CN108614249B - Phase error estimation method, device, compensation method and system - Google Patents

Phase error estimation method, device, compensation method and system Download PDF

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CN108614249B
CN108614249B CN201810327204.4A CN201810327204A CN108614249B CN 108614249 B CN108614249 B CN 108614249B CN 201810327204 A CN201810327204 A CN 201810327204A CN 108614249 B CN108614249 B CN 108614249B
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image
value
image sharpness
sharpness function
phase
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CN108614249A (en
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陈杰
邓嘉东
王凯
高贺利
曾虹程
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Beihang 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
    • 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
    • G01S7/40—Means for monitoring or calibrating
    • 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

Abstract

The present disclosure relates to a radar beaconA method, a device, a compensation method and a system for estimating multiband phase errors are disclosed, wherein the method comprises the following steps of 1: carrying out amplitude equalization on an image sharpness function of the image after the radar signal imaging; step 2: initializing an iteration flag i and compensating a phase value θi(ii) a And step 3: calculating a first image sharpness function value SiAnd the direction of iteration di(ii) a And 4, step 4: according to the direction of iteration diPerforming a line search by approximating a maximum of an image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1(ii) a And 5: when the second image sharpness function value Si+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase value theta is less than or equal to a preset threshold value, determining the current compensation phase value thetaiIf the phase error is found, otherwise, performing step 6; step 6: and (5) enabling i to be i +1, and returning to the step 3. The method can enable the estimation accuracy of radar observation to be higher, and can keep good performance no matter in a scene with a large number of strong points or a flat scene without strong point targets.

Description

Phase error estimation method, device, compensation method and system
Technical Field
The present disclosure relates to the field of signal processing technologies, and in particular, to a method, an apparatus, a compensation method, and a system for estimating a phase error.
Background
Synthetic Aperture Radar (SAR) is a high-resolution remote sensing Radar that can observe the earth. The satellite-borne SAR can overcome the influence of rain fog and dark night conditions to realize all-weather and all-weather earth observation, so the satellite-borne SAR has wide application prospect in the fields of agriculture, oceans, disaster monitoring, 3D mapping and the like. The resolution in observation is a key index of the space-borne SAR, the distance resolution is inversely proportional to the signal bandwidth, for example, to achieve the ground distance resolution better than 10cm, the signal bandwidth is to achieve the width of 2-3GHz, and this constitutes a great pressure for the hardware system. The multiband splicing technology provides a feasible solution for solving the problem of ultra-wideband signal transmission, and combines a plurality of signals with different carrier frequencies and non-overlapping bandwidths (or with a small overlapping range) into a large-bandwidth signal. However, while having multiple advantages, the multiband splicing technology has disadvantages, and a typical problem is that it is difficult to ensure the amplitude-phase consistency of each frequency band, and such inconsistency may cause a long smear phenomenon to occur in an image, and even may cause a false target, which greatly deteriorates SAR imaging quality, and affects SAR application performance.
In the prior art, an additional inner calibration loop is added in the system to extract amplitude and phase information of each frequency band, so that the amplitude and phase information can be used for compensation of observation results. However, this technique not only adds complexity to the system design, but also can only compensate a part of the amplitude-phase deviation, which cannot be compensated for the antenna.
To solve this problem, some algorithms begin to explore image-based post-processing methods, span intermediate processes, and directly estimate stitching errors with the goal of improving image focusing effect, where typical algorithms include two-step estimation methods and modified Phase Gradient auto-focusing (PGA) algorithms. At present, the two-step estimation method and the improved PGA both have some limitations, the former divides splicing errors into in-band errors and inter-band errors, and both are approximately represented by taylor expansion, however, the true phase errors are very complex, and the taylor expansion is difficult to accurately describe the true errors, so that the compensation precision is not high, and the effect is not obvious. The improved PGA algorithm has excellent effect in scenes with a large number of strong points, but has obvious performance reduction in flat areas and is not universally used in all scenes.
Disclosure of Invention
The method uniformly regards errors between frequency bands and in frequency bands as errors of each frequency point of a broadband spectrum, so that the complex phase errors can be accurately described, the estimation precision of radar observation is higher, good performance can be kept no matter in a scene with a large number of strong points or in a flat scene without strong point targets, and good scene adaptability is achieved.
