Background clutter suppression technology based on genetic neural network

doi:10.3778/j.issn.1002-8331.2010.23.050

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (23): 178-180.DOI: 10.3778/j.issn.1002-8331.2010.23.050

• 图形、图像、模式识别 • Previous Articles Next Articles

Background clutter suppression technology based on genetic neural network

LI Zhi-jun¹，FAN Qiao-yan²，Askar Hamdulla²

1.Institute of Physics Science and Technology，Xinjiang University，Urumqi 830046，China
2.Institute of Information Science and Technology，Xinjiang University，Urumqi 830046，China

Received:2009-01-19 Revised:2009-03-27 Online:2010-08-11 Published:2010-08-11
Contact: LI Zhi-jun

基于遗传神经网络的背景杂波抑制技术研究

李志军¹，范巧艳²，艾斯卡尔·艾木都拉²

1.新疆大学物理科学与技术学院，乌鲁木齐 830046
2.新疆大学信息科学与工程学院，乌鲁木齐 830046

通讯作者: 李志军

Abstract

Abstract: The performance of detecting point moving target under the condition of low Signal Noise Ratio（SNR） IR（Infra-
Red） images is dependent greatly on the suppression of background clutter.For the global search capability of genetic algorithm and nonlinear mapping ability of neural network，a kind of background clutter suppression technology based on genetic neural network is presented in this paper.Gaussianity and independency of residuals are also verified using Kendall rank correlation and Friedman statistic methods.

Key words: clutter suppression, genetic algorithm, neural network, Kendall rank correlation, Friedman statistic

摘要： 低信噪比条件下点状运动目标的检测性能在很大程度上依赖于对红外背景杂波的抑制情况。针对遗传算法的全局搜索能力以及神经网络的非线性预测能力，提出了一种基于遗传神经网络的背景杂波抑制技术。杂波抑制后，残留噪声的高斯性和独立性通过 Kendall秩相关法和计算Friedman统计量的方法进行了验证。

关键词: 杂波抑制, 遗传算法, 神经网络, Kendall秩相关系数, Friedman统计量

CLC Number:

TN911.23

LI Zhi-jun¹，FAN Qiao-yan²，Askar Hamdulla². Background clutter suppression technology based on genetic neural network[J]. Computer Engineering and Applications, 2010, 46(23): 178-180.

李志军¹，范巧艳²，艾斯卡尔·艾木都拉². 基于遗传神经网络的背景杂波抑制技术研究[J]. 计算机工程与应用, 2010, 46(23): 178-180.

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Background clutter suppression technology based on genetic neural network

基于遗传神经网络的背景杂波抑制技术研究

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