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A Quantile Estimation Method Based on Inverse Gaussian Textured Sea Clutter Amplitude Distribution Parameters

An amplitude distribution, sea clutter technology, applied in the field of information processing, can solve the problems affecting the realization of sea surface target detection, the reduction of the accuracy of moment estimation methods, and the high power, so as to improve the target detection effect, improve the robustness, and reduce the impact. Effect

Active Publication Date: 2018-12-21
XIDIAN UNIV
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Problems solved by technology

In the actual clutter data collection, there are often abnormal scattering units with high power generated by sea conditions, islands and reefs, etc., which greatly reduces the accuracy of the moment estimation method and affects the realization of sea surface target detection.

Method used

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  • A Quantile Estimation Method Based on Inverse Gaussian Textured Sea Clutter Amplitude Distribution Parameters
  • A Quantile Estimation Method Based on Inverse Gaussian Textured Sea Clutter Amplitude Distribution Parameters
  • A Quantile Estimation Method Based on Inverse Gaussian Textured Sea Clutter Amplitude Distribution Parameters

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Embodiment Construction

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

[0028] refer to figure 1 , the implementation steps of the present invention are as follows:

[0029] Step 1. Calculate the probability density function f(r, μ, η) based on the amplitude distribution of inverse Gaussian texture sea clutter.

[0030] (1.1) Calculate the probability density function p of the texture component τ of the sea clutter μ,η (τ):

[0031]

[0032] Among them, μ represents the scale parameter based on the amplitude distribution of sea clutter with inverse Gaussian texture, and η represents the shape parameter based on the amplitude distribution of sea clutter with inverse Gaussian texture;

[0033] (1.2) Using formula , the probability density function f(r, μ, η) based on the amplitude distribution of inverse Gaussian texture sea clutter is obtained:

[0034]

[0035] Among them, r represents the amplitude of sea clutter.

[0036] Step 2, u...

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Abstract

The invention discloses a quantile estimation method based on an inverse Gaussian texture sea clutter amplitude distribution parameter. The method mainly aims at solving a problem that estimation precision is not stable in the prior art. The method comprises the following steps of 1) calculating a probability density function based on inverse Gaussian texture sea clutter amplitude distribution and calculating an accumulation distribution function of the distribution; 2) selecting two accumulation probabilities in a sample and acquiring two quantiles according to a quantile definition; 3) using MATLAB software to calculate a ratio of the two quantiles when shape parameters are different so as to generate a shape parameter comparison table; 4) sorting clutter amplitude data and acquiring estimation values of the two quantiles; and 5) calculating a ratio of the estimation values of the quantiles, based on the shape parameter comparison table, acquiring an estimation value of the shape parameter and then acquiring an estimation value of a scale parameter. In the invention, an interference of an abnormal scattering unit on a sample is reduced, parameter estimation performance is increased and the method can be used for target detection under a sea clutter background.

Description

technical field [0001] The invention belongs to the technical field of information processing, and in particular relates to a method for estimating amplitude distribution parameters of sea clutter, which can be used for target detection under the background of sea clutter. Background technique [0002] Sea clutter is the electromagnetic echo that objectively exists in the process of radar detection and interferes with the detection of sea surface targets. Because sea clutter is affected by various factors such as climate conditions and sea surface environment, radar target detection under sea clutter background becomes more complicated. Therefore, the establishment of the sea clutter model and the determination of the corresponding parameters are of great significance in target detection. In previous studies, people used the central limit theorem to describe clutter data as a Gaussian model. However, with the improvement of radar resolution, sea spikes lead to intensified ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/292G01S7/41
CPCG01S7/2923G01S7/414
Inventor 水思源于涵史利香黄宇婷
Owner XIDIAN UNIV
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