现代雷达2016，Vol.38Issue(10)：36-38,73,4.DOI:10.16592/j.cnki.1004-7859.2016.10.009
基于 K－邻相关与 RFT 的长时间积累算法
Long-time Accumulation AlgorithmB ased on K-neighborhood Correlation and Radon-Fourier
摘要
Abstract
With the development of stealth technology, the RCS of high-speed moving targets such as aircraft, the RCS of missile is getting smaller, which requires a long-time accumulation to improve detection capability.This paper proposed a small target long-time accumulation algorithm based on K-neighborhood correlation and Radon-Fourier transform( RFT) .Firstly, a rough estimation of target motion parameters is processed by the K-neighborhood correlation.Subsequently, a high efficiency accumulation is execu-ted by the RFT.Experimental results with simulated and measured data indicate that the proposed method provides an effective and efficient way for small target detection with the loss of SNR better than 0.5 dB.关键词
K-邻相关法/Radon-Fourier变换/长时间积累Key words
K-neighborhood correlation/Radon-Fourier Transform/long-time accumulation分类
信息技术与安全科学引用本文复制引用
陈昆,汪文英,桂佑林..基于 K－邻相关与 RFT 的长时间积累算法[J].现代雷达,2016,38(10):36-38,73,4.
