CN110308450B - Two-dimensional ISAR imaging method and system based on linear prediction - Google Patents
Two-dimensional ISAR imaging method and system based on linear prediction Download PDFInfo
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- 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
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- 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
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Abstract
The invention discloses a two-dimensional ISAR imaging method and system based on linear prediction, relates to the technical field of space target bistatic inverse synthetic aperture radar imaging, and mainly solves the problem of low two-dimensional image focusing degree under the condition of incomplete echo data. Firstly, processing acquired space target echo data by using a pulse compression mode to obtain a one-dimensional distance image; then processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model obtained by calculation to obtain missing data, and supplementing the one-dimensional distance image by utilizing the missing data to obtain a one-dimensional complete distance image; and finally, performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target. By utilizing the method or the system provided by the invention, the focusing degree of the two-dimensional image can be obviously improved, and the calculation amount is reduced.
Description
Technical Field
The invention relates to the technical field of space target bistatic Inverse Synthetic Aperture Radar (ISAR) imaging, in particular to a two-dimensional ISAR imaging method and system based on linear prediction.
Background
The problem of image data deletion of the inverse synthetic aperture radar is easily caused by echo data deletion, under the condition, azimuth compression is generally completed by adopting a non-uniform Fourier transform algorithm, and then a two-dimensional ISAR image is obtained, but in the process of performing non-uniform Fourier transform, time intervals among the deleted data need to be estimated firstly, and since the estimation values of the time intervals are influenced by the signal-to-noise ratio of echoes, the estimation error is large, the focusing degree of the two-dimensional ISAR image is finally deteriorated, and the estimation algorithm has large calculation amount and is not easy to realize in engineering.
Disclosure of Invention
The invention aims to provide a two-dimensional ISAR imaging method and a two-dimensional ISAR imaging system based on linear prediction, which can obviously improve the focusing degree of a two-dimensional image and reduce the calculation amount.
In order to achieve the purpose, the invention provides the following scheme:
a two-dimensional ISAR imaging method based on linear prediction comprises the following steps:
acquiring echo data of a space target;
calculating a low-order model parameter and a high-order model parameter of the linear prediction model;
processing the echo data by using a pulse compression mode to obtain a one-dimensional distance image of the space target;
processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data;
supplementing the one-dimensional distance image by using the missing data to obtain a one-dimensional complete distance image;
and performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target.
Optionally, the two-dimensional ISAR imaging method further includes:
combing prior information of a space target; the prior information comprises track information of the space target and size information of the space target; the orbit information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point.
Optionally, the calculating the low-order model parameter and the high-order model parameter of the linear prediction model specifically includes:
calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance.
Optionally, the processing the echo data in a pulse compression manner to obtain a one-dimensional range image of the spatial target specifically includes:
performing a Fourier transform on the echo data;
multiplying the transformed data by the conjugate spectrum of the reference signal;
and performing Fourier inverse transformation on the multiplied data to obtain a one-dimensional distance image of the space target.
Optionally, the processing the one-dimensional distance image by using a linear prediction extrapolation method according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data specifically includes:
calculating missing data according to the following formula;
the formula is z ═ ax + by)/(a2+b2) (ii) a Where z represents missing data, a represents low-order model parameters, b represents high-order model parameters, x represents echo data at the first two time instants adjacent to the missing data, and y represents echo data at the previous time instant adjacent to the missing data.
Optionally, the performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the spatial target specifically includes:
carrying out envelope alignment processing on the one-dimensional complete distance image;
carrying out initial phase correction processing on the images after envelope alignment;
and processing the corrected image by adopting Fourier transform to obtain a two-dimensional ISAR image of the space target.
A linear prediction based two-dimensional ISAR imaging system comprising:
the echo data acquisition module is used for acquiring echo data of the space target;
the model parameter calculation module is used for calculating low-order model parameters and high-order model parameters of the linear prediction model;
the one-dimensional distance image obtaining module is used for processing the echo data by using a pulse compression mode to obtain a one-dimensional distance image of the space target;
the missing data calculation module is used for processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data;
a one-dimensional complete distance image obtaining module, configured to supplement the one-dimensional distance image with the missing data to obtain a one-dimensional complete distance image;
and the two-dimensional ISAR image obtaining module is used for carrying out azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target.
