A Correlation-based Sea Clutter Texture Estimation Method

A technology of sea clutter and correlation, applied in the research field of radar sea target detection, can solve problems affecting radar detection performance, sea clutter texture estimation error, etc., achieve good adaptive characteristics, improve accuracy, and accurately estimate the effect

Active Publication Date: 2021-09-17
中国电波传播研究所
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Problems solved by technology

The mean value processing is based on the assumption that sea clutter texture components are independently and identically distributed in the distance of the reference unit, and the median value processing is based on the above assumption to solve the problem of abnormal samples. However, with the improvement of radar resolution, the measured data The analysis results show that the texture components of sea clutter are not completely independent and identically distributed in the distance dimension, but have certain correlation characteristics. The inconsistency between the actual and the assumption will inevitably lead to a large error in sea clutter texture estimation, which will affect Radar Target Detection Performance

Method used

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  • A Correlation-based Sea Clutter Texture Estimation Method
  • A Correlation-based Sea Clutter Texture Estimation Method
  • A Correlation-based Sea Clutter Texture Estimation Method

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Embodiment 1

[0033] Example 1, such as figure 1 As shown, this embodiment discloses a correlation-based sea clutter texture estimation method, including the following steps:

[0034] Step 1, the echo data received by the radar is denoted as X, where X is a J×K dimensional complex matrix, and J and K are the number of distance units and pulses of the radar echo data respectively;

[0035] Step 2, calculate the power value of each pulse of the radar echo data based on X, and average the power values ​​of adjacent N pulses to form a matrix Y:

[0036]

[0037] L=floor(K / N).

[0038] Among them, N is the number of accumulated pulses in the target detection process, and floor( ) means rounding to the left;

[0039] Step 3, calculate the average correlation coefficient ρ of the radar echo power in the distance dimension based on Y:

[0040] Step 31, take the lth column in the matrix Y to calculate its autocorrelation coefficient:

[0041]

[0042]

[0043]

[0044] Where r (l, m)...

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Abstract

The invention discloses a method for estimating sea clutter texture based on correlation, which includes the following steps: step 1, the echo data received by the radar is recorded as; step 2, based on calculating the power value of each pulse of the radar echo data, and corresponding The power values ​​of adjacent pulses are averaged to form a matrix; step 3 is based on the steps of calculating the average correlation coefficient of radar echo power on the distance dimension; the method of the present invention is to solve the independent and identical distribution assumption and actual measurement in sea clutter texture component estimation To deal with the problem of inconsistent data, it is better adaptive to estimate the distance correlation characteristics of sea clutter texture components from measured data.

Description

technical field [0001] The invention belongs to the research field of radar sea target detection, in particular to a correlation-based sea clutter texture estimation method in the field, which can be used for sea clutter texture estimation in radar sea target detection. Background technique [0002] At present, the composite Gaussian model is recognized as the most effective sea clutter modeling model. It uses the product (or modulation) of two mutually independent processes to describe sea clutter: one is called the speckle component or the fast-varying component, which can be represented by zero The complex Gaussian process of the mean is modeled, and the other is called the texture component or slowly varying component, which is a non-negative random variable that characterizes the clutter power. In radar sea target detection, especially the target detection method based on statistical characteristics, the effectiveness of sea clutter texture component estimation of the u...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/41G01S7/292
CPCG01S7/2923G01S7/414
Inventor 夏晓云张玉石李清亮尹志盈朱秀芹黎鑫许心瑜张浙东张金鹏尹雅磊赵鹏李慧明李善斌万晋通
Owner 中国电波传播研究所
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