Airborne multichannel circular SAR moving target detection and estimation method

Abstract

The invention provides an airborne multichannel circular SAR moving target detection and estimation method. The method comprises the following steps: preprocessing an original echo signal; projecting the multi-channel echo signal to a noise subspace by utilizing subspace projection in an original data domain, and performing clutter suppression; positioning the geographic space of the image in the absolute geographic space coordinate system, and constructing a model for back projection imaging; using the two-dimensional motion characteristics of the moving target and a backward projection algorithm for point-by-point pulse-by-pulse coherent accumulation imaging, compensating the aircraft motion error, the azimuth space-variant error and the error caused by the two-dimensional motion of the moving target, and directly outputting the imaging result to a digital orthoimage map in a geographic reference coordinate system; forming a steering vector by using a phase difference generated by a moving target between SAR images of different channels, performing coherent superposition on the SAR images of the multiple channels, and improving the signal-to-noise ratio of the target; and performing moving target detection on the synthesized SAR image, and estimating two-dimensional motion parameters of the target.

Description

technical field [0001] The invention relates to the technical field of radar, in particular to an airborne multi-channel circular SAR moving target detection and estimation method. Background technique [0002] Synthetic Aperture Radar (SAR) synthesizes a large antenna array through platform movement, thereby greatly improving the lateral resolution and realizing two-dimensional high-resolution imaging of the ground. Synthetic Aperture Radar (SAR)-Ground Moving Target Indication (GMTI) radar system combines SAR imaging and ground moving target indication technology, has its all-weather, all-weather advantages, so in the civil and military fields It has broad application potential. The airborne multi-channel SAR system can effectively suppress clutter and interference because of the increased degree of freedom in the airspace, and significantly improve the detection performance of the system for moving targets. Conventional airborne multi-channel SAR-GMTI systems usually tr...

AI Technical Summary

Problems solved by technology

Usually the MCSAR-GMTI system works in the downward-looking mode when detecting ground moving targets, so the impact of ground clutter on the system's detection performance is very serious

Ground clutter not only has a wide range of distribution, but also has a large intensity. At the same time, due to the continuous movement of the radar platform, the speed of the ground clutter in different directions relative to the radar platform is different, which makes the clutter spectrum broaden seriously, and the echo signal of the moving target is submerged. In strong ground clutter, it seriously affects the system's detection of moving targets

In addition, the two-dimensional motion characteristics and low radar cross section (Radar Cross Section, RCS) of slow moving targets also exacerbate this difficulty

With the development of MCSAR-GMTI towards high detection rate and high parameter estimation accuracy for slow moving targets, the traditional MCSAR-GMTI clutter suppression and detection processing algorithms can no longer meet this requirement

[0004] The traditional detection and estimation algorithms based on the data domain have the following technical defects: This type of method generally uses the space-time two-dimensional characteristics of clutter to perform adaptive clutter suppression. sport goal

However, in order to reduce the secondary phase effect of the moving target on the echo signal, this type of method generally uses less pulses, that is, sub-aperture data for processing, so the signal-to-noise ratio of the target is low, which affects the detection performance of the system

In addition, the adaptive algorithm in this type of method needs to use uniform sample data for clutter covariance estimation, but in reality, the environment is non-uniform, so its application is limited, and the estimation and inversion process of the covariance matrix is ​​calculated The complexity is also higher

[0005] The traditional detection and estimation algorithms based on the image domain have the following technical defects: this type of method uses the focused SAR image for processing, and the detection performance has a certain improvement due to the improvement of the signal-to-noise ratio of moving targets in the image domain

Due to the two-dimensional motion characteristics of the moving target, it is defocused on the SAR image, which causes a certain degree of loss in the signal-to-noise ratio of the target, and also deviates from the original position, which brings certain problems to the detection and parameter estimation of the target. Difficulties

Moreover, this type of method can only estimate the relative radial velocity of the moving target, but cannot estimate its along-course velocity, which is incomplete for the parameter estimation of the target

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