Parameter estimation range expansion method of sea clutter Pareto distribution model

Abstract

The invention discloses a parameter estimation range expansion method of a sea clutter Pareto distribution model. The method mainly solves the problem of effective estimation range limitation during the sea clutter shape parameter estimation in the prior art, and uses the realization scheme of 1, building a Pareto distribution model f<N>(z) of the sea clutters according to the composite model theory of the sea clutters; 2, using the Pareto distribution possibility density function of the sea clutters in N times of observation to deduce the r-odor origin matrix estimation expression <z<r>> of the practical observation value z of the sea clutters; 3, enlarging the value range of the r to the negative number range; estimating the sea clutter shape parameter alpha to obtain the estimated expression of the alpha; 4, when the observation times N is greater than 2, estimating the Pareto distribution parameter of the shape parameter in the range that alpha is an element of a set from 0 to positive infinity. The parameter estimation range expansion method has the advantages that the shape estimation range of the sea clutters is effectively enlarged; the estimation efficiency is improved; the method can be used for target detection.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a method for expanding the parameter estimation range of a sea clutter Pareto distribution model, which can be used for target detection. Background technique [0002] Parameter estimation has always been a core issue in the field of signal and information processing. The K-distribution model of sea clutter has attracted extensive attention from many scholars because of its reasonable theoretical explanation and good practical fitting. However, when the sea peak is strong, the K distribution model often cannot fit the actual sea clutter well at its tail. Although the KA and KK distributions can better fit the measured sea clutter than the K distribution, they are also due to The new components introduced bring more parameter estimation requirements and affect the real-time performance of radar target detection. [0003] Many literatures and studies i...

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Problems solved by technology

[0009] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art, and propose a method for expanding the parameter estimation range of the sea clutter Pareto distribution model based on closed expressions, so as to solve the problem that the effective parameter estimation range is limited while improving the operation efficiency. problem, to ensure the real-time performance of radar target detection

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