Maximum likelihood estimation method for sea clutter amplitude model parameters based on inverse Gaussian texture

A sea clutter and inverse Gaussian technology, applied in the field of signal processing, can solve the problems affecting the realization of sea surface target detection, low estimation accuracy of moment estimation method and high order.

Active Publication Date: 2016-11-23
XIDIAN UNIV
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Problems solved by technology

However, the moment estimation method requires a high order, especially for the use of the fourth-order moment of amplitude. When the number of sample

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  • Maximum likelihood estimation method for sea clutter amplitude model parameters based on inverse Gaussian texture
  • Maximum likelihood estimation method for sea clutter amplitude model parameters based on inverse Gaussian texture
  • Maximum likelihood estimation method for sea clutter amplitude model parameters based on inverse Gaussian texture

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[0027] The present invention will be further described below in conjunction with accompanying drawing:

[0028] The present invention utilizes the moment estimation method to estimate the scale parameters of the sea clutter amplitude distribution model based on the inverse Gaussian texture and shape parameter estimation As the initial value of the iteration of the scale parameter and the iterative initial value of the shape parameter Iterate according to the maximum likelihood estimation two-parameter iteration formula, and finally obtain the maximum likelihood estimation value of the scale parameter and the maximum likelihood estimates of the shape parameters

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

[0030] Step 1, select N clutter amplitude data: x 1 ,x 2 ,...,x n ,....,x N , to calculate the moment estimates of the scale parameter of the sea clutter data R and the moment estimates of the shape paramete...

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Abstract

The invention discloses a maximum likelihood estimation method for sea clutter amplitude model parameters based on inverse Gaussian texture and mainly solves the problem that the sea clutter amplitude model parameters are estimated inaccurately in the prior art. The method comprises steps as follows: 1), N clutter amplitude data are selected, and a moment estimation value of a scale parameter and a moment estimation value of a shape parameter are calculated; 2), a log-likelihood function is calculated according to a probability density function of a sea clutter amplitude distribution model; 3), a two-parameter iterative formula of the maximum likelihood estimation is obtained with the adoption of the log-likelihood function; 4), the two moment estimation values in the step 1) are taken as iterative initial values of the two parameters in the maximum likelihood estimation respectively; 5), the maximum likelihood estimation value (shown in the specification) of the scale parameter and the maximum likelihood estimation value (shown in the specification) of the shape parameter are obtained according to the two-parameter iterative formula in the step 3). The method can be used for effectively and accurately estimating the sea clutter amplitude distribution model parameters based on the inverse Gaussian texture through sufficient utilization of sample information, and can be used for target detection under the background of sea clutters.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a method for estimating parameters of an inverse Gaussian texture sea clutter amplitude distribution model, which can be used for target detection under the background of sea clutter. Background technique [0002] The backscattering of radar transmissions by the sea surface is known as sea clutter or sea surface echo. Compared with ground clutter or meteorological clutter, the characteristics of sea clutter are much more complex, and the existence of sea clutter will have a serious impact on radar target detection, positioning and tracking performance. The optimal target detection method in the sea clutter background depends on the model parameters of the sea clutter amplitude distribution model. The sea clutter amplitude distribution model changes with the radar resolution and sea conditions. How to effectively estimate the sea clutter amplitude distributio...

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 水鹏朗史利香黄宇婷于涵
Owner XIDIAN UNIV
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