Clutter covariance matrix estimation method for fast decoupling of airborne stap radar
A technology of covariance matrix and radar echo, applied in radio wave measurement systems, instruments, etc., can solve the problems of difficulty in accurately estimating clutter and noise covariance matrix and affecting target estimation, etc.
Active Publication Date: 2022-03-08
CHENGDU AERONAUTIC POLYTECHNIC
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[0006] Aiming at the above-mentioned deficiencies in the prior art, a fast airborne STAP clutter covariance matrix estimation method provided by the present invention solves the problem that the clutter-plus-noise covariance matrix is difficult to estimate accurately in small samples, which seriously affects the accuracy of target estimation. question
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[0059] This application studies the covariance matrix reconstruction problem of STAP radar signal detection in the presence of small samples and mutual coupling, uniform linear structure and sparse linear structure. More specifically, using the Toeplitz structure of the output covariance matrix, the problem of covariance matrix recovery for ULS and SLS is proposed. Firstly, an address matrix recovery problem based on covariance matrix recovery based on the toeplitz structure is proposed, and then the rank norm is replaced by the kernel norm to relax it, and a fast and feasible implementation algorithm is given to solve the address matrix recovery problem to improve the speed and Accuracy, then, utilizes the recovered covariance matrix to efficiently detect objects according to root STAP theory. At the same time, we combine the advantages of the sparse structure and use the concept of difference to reduce the influence of mutual coupling while improving the degree of freedom of...
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The present invention provides a clutter covariance matrix estimation method for rapid decoupling of airborne STAP radar, which obtains the original radar echo signal; obtains a model of the covariance matrix estimation value corresponding to the virtual structure composed of sparse linear structures; According to the model of the estimated value of the covariance matrix, the fast clutter covariance matrix estimation for the mutual decoupling of the airborne STAP radar is completed. This paper proposes a framework for Toeplitz covariance matrix reconstruction and applies it to uniform linear and sparse linear structures to solve the problems of insufficient training samples and mutual coupling. In order to make full use of the prior knowledge of the noise, this application adopts the clutter covariance matrix recovery structure, replaces the rank norm with the nuclear norm to relax it, derives the closed form solution of the problem, and gives its fast solution method. At the same time, the differential operation is applied to the sparse linear structure, and the limited number of array elements and pulses is used to obtain a higher degree of freedom of the system and reduce the mutual coupling effect.
Description
technical field [0001] The invention belongs to the field of airborne radar clutter suppression, in particular to a clutter covariance matrix estimation method for fast decoupling of airborne STAP radar. Background technique [0002] Space-time adaptive processing (STAP), which has excellent performance in clutter suppression and target detection, plays an important role in airborne radar. In the practical application of STAP, the system can calculate the ideal weight vector, and then obtain the optimal filter output response according to the clutter impulse noise covariance matrix estimated by the snapshots of its adjacent range cells. Therefore, the training samples in the adaptive radar system plays a vital role in. In practice, in order to obtain a reliable and accurate estimate of the covariance matrix, a large number of uniform training samples are required. In a heterogeneous environment, especially in a small sample, it is difficult to meet the above conditions. ...
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IPC IPC(8): G01S7/41G01S7/36
CPCG01S7/414G01S7/36
Inventor 刘明鑫冯文英王旭曹仕平
Owner CHENGDU AERONAUTIC POLYTECHNIC