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Moment Estimation Method of Sea Clutter Amplitude Distribution Parameters Based on Inverse Gaussian Texture

A technology of amplitude distribution and sea clutter, which is applied in the field of signal processing, can solve the problems of inapplicability and large error in estimating sea clutter amplitude distribution model parameters, and achieve the effect of simplifying the process and improving accuracy

Active Publication Date: 2018-08-10
XIDIAN UNIV
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Problems solved by technology

Due to the large error in estimating the model parameters of the amplitude distribution of sea clutter, this method cannot be applied to the actual parameter estimation

Method used

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  • Moment Estimation Method of Sea Clutter Amplitude Distribution Parameters Based on Inverse Gaussian Texture
  • Moment Estimation Method of Sea Clutter Amplitude Distribution Parameters Based on Inverse Gaussian Texture
  • Moment Estimation Method of Sea Clutter Amplitude Distribution Parameters Based on Inverse Gaussian Texture

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with accompanying drawing:

[0029] refer to figure 1 , the implementation steps of the present invention are as follows:

[0030] Step 1, calculate the first-order moment E(y) and second-order moment E(y) of the sea clutter amplitude distribution model 2 ).

[0031] (1.1) Calculate the integral according to the probability density function f(y, μ, γ) of the sea clutter amplitude distribution model based on inverse Gaussian texture with The first-order moment E(y) and the second-order moment E(y) of the sea clutter amplitude distribution model based on the inverse Gaussian texture are obtained 2 ):

[0032]

[0033]

[0034] in,

[0035] y≥0, y represents the sea clutter amplitude, μ represents the scale parameter of the amplitude distribution model, γ represents the shape parameter of the amplitude distribution model, K 0 Indicates the 0th order modified Bessel function of the second ...

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Abstract

The invention provides a moment estimation method of sea clutter amplitude distribution parameters based on inverse Gaussian texture. The method mainly solves the problem of large parameter estimation error in the prior art is solved. The method comprises the steps that 1) the first moment and the second moment of a sea clutter amplitude distribution model are calculated; 2) sea clutter sample data are generated, and the scale parameter estimation value is calculated; 3) the scale parameter estimation value is used to normalize the sea clutter sample data, and the first moment of the normalized data is calculated; 4) different values are taken for the shape parameter gamma of the sea clutter sample data, and the first moment of the corresponding normalized sea clutter sample data is calculated to generate a shape parameter comparison table; 5) sea clutter amplitude data are generated, and after the data are normalized, the first moment is calculated; and 6) the first moment is compared with the shape parameter comparison table to acquire the shape parameter estimation value of sea clutter amplitude distribution based on inverse Gaussian texture. According to the invention, the parameter estimation accuracy is improved, and the method can be used for target detection under the sea clutter background.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a moment estimation method, which can be used for target detection under the sea clutter background. Background technique [0002] Sea clutter refers to the backscattered echo of the sea surface after the radar beam illuminates the sea surface. Compared with ground clutter and meteorological clutter, the characteristics of sea clutter are much more complicated, and the existence of sea clutter has a great impact on radar target detection, Location tracking performance will have a severe impact. In order to reduce the influence of sea clutter on radar target detection, the research and perception of sea clutter characteristics are necessary foundations. When detecting sea surface targets, establishing a model that can accurately describe the amplitude distribution and correlation characteristics of sea clutter is an important prerequisite for optimal detecti...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41
CPCG01S7/414
Inventor 水鹏朗黄宇婷于涵史利香
Owner XIDIAN UNIV
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