In order to achieve the above object, the present disclosure provides a method for estimating a multiband phase error of a radar signal, the method including:
step 1: carrying out amplitude equalization on an image sharpness function of the image after the radar signal imaging;
step 2: initializing an iteration flag i and compensating a phase value θiWherein i is more than or equal to 0;
and step 3: calculating a first image sharpness function value SiAnd the direction of iteration di；
And 4, step 4: according to the direction of iteration diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1；
And 5: when said second image sharpness function value Si+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase value theta is less than or equal to a preset threshold value, determining the current compensation phase value thetaiIf the phase error is found, otherwise, performing step 6;
step 6: and (5) enabling i to be i +1, and returning to the step 3.
Optionally, the amplitude equalizing an image sharpness function of the radar signal-imaged image comprises:
amplitude equalizing the image sharpness function according to the following formula:
Figure BDA0001626967470000031
the method comprises the steps of obtaining an image sharpness function of an imaged image, obtaining M image orientation coordinates, obtaining M image orientation total sampling points, obtaining F (M, k) an image distance spectrum function, obtaining k frequency points, wherein k is 1,2 … N, and N is the image distance total sampling points.
Optionally, the image sharpness function is:
Figure BDA0001626967470000032
wherein S is an image sharpness function of the imaged image, m is an image azimuth coordinate, n is an image distance coordinate, f (m, n) is an imaged image function, | f (m, n) |2Is the pixel intensity in the image, M is the total sampling point number of the image orientation, N is the total sampling point number of the image distance, b is the image background average intensity, wherein,
Figure BDA0001626967470000033
optionally, the first image sharpness function value SiObtained by the following formula:
Si＝S(θi)，
wherein the function S (θ)i) The gradient expression for the compensation phase θ (k) at frequency point k is:
Figure BDA0001626967470000034
f (m, k) is an image distance spectrum function,
Figure BDA0001626967470000035
optionally, the iteration direction diObtained by the following formula:
di＝-Hi·gi，
wherein the content of the first and second substances,
Figure BDA0001626967470000036
Figure BDA0001626967470000041
optionally, said step of determining according to said iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1The method comprises the following steps:
obtaining a step length alpha satisfying the following two formulasi：
S(θi+αidi)≤S(θi)+0.1αigiTdi，
Figure BDA0001626967470000042
According to the step length alphaiCalculating the compensation phase value theta by the following formulaiAnd said second image sharpness function value Si+1：
θi+1＝θi+αidi，
Si+1＝S(θi+1)。
Alternatively, the variation is calculated by the following formula:
ε＝|Si+1-Si|/Si，
wherein ε represents the variation.
The present disclosure also provides an apparatus for estimating a multiband phase error of a radar signal, the apparatus comprising:
the equalization module is used for carrying out amplitude equalization on an image sharpness function of the image imaged by the radar signal;
an initialization module for initializing an iteration flag i and a compensation phase value thetaiWherein i is more than or equal to 0;
a calculation module for calculating a first image sharpness function value SiAnd the direction of iteration di；
A line search module for searching the line according to the iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1；
A compensation phase value determining module for determining a second image sharpness function value S when determining said second image sharpness function valuei+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase value theta is less than or equal to a preset threshold value, determining the current compensation phase value thetaiIs the calculated phase error;
a loop module for applying a second image sharpness function value S to the second imagei+1And said first image sharpness function value SiWhen the variation is larger than the preset threshold, let i be i +1, and let the calculation module recalculate the first image sharpness function value SiAnd the direction of iteration di。
The present disclosure also provides a method for compensating for a multiband phase error of a radar signal, the method including:
constructing a corresponding model between the original image function and the distance spectrum:
Figure BDA0001626967470000051
where f' (m, n) is the original image function,
Figure BDA0001626967470000052
the method comprises the following steps of (1) obtaining an error-free image distance spectrum function, wherein k is a frequency point, k is 1,2 … N, m is an image azimuth coordinate, N is an image distance coordinate, and N is the total number of image distance sampling points;
the method for estimating the multiband phase error of the radar signal obtains the phase error theta corresponding to each frequency point ki(k)；
Order to
Figure BDA0001626967470000053
The phase error theta is measuredi(k) And substituting the image into the corresponding model to obtain a compensated image.
