基于波导干涉条纹的目标距离特征量提取方法  

Extraction Method of Target Distance Characteristic Feature Based on Waveguide Interference Striations

作　　者：何青海[1] 李长军[1] 于雪泳[1] 

机构地区：[1]海军潜艇学院,山东青岛266042

出　　处：《火力与指挥控制》2015年第7期57-61,共5页Fire Control & Command Control

基　　金：国家重点实验室基金资助项目(No.613122)

摘　　要：浅海波导中目标辐射噪声LOFAR谱图存在明暗相间的干涉条纹,从中可以提取出目标距离特征量信息,它反映了目标运动过程中的距离变化率。低信噪比情况下,条纹特征不够清晰,提取的距离特征量值精度会降低。提出了一种边缘定向增强型偏微分方程去噪方法,对LOFAR谱图进行处理,使条纹特征更加明显。海试数据处理结果表明,去噪处理后提取出的距离特征量精度明显提高。为满足实时性需要,提出了基于CUDA的距离特征量实时处理方法,实验结果表明能大幅提高算法运行速度。Striations have been appeared in plots of Low Frequency Analysis Recording（LOFAR）spectrum in acoustic environment of the shallow water. The distance change ratio of target can be described by distance characteristic feature. It can be extracted from LOFAR spectrum striations. Low precision of distance characteristic feature has been obtained because of the low signal to noise ratio and striation pollution. In order to make the striations more clearly,a new edge-directed enhancement partial differential equation model has been put forward to denoise the LOFAR spectrum image. The ocean experimental results show that the precision of distance characteristic feature is one times higher after LOFAR spectrum image processing. Considering the real-time requirements of distance characteristic feature,real-time extracting method of distance characteristic feature based on Compute Unified Device Architecture（CUDA）is put forward. Experimental results show that the running speed of real-time algorithm has been highly increased.

关 键 词：距离特征量 LOFAR谱 偏微分方程去噪 CUDA 

分 类 号：TN24[电子电信—物理电子学] TM934[电气工程—电力电子与电力传动]