摘要
由于噪声的影响,基于引导源定位算法中形成的声场干涉条纹图像模糊不清,利用图像特征提取技术无法提取出距离特征量。为了实现低信噪比条件下对目标的准确定位,提出了先对干涉图像进行降噪处理,再进行特征提取的解决思路。介绍了3种去噪方法,并对它们的性能进行比较。研究结果表明,降噪能有效克服定位失准问题,且小波阈值方法效果最好。
Sound field interference fringe image generated in target localization algorithm using a guide source（GTL algorithm）is always ambiguous because of noise. Range measure of characteristics can not be extracted. In order to achieve the distance accurate location in the low signal to noise（SNR） ,image denoisingmethod is proposed. In the first, fringe image has been denoised; after that extractive technique of characteristics is used to estimate object range. Three denoising methods are introduced and compared on denoising performance. The research results show that wavelet thresholding denoising method is the best one.
出处
《舰船科学技术》
北大核心
2012年第3期80-84,共5页
Ship Science and Technology
基金
国防预研基金项目资助(51303020401)
关键词
引导源目标定位算法
低信噪比条件
小波阈值去噪
距离特征量
GTL algorithm
low signal to noise
wavelet thresholding denoising
range measure ofcharacteristics