Optionally, the two-dimensional ISAR imaging system further includes:
the prior information combing module is used for combing the prior information of the space target; the prior information comprises track information of the space target and size information of the space target; the orbit information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point.
Optionally, the model parameter calculation module specifically includes:
the model parameter calculation unit is used for calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance.
Optionally, the one-dimensional distance image obtaining module specifically includes:
a Fourier transform unit for performing Fourier transform on the echo data;
a multiplying unit for multiplying the transformed data by the conjugate spectrum of the reference signal;
and the inverse Fourier transform unit is used for performing inverse Fourier transform on the multiplied data to obtain a one-dimensional distance image of the space target.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a method and a system for performing two-dimensional imaging after estimating missing data based on linear prediction, which are used for performing analog analysis on the missing imaging data caused by the missing echo data and the missing frequency spectrum estimation in power spectrum calculation. The parameters of the linear prediction model can be obtained through the prior orbit information, the target size information and the like of the echo data, and are less influenced by the signal-to-noise ratio of the echo, so that the prediction precision is higher, the one-dimensional range profile data after pulse compression can be recovered with high precision, and the focusing degree of a two-dimensional image is obviously improved.
In addition, the invention only needs to predict the data after pulse compression, thereby avoiding the problem of operation amount caused by predicting the original data. The invention makes full use of the prior information of space target imaging, is insensitive to the signal-to-noise ratio of the echo and is suitable for a target two-dimensional ISAR imaging environment under multiple environments.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a two-dimensional ISAR imaging method based on linear prediction according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a two-dimensional ISAR imaging system based on linear prediction according to an embodiment of the present invention;
fig. 3 is a simple flow chart of a two-dimensional ISAR imaging method based on linear prediction according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a two-dimensional ISAR imaging method and a two-dimensional ISAR imaging system based on linear prediction, which can obviously improve the focusing degree of a two-dimensional image and reduce the calculation amount.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example 1
As shown in fig. 1, the two-dimensional ISAR imaging method based on linear prediction provided in this embodiment includes the following steps:
step 101: echo data of a spatial target is acquired.
Step 102: and calculating the low-order model parameters and the high-order model parameters of the linear prediction model.
Step 103: and processing the echo data by using a pulse compression mode to obtain a one-dimensional distance image of the space target.
Step 104: and processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data.
Step 105: and supplementing the one-dimensional distance image by using the missing data to obtain a one-dimensional complete distance image.
Step 106: and performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target.
Before performing step 102, the two-dimensional ISAR imaging method further includes: combing prior information of a space target; the prior information comprises track information of the space target and size information of the space target; the orbit information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point.
Step 102 specifically includes:
calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance.
Step 103 specifically comprises:
fourier transform is performed on the echo data.
The transformed data is multiplied by the conjugate spectrum of the reference signal.
And performing Fourier inverse transformation on the multiplied data to obtain a one-dimensional distance image of the space target.
Step 104 specifically includes:
according to the formula z ═ ax + by)/(a2+b2) Calculating missing data; where z represents missing data, a represents low-order model parameters, b represents high-order model parameters, x represents echo data at the first two time instants adjacent to the missing data, and y represents echo data at the previous time instant adjacent to the missing data.
Step 106 specifically includes:
and carrying out envelope alignment processing on the one-dimensional complete distance image.
And carrying out initial phase correction processing on the image after the envelope alignment.
And processing the corrected image by adopting Fourier transform to obtain a two-dimensional ISAR image of the space target.