The present disclosure also provides a system for compensating for a multiband phase error of a radar signal, the system comprising:
the corresponding model building module is used for building a corresponding model between the original image function and the distance spectrum:
Figure BDA0001626967470000054
where f' (m, n) is the original image function,
Figure BDA0001626967470000055
the method comprises the following steps of (1) obtaining an error-free image distance spectrum function, wherein k is a frequency point, k is 1,2 … N, m is an image azimuth coordinate, N is an image distance coordinate, and N is the total number of image distance sampling points;
the estimation device for the multiband phase error of the radar signal is used for acquiring the phase error theta corresponding to each frequency point ki(k)；
Compensation module, order
Figure BDA0001626967470000056
And the phase error theta obtained by the estimating means is usedi(k) And substituting the image into the corresponding model to obtain a compensated image.
By the technical scheme, the inter-frequency band errors and the in-frequency band errors are uniformly regarded as the frequency point errors of the broadband spectrum, and the errors are estimated, so that the complex phase errors can be accurately estimated, the estimation precision of radar observation is higher, good performance can be kept no matter in a scene with a large number of strong points or in a flat scene without strong point targets, and good scene adaptability is achieved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
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The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is a flow chart illustrating a method of estimating a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure.
Fig. 2 is a block diagram illustrating a schematic structure of an apparatus for estimating a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure.
Fig. 3 is a flow chart illustrating a method of compensating for a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure.
Fig. 4 is a block diagram illustrating a schematic structure of a system for compensating for multiband phase errors of radar signals according to an exemplary embodiment of the present disclosure.
Fig. 5 is a phase error curve estimated by a method for estimating a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure.
Fig. 6 is a graph illustrating image sharpness function changes during an iteration of a method for estimating multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure.
Fig. 7 is a diagram illustrating a method for compensating a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure, and evaluation results of an original method, a two-step estimation method, and an improved PGA algorithm.
Description of the reference numerals
10 equalization module 20 initialization module
30 calculation module 40 line search module
50-cycle module 60 compensated phase value determination module
100 estimation device 200 corresponds to a model building block
300 compensation module
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
The present disclosure provides a method for estimating a multiband phase error of a radar signal, as shown in fig. 1, the method includes steps 1 to 5.
In step 1, the image sharpness function of the radar signal imaged image is amplitude equalized. The amplitude equalization operation can be performed by an electronic device such as a computer, so as to make the imaging effect of the image better and optimize the imaged image.
In one possible embodiment, the amplitude equalizing an image sharpness function of the image after the radar signal is imaged includes:
amplitude equalizing the image sharpness function according to the following formula:
Figure BDA0001626967470000071
the method comprises the steps of obtaining an image sharpness function of an imaged image, obtaining M image orientation coordinates, obtaining M image orientation total sampling points, obtaining F (M, k) an image distance spectrum function, obtaining k frequency points, wherein k is 1,2 … N, and N is the image distance total sampling points. The above related parameters may be read from the received radar signal, or may be obtained from the imaged image data.
In one possible embodiment, the image sharpness function is:
Figure BDA0001626967470000072
wherein S is an image sharpness function of the imaged image, m is an image azimuth coordinate, n is an image distance coordinate, f (m, n) is an imaged image function, | f (m, n) |2Is the pixel intensity in the image, M is the total sampling point number of the image orientation, N is the total sampling point number of the image distance, b is the image background average intensity, wherein,
Figure BDA0001626967470000081
in one possible embodiment, the corresponding model between the original image function and the distance spectrum is:
Figure BDA0001626967470000082
where f' (m, n) is the original image function,
Figure BDA0001626967470000083
and k is a frequency point, k is 1,2 … N, m is an image orientation coordinate, N is an image distance coordinate, N is an image distance total sampling point number, and j represents an imaginary number.
It can be seen from the corresponding model that if the compensation phase is set to θ (k), then
Figure BDA0001626967470000087
Then, the multiband phase error compensation is completed, and the image sharpness function reaches the maximum value at this time, so the expression of the phase error can be expressed as:
Figure BDA0001626967470000084
wherein the content of the first and second substances,
Figure BDA0001626967470000085
the finally obtained phase error is k is a frequency point, k is 1,2 … N, that is, the finally obtained phase error
Figure BDA0001626967470000086
Is S (theta)k) And taking the value of theta corresponding to the maximum value.
