Space-time adaptive processing method for radar clutters based on prior knowledge

Abstract

The invention discloses a space-time adaptive processing method for radar clutters based on prior knowledge. An airborne radar is determined, the airborne radar includes N array elements, each array element includes L distance units, each distance unit includes K coherent pulses, Doppler domain data vectors in the first distance units of the N array elements of the airborne radar are calculated, and the weighted coefficient alphanlk of the first distance unit in the nth array element and the kth Doppler unit, the Doppler domain data vectors znlk of the first distance unit in the nth array element in the (k-1)th, kth and (k+1)th Doppler channels, and a covariance matrix Rnlk of the first distance unit of the weighted nth array element in the kth Doppler channel are calculated successively; a space-time filter coefficient wnlk of the first distance unit in the nth array element and the kth Doppler channel is calculated, and output data ynlk of the first distance unit in the nth array element and the kth Doppler channel after clutter inhibition is calculated; and further, final Doppler-spectrum output data of the airborne radar after clutter inhibition is calculated.

Description

technical field [0001] The invention belongs to the technical field of radar communication, and in particular relates to a priori knowledge-based radar clutter space-time adaptive processing method, that is, a priori knowledge-based radar clutter space-time adaptive processing (Knowledge-Aided Space TimeAdaptive Processing, KASTAP ) method, which is suitable for solving the problem of inaccurate estimation of airborne radar sampling covariance matrix in non-uniform clutter environment, and can assign different weights to different training samples according to prior knowledge, thereby improving the clutter of adaptive signal processing. Wave suppression performance. Background technique [0002] The main task of airborne early warning radar is to detect targets in complex clutter environment and to locate and track them, and effective suppression of clutter is the core means to improve the performance of early warning radar; space-time adaptive processing technology (SpaceTi...

AI Technical Summary

Problems solved by technology

[0004] In order to improve the performance of the STAP algorithm for space-time adaptive processing in a non-uniform environment, the generalized inner product (GIP) algorithm can be used to eliminate non-uniform training samples from the initial training samples, but the GIP algorithm does not combine the clutter of the unit to be detected In addition, some scholars have proposed knowledge-aided space time adaptive processing (KASTAP) based on prior knowledge, using available radar inertial navigation data, map data and road information as prior knowledge knowledge to assist space-time adaptive processing, and achieved good results, proving the application value of prior information in space-time adaptive processing STAP; however, because the reflectivity of the airborne radar changes with the grazing angle, the same Surface types may also produce different reflectances. At this time, it is obviously inappropriate to simply select units that are similar to the terrain of the unit to be detected as training samples.

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