Example 2
As shown in fig. 2, the two-dimensional ISAR imaging system based on linear prediction provided by this embodiment includes:
an echo data acquiring module 201, configured to acquire echo data of a space target;
the model parameter calculation module 202 is configured to calculate a low-order model parameter and a high-order model parameter of the linear prediction model;
a one-dimensional range image obtaining module 203, configured to process the echo data in a pulse compression manner to obtain a one-dimensional range image of the spatial target;
a missing data calculation module 204, configured to process the one-dimensional distance image in a linear prediction extrapolation manner according to the low-order model parameter and the high-order model parameter of the linear prediction model, so as to obtain missing data;
a one-dimensional complete distance image obtaining module 205, configured to utilize the missing data to supplement the one-dimensional distance image to obtain a one-dimensional complete distance image;
a two-dimensional ISAR image obtaining module 206, configured to perform azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the spatial target.
The two-dimensional ISAR imaging system further comprises:
the prior information combing module is used for combing the prior information of the space target; the prior information comprises track information of the space target and size information of the space target; the orbit information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point.
The model parameter calculation module 202 specifically includes:
the model parameter calculation unit is used for calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance.
The one-dimensional distance image obtaining module 203 specifically includes:
a Fourier transform unit for performing Fourier transform on the echo data;
a multiplying unit for multiplying the transformed data by the conjugate spectrum of the reference signal;
and the inverse Fourier transform unit is used for performing inverse Fourier transform on the multiplied data to obtain a one-dimensional distance image of the space target.
Example 3
The two-dimensional ISAR imaging method based on linear prediction provided by the embodiment specifically comprises the following steps:
first, echo data is collected.
Secondly, combing prior information; the prior information comprises target track information and target size information. Wherein the target is a spatial target; the target orbit information is the distance information between the target centroid and the transmitting station and between the target centroid and the receiving station at each time point.
Thirdly, after echo data are collected, calculating a low-order model parameter and a high-order model parameter of the linear prediction model through prior information; wherein, the low-order model parameter, i.e. the first-order parameter, is a ratio of the first distance and the third distance at a certain moment; the high-order model parameter, namely the second-order parameter, is the ratio of the second distance to the third distance at a certain moment; the first distance is the distance between the target centroid and the transmitting station, and the second distance is the distance between the target centroid and the receiving station; the third distance is the sum of the first distance and the second distance.
Fourthly, completing one-dimensional range imaging by utilizing a pulse compression mode according to the echo data to obtain a one-dimensional range image of the target; the method specifically comprises the following steps: the echo data is subjected to Fourier transform, then the conjugate frequency spectrum of the reference signal is multiplied by the transformed data, and finally inverse Fourier transform is carried out to obtain a one-dimensional range profile of the target.
Fifthly, based on the low-order model parameters and the high-order model parameters of the linear prediction model, performing prediction extrapolation on the missing one-dimensional range profile by using a linear prediction extrapolation mode, and supplementing missing one-dimensional range profile data to obtain a complete one-dimensional range profile; the data extrapolation calculation process is as follows: assuming that the low-order model parameter is a, the high-order model parameter is b, and the echo data at the first two times adjacent to the missing data are x and y, respectively, the linear prediction extrapolated data z is (ax + by)/(a) at this time2+b2). The extrapolated data length is typically chosen to be 1/3 of the known data length.
And sixthly, aligning envelopes. The embodiment is completed by a method of a maximum feature point, which specifically includes: and after a one-dimensional range profile of the target is obtained, a range unit with the maximum signal-to-noise ratio is searched in each echo, and then the maximum feature points are aligned by a cyclic shift method to complete envelope alignment.
And seventhly, correcting the initial phase. The initial phase correction is implemented by constructing a translation phase compensation term through the prior orbit information of the target and then multiplying the compensation term by the echo phase.
