摘要
在直升机和无人机等目标的检测和识别方面,常用的方法没有充分利用目标信号的谐波特性,易受实战环境下强噪声和干扰的影响而降低检测能力。采用两个途径提高检测能力:利用谐波信号的相干特性,采用循环处理方法降低随机噪声和干扰的影响;采用频率分集分析和处理方法,将各阶谐波的循环平稳特征融合,提高抗干扰能力。计算结果表明,循环平稳处理方法可以正确的提取信号的频率特征;融合处理方法能在信噪比为2 dB甚至更低时检测谐波信号的循环平稳特征。该方法在多个领域具有较好的应用前景。
For the detection and identification of helicopters and UAV,the common methods do not take full advantage of the harmonic characteristics of the target signals,and are vulnerable to environment noise and interference on the battlefield,so the detection ratio is reduced.Efforts to improve the detection ability are done in two ways：first,according to the coherence properties of harmonic signals,the cyclostationary analysis arithmetic is used to reduce the effect of the noise;second,the frequency diversity concept is used to analyze and fuse the harmonic signal feature.The results show that the cyclostationary analysis arithmetic can accurately extract the frequency characteristics of signals,and the fusion arithmetic can detect signal with SNR as low as 2 dB or even lower.This method has a good prospect in more application.
出处
《探测与控制学报》
CSCD
北大核心
2009年第5期33-37,共5页
Journal of Detection & Control
关键词
循环平稳
频率分集
直升机
声信号
检测
cyclostationary analysis
frequency diversity
helicopter
acoustic signal
detection
