtain ln (| A' 11 |)、ln(|A′ 12 |)、ln(|A′ 13 |)、…、ln(|A′ 1M |). Next, we take ln (| A' 11 |)、ln(|A′ 12 |)、ln(|A′ 13 |)、…、ln(|A′ 1M | is a dependent variable, and the natural logarithm ln (f) of the center frequency of the M sub-images 1 )、ln(f 2 )、ln(f 3 )、…、ln(f M ) As independent variables, linear fitting was performed to obtain a first fitted curve. Finally, the slope k of the fitted curve is determined 1 As an estimate of the type parameter of the first scattering center 1 I.e. alpha 1 ＝k 1 . Similarly, for the position R 2 At a second scattering center, we fit to obtain the slope k of a second fitted curve 2 And the slope k of the fitted curve is determined 2 As an estimate of the type parameter of the second scattering center 2 I.e. alpha 2 ＝k 2 . . For position R L At the Lth scattering center, we can fit to get the slope k of the Lth fitting curve L And the slope k of the fitted curve is determined L As an estimate a of the type parameter of the lth scattering center L I.e. alpha L ＝k L 。。
In the embodiment of the invention, the random type parameter estimation in the SPLIT algorithm is effectively eliminated by selecting multiple sections of frequency domain data in the whole scattering echo data to jointly estimate the type parameter of the scattering center. Furthermore, linear fitting is carried out based on the amplitude coefficient module value of each scattering center on a plurality of sub-images and the center frequency corresponding to the sub-images, and the inclination of a fitting curve is used as the type parameter estimation value of the scattering center, so that the estimation precision of the type parameters of the scattering center is effectively improved.
While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the specific embodiments described and illustrated in detail herein, and that various changes may be made therein by those skilled in the art without departing from the scope of the invention as defined by the appended claims.

Claims (8)

1. A method for estimating a type parameter of a scattering center, the method comprising:
s1, setting the bandwidth as B z The scattered echo data are divided into M frequency domain intervals, and the data of the frequency domain intervals are imaged to obtain M sub-images; wherein, the center frequency of the ith frequency domain interval is f i I =1,2,3 \ 8230M, M being an integer greater than 1;
s2, searching local peak points of each sub-image to obtain the position and amplitude coefficient module value information of the local peak points on the sub-image;
s3, comparing the local peak points on the M sub-images, and taking the local peak points occupying the same position on the M sub-images as a scattering center of the target;
and S4, for each scattering center, performing linear fitting by taking the natural logarithm of the amplitude coefficient module value of the scattering center on the M sub-images as a dependent variable and the natural logarithm of the central frequency of the M sub-images as an independent variable, and taking the slope of a fitting curve as an estimated value of the type parameter of the scattering center.
2. The method according to claim 1, wherein the local peak point search is specifically:
comparing the pixel value of any pixel point on the subimage with the pixel values of 8 adjacent pixel points in the neighborhood of the pixel point, and if the pixel value of the pixel point is greater than the pixel value of the pixel point in the neighborhood, the pixel point is a local peak point.
3. The method of claim 2, wherein the center frequency f of the ith frequency domain interval i Satisfies the following conditions:
f i ＝f 1 +(i-1)*Δf；
in the formula, f 1 Is the center frequency, f, of the first frequency domain interval i Is the center frequency of the ith frequency domain interval, and Δ f is the step value of the center frequency of the adjacent frequency domain interval.
4. The method of claim 3, wherein the M frequency-domain bins have sub-bandwidths that are each B, and B is<B z 。
5. The method of claim 4, wherein M satisfies:
6. the method of claim 5, wherein B satisfies:
7. the method of claim 6, wherein Δ f satisfies:
8. the method according to any of claims 1-7, wherein imaging the data of the frequency domain intervals is in particular:
and imaging the data of the frequency domain interval by a filtering-inverse projection algorithm to obtain M sub-images.
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