And eighthly, utilizing Fourier transform to complete azimuth compression to obtain a two-dimensional ISAR image of the target. The method specifically comprises the following steps: and performing Fourier transform on the echo of each distance unit, starting from the first distance unit, performing Fourier transform on all the distance units in sequence to complete azimuth compression, and further obtaining a two-dimensional ISAR image of the target.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (5)
1. A two-dimensional ISAR imaging method based on linear prediction is characterized in that the two-dimensional ISAR imaging method comprises the following steps:
acquiring echo data of a space target;
combing prior information of a space target; the prior information comprises track information of the space target and size information of the space target; the track information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point;
calculating a low-order model parameter and a high-order model parameter of the linear prediction model;
processing the echo data by using a pulse compression mode to obtain a one-dimensional distance image of the space target;
processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data;
supplementing the one-dimensional distance image by using the missing data to obtain a one-dimensional complete distance image;
performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target;
the calculating of the low-order model parameters and the high-order model parameters of the linear prediction model specifically includes: calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance;
the processing the one-dimensional distance image by using a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data specifically comprises the following steps: calculating missing data according to the following formula; the formula is z ═ ax + by)/(a2+b2) (ii) a Where z represents missing data, a represents low-order model parameters, b represents high-order model parameters, x represents echo data at the first two time instants adjacent to the missing data, and y represents echo data at the previous time instant adjacent to the missing data.
2. The two-dimensional ISAR imaging method based on linear prediction according to claim 1, wherein the processing the echo data by using a pulse compression method to obtain a one-dimensional range image of a spatial target specifically comprises:
performing a Fourier transform on the echo data;
multiplying the transformed data by the conjugate spectrum of the reference signal;
and performing Fourier inverse transformation on the multiplied data to obtain a one-dimensional distance image of the space target.
3. The two-dimensional ISAR imaging method based on linear prediction according to claim 1, wherein the performing azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of a spatial target specifically comprises:
carrying out envelope alignment processing on the one-dimensional complete distance image;
carrying out initial phase correction processing on the images after envelope alignment;
and processing the corrected image by adopting Fourier transform to obtain a two-dimensional ISAR image of the space target.
4. A two-dimensional ISAR imaging system based on linear prediction, the two-dimensional ISAR imaging system comprising:
the echo data acquisition module is used for acquiring echo data of the space target;
the prior information combing module is used for combing the prior information of the space target; the prior information comprises track information of the space target and size information of the space target; the track information of the space target is the distance information between the mass center of the space target and the transmitting station and between the mass center of the space target and the receiving station at each time point;
the model parameter calculation module is used for calculating low-order model parameters and high-order model parameters of the linear prediction model;
the one-dimensional distance image obtaining module is used for processing the echo data by using a pulse compression mode to obtain a one-dimensional distance image of the space target;
the missing data calculation module is used for processing the one-dimensional distance image by utilizing a linear prediction extrapolation mode according to the low-order model parameter and the high-order model parameter of the linear prediction model to obtain missing data;
a one-dimensional complete distance image obtaining module, configured to supplement the one-dimensional distance image with the missing data to obtain a one-dimensional complete distance image;
the two-dimensional ISAR image obtaining module is used for carrying out azimuth compression on the one-dimensional complete distance image to obtain a two-dimensional ISAR image of the space target;
the model parameter calculation module specifically includes: the model parameter calculation unit is used for calculating a low-order model parameter and a high-order model parameter of the linear prediction model according to the prior information of the space target; the low-order model parameter is the ratio of the first distance to the third distance at a specific time point; the high-order model parameter is the ratio of the second distance to the third distance at a specific time point; the first distance is the distance between the centroid of the space target and the transmitting station, and the second distance is the distance between the centroid of the space target and the receiving station; the third distance is the sum of the first distance and the second distance;
the missing data calculation module specifically includes: calculating missing data according to the following formula; the formula is z ═ ax + by)/(a2+b2) (ii) a Where z represents missing data, a represents low-order model parameters, b represents high-order model parameters, x represents echo data at the first two time instants adjacent to the missing data, and y represents echo data at the previous time instant adjacent to the missing data.
5. The linear prediction based two-dimensional ISAR imaging system of claim 4, wherein the one-dimensional distance image obtaining module specifically comprises:
a Fourier transform unit for performing Fourier transform on the echo data;
a multiplying unit for multiplying the transformed data by the conjugate spectrum of the reference signal;
and the inverse Fourier transform unit is used for performing inverse Fourier transform on the multiplied data to obtain a one-dimensional distance image of the space target.
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| WO2014149095A2 (en) * | 2013-03-20 | 2014-09-25 | Raytheon Company | Bistatic inverse synthetic aperture radar imaging |
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