In step 2, an iteration flag i and a compensation phase value θ are initializediWherein i is greater than or equal to 0. Wherein, initializing an iteration mark i and compensating a phase value thetaiFurther comprising: initializing matrix Hi。
In one possible embodiment, the initialization iteration flag i is equal to 0, and the compensation phase value θ is initialized0When it is 0, initialize matrix H0I, where I is an N-order identity matrix. Wherein, thetai＝(θi(1),θi(2),...,θi(N))TI.e. thetaiIs the transpose of the matrix formed by the phase error vectors of different distance grid points in each direction, and represents the graph at the ith iterationA phase error matrix of the image.
In step 3, a first image sharpness function value S is calculatediAnd the direction of iteration di。
In a possible embodiment, the first image sharpness function value SiObtained by the following formula:
Si＝S(θi)，
wherein the function S (θ)i) The gradient expression for the compensation phase θ (k) at frequency point k is:
Figure BDA0001626967470000091
im {. is an imaginary operator. The symbol x represents the conjugate operator, j represents the imaginary number, F (m, k) is the image distance spectrum function,
Figure BDA0001626967470000092
Figure BDA0001626967470000093
for fast fourier transform, b is the image background mean intensity,
Figure BDA0001626967470000094
f (m, n) is the image function after imaging, | f (m, n) | non-conducting phosphor2Is the intensity of a pixel in the image.
Pixel intensity | f (m, n) <nin image2The gradient expression for the compensation phase θ (k) at frequency point k is as follows:
Figure BDA0001626967470000095
function S (theta)i) The gradient expression for the compensated phase θ (k) at frequency point k is obtained by the conversion process shown below:
Figure BDA0001626967470000101
the image distance spectrum function F (m, k) may be obtained from the correlation parameters in the received radar information, or may be obtained from the correlation parameters in the imaged image data, and the function expression thereof is as follows:
Figure BDA0001626967470000102
wherein M is an image azimuth coordinate, N is an image distance coordinate, f (M, N) is an imaged image function, M is the total sampling point number of the image azimuth, N is the total sampling point number of the image distance, and j represents an imaginary number.
In a possible embodiment, the iteration direction diObtained by the following formula:
di＝-Hi·gi，
wherein the content of the first and second substances,
Figure BDA0001626967470000103
gia matrix representing the gradient of sharpness values of the image, when i > 0,
Figure BDA0001626967470000104
when i is 0, H0Obtained by an initialization operation in step 2, e.g. H0＝I。
In step 4, according to the iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1。
The line search may be a non-exact search, which may be, for example, a line search method based on strong wolfe criteria, or an exact search, which may be, for example, a dichotomy, etc.
In a possible embodiment, said iteration is according to said iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1The method comprises the following steps: method for acquiring compensation phase value theta by using line search method based on strong wolfe criterioni+1And the second diagramFunction value S of image sharpnessi+1The method comprises the following steps:
first, a step length α satisfying the following two formulas is obtainedi：
S(θi+αidi)≤S(θi)+0.1αigi Tdi，
Figure BDA0001626967470000111
Then, according to said step length αiCalculating the compensation phase value theta by the following formulai+1And said second image sharpness function value Si+1：
θi+1＝θi+αidi，
Si+1＝S(θi+1)。
Wherein, step size alpha is calculatediIn the two formulae of (a) and (b),
Figure BDA0001626967470000112
di＝-Hi·gi. Calculating to obtain the step length alpha meeting the conditioniThereafter, a new compensation phase value θ can be calculatedi+1So that a second image sharpness function value S can be calculatedi+1。
In step 5, when said second image sharpness function value Si+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase value theta is less than or equal to a preset threshold value, determining the current compensation phase value thetaiOtherwise, step 6 is performed. The preset threshold may be an error threshold read from a relevant parameter in the radar signal, or an error threshold adjusted or defined according to actual conditions.
In one possible embodiment, the variation is calculated by the following formula:
ε＝|Si+1-Si|/Si，
wherein ε represents the variation.
When the variation is smaller than the preset threshold, ending the iteration, finishing the estimation of the multiband phase error of the radar signal, and determining the current compensation phase value thetaiIs the phase error found. If not, go to step 6.
