Approximately optimal radar target detection method against K-distributed clutter plus noise

Abstract

The invention discloses an approximately optimal radar target detection method against K-distributed clutter plus noise and aims to solve the problem that the prior art is not completely suitable for target detection against K-distributed clutter plus Gaussian white noise. The method comprises steps of: 1) acquiring an echo data matrix, and blocking the echo data matrix; 2) selecting a to-be-detected distance unit zk of the bth echo data block, and calculating the covariance matrix estimator R<k> of the to-be-detected distance unit zk; 3) calculating the carrier noise ratio CNR of the echo data by use of the covariance matrix estimator R<k>; 4) calculating the test statistics xik of the to-be-detected distance unit by use of the CNR and the R<k>; 5) calculating the detection threshold T<xi> according to the false alarm probability; and 6) judging whether the a target exists or not by comparing the size of the test statistics xik and the detection threshold T<xi>. In this way, the target detection performance is improved and the approximately optimal radar target detection method can be used for radar motion detection under the back ground of sea clutter.

Description

technical field [0001] The invention belongs to the technical field of radar target detection, and in particular relates to a near-optimal radar target detection method under K-distribution clutter plus noise, which can be used for target detection under the background of sea clutter. Background technique [0002] Object detection in sea clutter background is an important application field of radar. [0003] Matched filter MF and adaptive matched filter AMF are the optimal detectors in Gaussian clutter background. As the radar resolution increases, the Gaussian model is no longer applicable, and the two detectors are no longer applicable due to model mismatch. [0004] The composite Gaussian model is a sea clutter model widely recognized by scholars at present. It is the product of a slowly varying positive random variable texture component and a rapidly varying complex Gaussian random vector speckle component. When the texture component of the sea clutter obeys the Gamma ...

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Problems solved by technology

Literature. F.Gini, "Suboptimal coherent radar detection in a mixture of K-distributed and Gaussian clutter," IEE Proc.-Radar, Sonar, Navig., 144(1):39-47, 1997. and literature F.Gini , M.V.Greco, A.Farina, P.Lombardo, "Optimum and mismatched detection against K-distributed clutter plus Gaussian clutter," IEEE Trans.Aerospace Electron.Systems 34(3):860-876, 1998. This model is discussed in the context of The optimal detector is the optimal K distribution plus Gaussian white noise detector OKGD, but because the detector expression is too complex, the calculation efficiency is extremely low and cannot be applied in practice

In the background of K-distributed clutter plus Gaussian white noise, the detection performance of the currently used matched filter MF and adaptive matched filter AMF decreases rapidly with the increase of the clutter-to-noise ratio, and the detector α-MF which depends on the shape parameter and shape parameter dependent adaptive detector α-AMF have poor detection performance at low noise-to-noise ratio

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