Optimal adaptive detection method under uniform K-distributed clutter

A K-distribution and clutter technology, applied in the field of adaptive detection, can solve the problems of detection performance degradation and achieve good detection performance and good detection effect

Inactive Publication Date: 2017-03-08
XIDIAN UNIV
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Problems solved by technology

[0005] The premise of the above optimal detection method is to assume that the detection unit and the reference unit have independent and identically distributed texture components. However, since the actual situation is that th

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  • Optimal adaptive detection method under uniform K-distributed clutter
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Embodiment Construction

[0034] The present invention will be further described below in conjunction with accompanying drawing:

[0035] refer to figure 1 , the implementation steps of the present invention are as follows:

[0036] Step 1. Construct the observation vector of the detection unit and the observation vector of the reference unit in the radar echo data.

[0037] (1.1) The radar emits a continuous pulse signal and irradiates the surface of the object to generate an echo, and then uses the radar to receive the echo data;

[0038] (1.2) Assuming that there is only clutter in the echo data and the target does not exist as H 0 , assuming that the clutter and the target exist simultaneously in the echo data as H 1 ;

[0039] (1.3) According to the echo data, the observation vector z of the detection unit and the observation vector z of the reference unit in the echo data under different assumptions are respectively constructed k :

[0040]

[0041] Among them, α represents the amplitude...

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Abstract

The invention discloses an optimal adaptive detection method under uniform K-distributed clutter. The method is implemented by the steps as follows: (1) building an observation vector of radar echo data; (2) calculating the estimated value of signal amplitude alpha<^>ML; (3) calculating data dependencies with use of the observation vector and alpha<^>ML; (4) getting a generalized likelihood ratio detector according to the Neyman-Pearson criterion; (5) getting the estimator M<^>SCM of a covariance matrix M of sea clutter speckle components and the iterative estimator beta of a scale parameter b through maximum likelihood estimation and sample covariance matrix estimation; (6) using M<^>SCM and beta to replace M and b in the generalized likelihood ratio detector respectively to get an adaptive optimal detector based on uniform K distribution; (7) calculating a detection threshold T; and (8) judging whether a target exists based on the detection threshold T. The target detection performance is improved. The method can be used in target detection under a sea clutter background.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to an adaptive detection method, which can be used for target detection under the sea clutter background. Background technique [0002] When the high-resolution radar works at a small grazing angle, the sea clutter shows strong non-Gaussian characteristics, and the composite Gaussian model can be used to simulate the sea clutter. The composite Gaussian model uses the product of two independent processes to describe sea clutter: one process is called texture component or slowly varying component, which is a non-negative random variable; the other process is called speckle component or rapidly varying component, which is Complex Gaussian process with zero mean. Under the compound Gaussian model, when the texture component of the clutter obeys the Gamma distribution, the corresponding sea clutter amplitude distribution model is the K distribution model; whe...

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/414
Inventor 水鹏朗郝津钏施赛楠许述文
Owner XIDIAN UNIV
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