In step 6, let i equal i +1, return to step 3, and calculate a new first image sharpness function value S againiAnd the direction of iteration diAnd according to said iteration direction d in step 4iPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1Then said second image sharpness function value S is performed again in step 5i+1And said first image sharpness function value SiThereby iterating cyclically. Until finally finding the compensation phase value theta satisfying the conditioni。
For example, the iteration flag i is initialized to 0 in step 2, and the phase value θ is compensatediWhen 0, a first image sharpness function value S is calculated in step 30And an iteration direction d0Then in step 4 according to the iteration direction d0Performing a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θ1And a second image sharpness function value S1Finally, the variance | S is compared in step 51-S0|/S0And when the variation is less than or equal to the preset threshold, determining the compensation phase value theta0Otherwise, let i equal to i +1, i equal to 1, and then return to step 3 to recalculate the first image sharpness function value S1And an iteration direction d1And sequentially executing the following steps for iteration until the variable quantity meeting the condition is found, and determining the current compensation phase value thetaiIs the phase error found.
By the technical scheme, the inter-frequency band errors and the in-frequency band errors are uniformly regarded as the frequency point errors of the broadband spectrum, and the errors are estimated, so that the complex phase errors can be accurately estimated, the estimation precision of radar observation is higher, good performance can be kept no matter in a scene with a large number of strong points or in a flat scene without strong point targets, and good scene adaptability is achieved.
The present disclosure also provides an apparatus for estimating multiband phase error of a radar signal, as shown in fig. 2, the apparatus comprising:
the equalization module 10 is configured to perform amplitude equalization on an image sharpness function of the image after the radar signal imaging;
an initialization module 20 for initializing the iteration flag i and the compensation phase value θiWherein i is more than or equal to 0;
a calculation module 30 for calculating a first image sharpness function value SiAnd the direction of iteration di；
A line search module 40 for searching for a line according to the iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase value θi+1And a second image sharpness function value Si+1；
A compensation phase value determining module 50 for determining a second image sharpness function value S when determining said second image sharpness function value Si+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase value theta is less than or equal to a preset threshold value, determining the current compensation phase value thetaiIs the calculated phase error;
a loop module 60 for applying said second image sharpness function value Si+1And said first image sharpness function value SiIs greater than the preset threshold, let i be i +1, and let the calculation module 30 recalculate the first image sharpness function value SiAnd the direction of iteration di。
The present disclosure also provides a method for compensating for a multiband phase error of a radar signal, as shown in fig. 3, the method includes steps 301 to 303.
In step 301, a corresponding model between the original image function and the distance spectrum is constructed:
Figure BDA0001626967470000131
where f' (m, n) is the original image function,
Figure BDA0001626967470000132
the parameters are obtained by the relevant parameters in the received radar information or obtained from the relevant parameters in the imaged image data.
In step 302, according to the method for estimating the multiband phase error of the radar signal, a phase error θ corresponding to each frequency point k is obtainedi(k)。
In step 303, let
Figure BDA0001626967470000133
The phase error theta is measuredi(k) And substituting the image into the corresponding model to obtain a compensated image.
By the technical scheme, the inter-frequency-band and in-frequency-band errors can be uniformly regarded as the frequency point errors of the broadband spectrum, and the errors are estimated, so that the complex phase errors can be accurately estimated and compensated according to the phase errors, the estimation precision of radar observation is higher, good performance can be kept no matter in a scene with a large number of strong points or in a flat scene without strong point targets, and the method has good scene adaptability.
The present disclosure also provides a system for compensating for a multiband phase error of a radar signal, as shown in fig. 4, the system including:
a corresponding model construction module 200, configured to construct a corresponding model between the original image function and the distance spectrum:
Figure BDA0001626967470000141
where f' (m, n) is the original image function,
Figure BDA0001626967470000142
and k is a frequency point, k is 1,2 … N, m is an image orientation coordinate, N is an image distance coordinate, and N is the total number of image distance sampling points.
The estimation apparatus 100 for multiband phase error of radar signal is used to obtain the phase error θ corresponding to each frequency point ki(k)。
The compensation module 300, order
Figure BDA0001626967470000143
And the phase error theta obtained by the estimating means is usedi(k) And substituting the image into the corresponding model to obtain a compensated image.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the functional module, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
A set of experiments performed by a method for estimating a multiband phase error of a radar signal according to an exemplary embodiment of the present disclosure is given below to illustrate the present disclosure.
The data in the experiment adopts the Chinese central television station site of RADARSAT-2 imaging of the dual-band splicing technology as a data set. The television station in the original image and the round building beside the television station are not ideal in focusing effect, and the phenomena of high side lobe and long tail of the target are extremely obvious. Fig. 5 is a phase error curve estimated by the estimation method provided by the present disclosure, a significant constant phase error exists between two frequency bands, namely, subband 1 and subband 2, and it can be seen that the phase error of real data is very complex and is difficult to be described simply by taylor expansion. Fig. 6 is a graph of the change of the image sharpness function in the iterative process, from which it can be seen that the estimation method proposed by the present disclosure converges quickly, reaching the maximum value of the image sharpness after only 10 iterations.
