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System and method for radar sea clutter forecast by using chaos optimization

A forecasting system, sea clutter technology, applied in radio wave measurement systems, instruments, etc., can solve the problems of being easily affected by human factors and low accuracy

Inactive Publication Date: 2011-09-14
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the traditional radar sea clutter prediction method, which is not high in accuracy and is easily affected by human factors, the present invention provides a high-precision chaotic optimization radar sea clutter prediction system and method that avoids the influence of human factors

Method used

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  • System and method for radar sea clutter forecast by using chaos optimization
  • System and method for radar sea clutter forecast by using chaos optimization
  • System and method for radar sea clutter forecast by using chaos optimization

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Embodiment 1

[0082] refer to figure 1 , figure 2 , a chaotic optimization radar sea clutter forecasting system, comprising a database 2 connected to the radar 1, and a host computer 3, the radar 1, the database 2 and the host computer 3 are connected in sequence, the radar 1 irradiates the detected sea area, and The radar sea clutter data is stored in the database 2, and the upper computer 3 includes:

[0083] The data preprocessing module 4 is used for radar sea clutter data preprocessing, which is completed by the following process:

[0084] 1) Collect N radar sea clutter echo signal amplitude x from the database i As a training sample, i=1,...,N;

[0085] 2) Normalize the training samples to obtain the normalized amplitude

[0086] x ‾ i = x i - min x max x - ...

Embodiment 2

[0120] refer to figure 1 , figure 2 , a method for forecasting chaotic optimal radar sea clutter, said method comprising the following steps:

[0121] (1) Collect N radar sea clutter echo signal amplitude x from the database i As a training sample, i=1,...,N;

[0122] (2) Normalize the training samples to obtain the normalized amplitude

[0123] x ‾ i = x i - min x max x - min x

[0124] Among them, minx represents the minimum value in the training sample, and maxx represents the maximum value in the training sample;

[0125] (3) Reconstruct the normalized training samples to obtain the input matrix X and the corresponding output matrix Y respectively:

[0126] X = ...

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Abstract

A system for radar sea clutter forecast by using chaos optimization comprises a radar, a database and a host computer, wherein the radar, the database and the host computer are orderly connected; the radar irradiates on to-be-detected sea area, and saves radar sea clutter data into the database; the host computer comprises a data preprocessing module, a forecast model modeling module, a chaos optimizing module, a sea clutter forecasting module, a discrimination model updating module and a result display module. Besides, the invention also provides a chaos optimizing radar sea clutter forecasting method. In a word, the invention provides a high-precision system and method for radar sea clutter forecast by using chaos optimization, which can rapidly search optimization and avoid influence of human factor.

Description

technical field [0001] The invention relates to the field of radar data processing, in particular to a chaotic optimization radar sea clutter forecasting system and method. Background technique [0002] Sea clutter, that is, backscattered echoes from a patch of sea illuminated by radar transmissions. Because sea clutter severely restricts the detectability of radar echoes from "point" targets on or near the sea surface, such as navigational buoys and ice blocks floating on the sea, the study of sea clutter has a great impact on the ocean background. The detection performance of ships and other targets has a very important impact, so it has important theoretical significance and practical value. [0003] Habitual Shanghai clutter is regarded as a single random process, such as lognormal distribution, K distribution, etc. However, these models have their specific limitations in practical applications. One of the important reasons is that the seemingly random waveforms of sea...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/41
Inventor 刘兴高闫正兵
Owner ZHEJIANG UNIV
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