CN114488145A

CN114488145A - Image domain DPCA false alarm suppression method based on polarization classification

Info

Publication number: CN114488145A
Application number: CN202111613961.6A
Authority: CN
Inventors: 刘爱芳; 宋立文; 黄祖镇; 林幼权
Original assignee: CETC 14 Research Institute
Current assignee: CETC 14 Research Institute
Priority date: 2021-12-27
Filing date: 2021-12-27
Publication date: 2022-05-13

Abstract

The multi-channel SAR-GMTI method mainly includes Along-Track interference (ATI), Phase-Center offset Antenna (DPCA), Space-time Adaptive Processing (STAP), and the like. The DPCA technology carries out clutter suppression through complex data subtraction operation, further detects a moving target, and is widely applied to an actual system due to the fact that the DPCA technology is simple in structure and easy to achieve in engineering. However, because objective adverse factors such as noise inevitably exist in an actual system, a static target sometimes has a small interference phase, and after subtraction, the static clutter still has partial energy residue. For stationary targets with strong scattering on roads and bridges, even if signals of two channels have only small amplitude-phase difference, clutter amplitude remained after DPCA processing is still strong, so that a large amount of false alarms are caused, and the detection performance of moving targets is influenced. Aiming at the problem that a typical SAR image domain DPCA moving target detection method has excessive false alarms in a complex terrain scene, the invention provides an image domain DPCA false alarm suppression method based on polarization classification, which suppresses false alarms caused by houses, bridges, street lamps and the like through multi-polarization image ground object identification and improves the moving target detection performance.

Description

Image domain DPCA false alarm suppression method based on polarization classification

Technical Field

The invention belongs to the field of synthetic aperture radar target detection, and particularly relates to an image domain DPCA false alarm suppression method based on polarization classification.

Background

Synthetic Aperture Radars (SAR) can obtain high-resolution two-dimensional images by using the motion of a flight carrier, and have wide application in the military and civil fields. With the modern battlefield environment becoming more complex, the Moving Target is often the focus of radar detection, so Ground Moving Target Identification (GMTI) has become an essential function of SAR radar. A multi-channel system arranged along a track in the SAR-GMTI system is the most common SAR-GMTI mode at present, a traditional single-channel system generally detects a moving target through Doppler parameters, and the multi-channel SAR-GMTI system generally detects the moving target according to inter-channel interference phases generated by target motion. The multi-channel SAR-GMTI method mainly includes Along-Track interference (ATI), Phase-Center offset Antenna (DPCA), Space-time Adaptive Processing (STAP), and the like. The ATI technology detects a moving target by setting a certain threshold on an interference phase between channels, but the detection effect is greatly influenced by ground clutter due to the lack of clutter suppression operation; the STAP method is a two-dimensional joint adaptive processing technology and can effectively inhibit clutter interference, but the STAP method is complex in structure and very large in signal processing calculation amount; the DPCA technique performs clutter suppression by complex data subtraction to detect a moving target, and is widely applied to an actual system because of its simple structure and easy implementation in engineering. The polarization can describe the electromagnetic wave space propagation track, besides the amplitude, the phase and the Doppler frequency, the target polarization characteristic is further key information of the SAR echo, for example, the ground object types in the SAR image can be classified by utilizing the polarization information, and in a complex terrain scene, the SAR-GMTI combined with the polarization information is a great trend of future SAR development. The DPCA method subtracts two complex images subjected to image registration and channel equalization, and the residual amplitude is zero because the phases of the static clutter are the same; the amplitude of the moving target is not zero (except for blind speed) after subtraction because of the difference of the phase. However, because objective adverse factors such as noise inevitably exist in an actual system, a static target sometimes has a small interference phase, and after subtraction, the static clutter still has partial energy residue. For stationary targets with strong scattering on roads and bridges, even if signals of two channels have only small amplitude-phase difference, the amplitude of clutter remaining after DPCA processing is still strong, so that a large amount of false alarms are caused, and the detection performance of moving targets is influenced.

Disclosure of Invention

Aiming at the problem that a typical SAR image domain DPCA moving target detection method has excessive false alarms in a complex terrain scene, the invention provides an image domain DPCA false alarm suppression method based on polarization classification, which suppresses false alarms caused by houses, bridges, street lamps and the like through multi-polarization image ground object identification and improves the moving target detection performance. The method specifically comprises the following steps:

step one, SAR imaging processing is respectively carried out on two-channel data to obtain a reference channel complex image

And another channel complex image

And for the complex image

Carrying out image registration and channel equalization processing to obtain a complex image

。

Step two, carrying out image domain DPCA processing and CFAR detection, and carrying out reference channel complex image

Complex image processed with another channel

Subtracting to obtain DPCA processed image

Subsequently, subsequentlyAnd performing constant false alarm rate detection by adopting a unit average CFAR method.

Step three, polarization classification is carried out by utilizing full polarization data of the reference channel, and the method adopts

Iterative classification method using polarization scattering entropy H and polarization angle

The method comprises the steps of dividing the ground objects into a plurality of categories, and identifying the low-entropy multiple scattering and the low-entropy dipole scattering as building features.

And step four, extracting the pixel position of the building in the polarization classification result, substituting the pixel position into the CFAR detection result, comparing the polarization classification result with the CFAR detection image, and determining the specific position of a false alarm caused by the building in the CFAR image.

And step five, removing the target detection result of the corresponding position in the CFAR detection result according to the position of the building, and reducing the false alarm caused by the building.

Further, the image registration in the step one is firstly carried out spline interpolation processing, and then the image registration is carried out by adopting a cross-correlation method.