A set of experiments performed by a method for compensating for multiband phase errors of a radar signal according to an exemplary embodiment of the present disclosure is given below to illustrate the present disclosure.
Fig. 7 shows airborne flight experimental data of the dual-band splicing system. A road is arranged above the imaged image, street lamps on two sides of the road form a plurality of strong scattering points, and a flat farmland area is arranged below the imaged image. In the experiment, a flat farmland area is selected as a data set to estimate a phase error, an upper strong point target is compensated according to the obtained phase error value, and the performance of each method is compared through point target index evaluation. The experimental results are shown in fig. 7, where line 1 is the original evaluation result, the side lobe is high, and even the main lobe is phagocytosed by the side lobe. The line 3 and the line 4 are respectively the evaluation results of the two-step estimation method and the improved PGA algorithm, the two methods cannot complete compensation well, and the strong point target side lobe is still asymmetric. The line 2 is an evaluation result of the compensation method provided by the disclosure, and the evaluation result shows that the compensation method provided by the disclosure has good processing effect, side lobes are symmetrical left and right, and the null between the main lobe and the first side lobe is clearly visible. Because the experimental data set is a flat farmland area and does not include a strong point target, the experiment can show that the compensation method provided by the disclosure is still effective in the flat area and has excellent scene adaptability. Finally, a plurality of index evaluation results (image entropy, image contrast, resolution, peak side lobe ratio, and integral side lobe ratio) are given in table 1 shown below, and it can be seen from the data in table 1 that the evaluation results obtained by the compensation method proposed according to the present disclosure are optimal in all indexes as compared with the original method and the two-step estimation method and the improved PGA algorithm.
TABLE 1
Figure BDA0001626967470000161
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, various possible combinations will not be separately described in this disclosure.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.

Claims (10)

1. A method for estimating a multiband phase error of a radar signal, the method comprising:
step 1: carrying out amplitude equalization on an image sharpness function of the image after the radar signal imaging;
step 2: initializing an iteration marker i and compensating a phase matrix thetaiWherein i is more than or equal to 0;
and step 3: calculating a first image sharpness function value SiAnd the direction of iteration di；
And 4, step 4: according to the direction of iteration diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase matrix θi+1And a second image sharpness function value Si+1；
And 5: when said second image sharpness function value Si+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase matrix theta is less than or equal to a preset threshold value, determining the current compensation phase matrix thetaiElement of (2)i(k) Obtaining a compensation phase value on a frequency point k obtained by the ith iteration, wherein k is a frequency point, k is 1,2 … N, and N is the total number of sampling points in the image distance direction, otherwise, performing step 6;
step 6: and (5) enabling i to be i +1, and returning to the step 3.
2. The method of claim 1, wherein amplitude equalizing an image sharpness function of the radar signal imaged image comprises:
amplitude equalizing the image sharpness function according to the following formula:
Figure FDA0002808729570000011
the method comprises the steps of obtaining an image sharpness function of an imaged image, obtaining M image orientation coordinates, obtaining M image orientation total sampling points, obtaining F (M, k) an image distance spectrum function, obtaining k frequency points, wherein k is 1,2 … N, and N is the image distance total sampling points.
3. The method of claim 1 or 2, wherein the image sharpness function is:
Figure FDA0002808729570000021
wherein S is an image sharpness function of the imaged image, m is an image azimuth coordinate, n is an image distance coordinate, f (m, n) is an imaged image function, | f (m, n) |2Is the pixel intensity in the image, M is the total sampling point number of the image orientation, N is the total sampling point number of the image distance, b is the image background average intensity, wherein,
Figure FDA0002808729570000022
4. the method of claim 3, wherein said first image sharpness function value SiObtained by the following formula:
Si＝S(θi)，
wherein the function S (θ)i) The gradient expression for the compensation phase θ (k) at frequency point k is:
Figure FDA0002808729570000023
f (m, k) is an image distance spectrum function,
Figure FDA0002808729570000024
wherein the content of the first and second substances,
Figure FDA0002808729570000025
is a range-wise fast fourier transform.
