减少防撞雷达虚假目标的信号处理研究  

Signal processing study on reducing false targets for anti-collision radar

作　　者：孙艳敏 周长林[1] 常青美[1] 高辉[1] 

机构地区：[1]解放军信息工程大学理学院,河南郑州450001

出　　处：《微型机与应用》2011年第18期46-48,51,共4页Microcomputer & Its Applications

摘　　要：从信号处理的角度分析了防撞雷达虚报警率、漏报警率偏高的原因,采用AR模型功率谱估计的Burg算法代替传统的FFT算法,并将粗神经网络应用于防撞雷达目标识别。仿真结果表明,此方法提高了雷达信号处理的准确度和目标识别率,能有效地降低漏报警、虚报警率。This article analyzes the reasons for the high rate of leakage alarm and false alarm of the anti-collision radar from the point of the signal processing, using the Burg algorithm of AR models power spectrum estimation instead of the traditional FIT algorithm, and use the rough neural network for anti-collision radar target identification. Simulation results show that this method improves the accuracy of radar signal processing and target recognition rate, which can effectively reduce the leakage alarm and false alarm rate.

关 键 词：防撞雷达 虚假目标 功率谱估计 粗神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]