Further, in the step one, the channel equalization adopts a two-dimensional frequency domain self-adaptive channel equalization method, the equalization weight coefficients of the distance direction and the azimuth direction are respectively calculated, and the complex image is processed

Respectively multiplying the weighted values by the balanced weight coefficients in the distance direction and the azimuth direction to correct the complex image

And (4) the amplitude and phase error of each pixel point.

The invention has the beneficial effects that:

compared with the existing multi-channel SAR moving target detection method, the method has the following remarkable benefits:

(1) the method of the invention combines a polarization classification method on the basis of a classical image domain DPCA method, can obviously reduce the number of false alarms caused by artificial buildings on roads or bridges, and improves the detection performance of moving targets.

(2) The method is explained based on an image domain DPCA method, but the idea of identifying the artificial buildings by polarization classification can be used in other full-polarization multi-channel SAR-GMTI detection results to improve the detection performance of the moving target.

Drawings

FIG. 1 is a flow chart of the method of the present invention.

Fig. 2 is a radar reference channel measured data SAR image.

Fig. 3 is a schematic diagram of the CFAR detection results without false alarm suppression.

FIG. 4 is a diagram illustrating the final moving object detection result of the method of the present invention.

Detailed Description

The invention is further explained below with reference to the figures and examples.

The flow chart of the method of the invention is shown in figure 1, and the specific method is as follows:

And another channel complex image except the reference channel

And performing image registration and channel equalization processing on the other channel image except the reference channel. Here, cubic spline interpolation of 10 times is performed, and then the registration amount calculated by the cross-correlation method is 1.0 pixel. The channel equalization adopts a two-dimensional frequency domain self-adaptive channel equalization method, the equalization weight coefficients of the distance direction and the azimuth direction are respectively calculated, the complex image of the other channel except the reference channel is respectively multiplied by the equalization weight coefficients of the distance direction and the azimuth direction, so that the amplitude and phase error of each pixel point on the complex image of the other channel except the reference channel is corrected, and the processed complex image of the other channel except the reference channel is obtained

. The reference channel SAR imaging result is shown in FIG. 2, in which the vertical direction is the azimuth direction, the horizontal direction is the distance direction, and the number of azimuth points

Number of distance direction points

. From the imaging results, it can be seen that there are many buildings with strong scattering properties near roads and bridges, as indicated by the marks in the figure. The effectiveness of the method provided by the invention is verified through the mark;

Complex image processed with another channel except the reference channel

Subtracting to obtain DPCA processed image

：

Performing CFAR detection after DPCA processing, designing a hollow sliding window, wherein the sliding radius is 25, the radius of the protection unit is 5, calculating statistical characteristics of clutter in the window, and setting a false alarm rate based on Rayleigh distribution hypothesis

And traversing the image by a sliding window, determining a threshold according to a local sample, obtaining a moving target detection result, and setting the amplitude of the residual pixel to be 1 for convenient observation.

CFAR results as shown in fig. 3, it can be seen that the buildings at the marker appear many bright spots because the energy remaining after cancellation is still much stronger than the surrounding clutter.

Step three, polarization classification is carried out by utilizing reference channel full polarization data, and the method adopts

And dividing the ground objects into 8 categories, and identifying the low-entropy multiple scattering and the low-entropy dipole scattering as building features to obtain the specific positions of the buildings in the images.

And step four, extracting the pixel position of the building in the polarization classification result, substituting the pixel position into the CFAR detection result, and comparing the polarization classification result with the CFAR detection image so as to determine the specific position of the false alarm caused by the building in the CFAR image.

And fifthly, eliminating false alarms caused by buildings on the road or the bridge in the CFAR detection result, wherein the false alarms caused by the buildings on the road or the bridge can be eliminated by adopting a method of setting the pixel amplitude occupied by the building false alarms identified by polarization classification in the CFAR detection result to be 0.

In order to further verify the effectiveness of the algorithm provided by the invention, the number of false alarms in a marking area (a bridge area approximately occupies 1500 azimuth units and 55 distance units) in a CFAR detection result is calculated, and it can be obviously seen from the figure that after the pixel of an artificial building is eliminated, the number of the false alarms is obviously reduced, the CFAR result in the area has about 42 false alarm points, the method provided by the invention has about 9 false alarm points, and the number of the false alarms is reduced by 78.6%; the number of false alarm points is summarized in the following table.

The present invention is not limited to the above-described specific embodiments, and various modifications and variations are possible. Any modifications, equivalents, improvements and the like made to the above embodiments in accordance with the technical spirit of the present invention should be included in the scope of the present invention.

Claims

1. An image domain DPCA false alarm suppression method based on polarization classification is characterized in that: the method comprises the following steps:

And another channel complex image

And for the complex image

；

Complex image processed with another channel

Subtracting to obtain DPCA processed image

Then, a unit average CFAR method is adopted to carry out constant false alarm rate detection;

Dividing the ground objects into a plurality of categories, and identifying the low-entropy multiple scattering and the low-entropy dipole scattering as building features;

step four, extracting the pixel position of the building in the polarization classification result, substituting the pixel position into the CFAR detection result, comparing the polarization classification result with the CFAR detection image, and determining the specific position of a false alarm caused by the building in the CFAR image;

2. The image domain DPCA false alarm suppression method based on polarization classification as claimed in claim 1, wherein: the image registration is firstly carried out spline interpolation processing, and then the image registration is carried out by adopting a cross-correlation method.

3. The image domain DPCA false alarm suppression method based on polarization classification as claimed in claim 1, wherein: the channel equalization adopts a two-dimensional frequency domain self-adaptive channel equalization method, the equalization weight coefficients of the distance direction and the azimuth direction are respectively calculated, and the complex image is processed

And (4) the amplitude and phase error of each pixel point.