5. Method according to claim 4, characterized in that said iteration direction diObtained by the following formula:
di＝-Hi·gi，
wherein the content of the first and second substances,
Figure FDA0002808729570000026
gimatrix representing gradient of sharpness values of the image, thetai(k) The compensated phase value at frequency point k, obtained for the ith iteration, k is 1,2 … N,
when i is>At the time of 0, the number of the first,
Figure FDA0002808729570000027
when i is 0, H0＝I。
6. Method according to claim 5, characterized in that said method is based on said iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase matrix θi+1And a second image sharpness function value Si+1The method comprises the following steps:
obtaining a step length alpha satisfying the following two formulasi：
S(θi+αidi)≤S(θi)+0.1αigi Tdi，
Figure FDA0002808729570000031
According to the step length alphaiCalculating the compensated phase matrix theta by the following formulaiAnd said second image sharpness function value Si+1：
θi+1＝θi+αidi，
Si+1＝S(θi+1)。
7. The method of claim 1, wherein the variation is calculated by the following formula:
ε＝|Si+1-Si|/Si，
wherein ε represents the variation.
8. An apparatus for estimating a multiband phase error of a radar signal, the apparatus comprising:
the equalization module is used for carrying out amplitude equalization on an image sharpness function of the image imaged by the radar signal;
an initialization module for initializing an iteration flag i and a compensation phase matrix thetaiWherein i is more than or equal to 0;
a calculation module for calculating a first image sharpness function value SiAnd the direction of iteration di；
A line search module for searching the line according to the iteration direction diPerforming a line search by approximating a maximum of the image sharpness function to obtain a compensated phase matrix θi+1And a second image sharpness function value Si+1；
A compensation phase value determining module for determining a second image sharpness function value S when determining said second image sharpness function valuei+1And said first image sharpness function value SiWhen the variation amount of the current compensation phase matrix theta is less than or equal to a preset threshold value, determining the current compensation phase matrix thetaiElement of (2)i(k) For the ith iteration foundCompensating phase values at a frequency point k, wherein k is a frequency point, k is 1,2 … N, and N is the total number of sampling points in the image distance direction;
a loop module for applying a second image sharpness function value S to the second imagei+1And said first image sharpness function value SiWhen the variation is larger than the preset threshold, let i be i +1, and let the calculation module recalculate the first image sharpness function value SiAnd the direction of iteration di。
9. A method for compensating for multiband phase error of a radar signal, the method comprising:
constructing a corresponding model between the original image function and the distance spectrum:
Figure FDA0002808729570000041
where f' (m, n) is the original image function,
Figure FDA0002808729570000042
the method comprises the following steps of (1) obtaining an error-free image distance spectrum function, wherein k is a frequency point, k is 1,2 … N, m is an image azimuth coordinate, N is an image distance coordinate, and N is the total number of image distance sampling points;
the method for estimating multiband phase error of radar signal according to any one of claims 1 to 7, wherein the compensation phase value θ on the frequency point k obtained from the ith iteration is obtainedi(k)；
Order to
Figure FDA0002808729570000043
Obtaining a compensation phase value theta on a frequency point k through the ith iterationi(k) Is substituted into the corresponding model to obtain a compensated image, wherein,
Figure FDA0002808729570000044
is the phase error at frequency point k, and theta (k) is the compensated phase at frequency point kThe value is obtained.
10. A system for compensating for multiband phase error of a radar signal, the system comprising:
the corresponding model building module is used for building a corresponding model between the original image function and the distance spectrum:
Figure FDA0002808729570000045
where f' (m, n) is the original image function,
Figure FDA0002808729570000051
the method comprises the following steps of (1) obtaining an error-free image distance spectrum function, wherein k is a frequency point, k is 1,2 … N, m is an image azimuth coordinate, N is an image distance coordinate, and N is the total number of image distance sampling points;
estimation device for multiband phase error comprising a radar signal as claimed in claim 8, for obtaining a compensated phase value θ at a frequency point k obtained in an ith iterationi(k)；
Compensation module, order
Figure FDA0002808729570000052
And the compensation phase value theta on the frequency point k obtained by the ith iteration acquired by the estimation devicei(k) Is substituted into the corresponding model to obtain a compensated image, wherein,
Figure FDA0002808729570000053
is the phase error at frequency point k, and θ (k) is the compensated phase value at frequency point k.
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