基于主分量寻踪与分析的炮弹炸点检测

doi:10.3969/j.issn.1000-1093.2013.10.011

兵工学报 ›› 2013, Vol. 34 ›› Issue (10): 1266-1272.doi: 10.3969/j.issn.1000-1093.2013.10.011

基于主分量寻踪与分析的炮弹炸点检测

秦晓燕, 袁广林

解放军陆军军官学院管理工程系, 安徽合肥230031

收稿日期:2012-12-25 修回日期:2012-12-25 上线日期:2013-12-16
作者简介:秦晓燕(1980—),女,讲师。
基金资助:
国家自然科学基金项目(61175035)

Detection of Artillery Blast Point Based on Principal Component Pursuit and Analysis

QIN Xiao-yan, YUAN Guang-lin

Department of Management Engineering, Army Officer Academy of PLA, Hefei 230031, Anhui, China

Received:2012-12-25 Revised:2012-12-25 Online:2013-12-16

摘要/Abstract

摘要： 炮弹炸点检测是射击校射、毁伤效果评估和敌方火力位置估计的前提和基础。提出一种基于主分量寻踪(PCP)与主分量分析(PCA) 的炮弹炸点检测方法,该方法将炸点检测分为2 个阶段:利用PCP 从序列图像中恢复出候选目标;利用PCA 提取候选目标的线性度和运动方向 2 个特征实现炸点检测。采用炮弹炸点序列图像对提出的方法进行了实验验证,结果表明:与现有炮弹炸点检测方法相比,该方法在准确率和误检率方面均具有优越性能。

关键词: 信息处理技术, 炸点检测, 主分量寻踪, 主分量分析

Abstract: The blast point detection is a foundation of fire correction, damage evaluation and opposite firepower point estimation. Based on principal component pursuit and analysis, the proposed blast point detection method consists of foreground recovery and blast point detection. Firstly, the candidate targets are recovered from image sequence by using principal component pursuit (PCP). Then the blast points are detected with the linearity and motion direction features which are calculated via principal component analysis (PCA). Experimental results on large number of blast point image sequences show that the proposed method has superior performance in correct detection rate and false positive rate in comparison with the existing blast point detection method.

Key words: information processing, blast point detection, principal component pursuit, principal component analysis

中图分类号:

TP301. 6

秦晓燕, 袁广林. 基于主分量寻踪与分析的炮弹炸点检测[J]. 兵工学报, 2013, 34(10): 1266-1272.

QIN Xiao-yan, YUAN Guang-lin. Detection of Artillery Blast Point Based on Principal Component Pursuit and Analysis[J]. Acta Armamentarii, 2013, 34(10): 1266-1272.

参考文献

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基于主分量寻踪与分析的炮弹炸点检测

Detection of Artillery Blast Point Based on Principal Component Pursuit and Analysis

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