噪声跟踪干扰检测算法性能分析

Performance Analysis of Detection Algorithm for Follower Noise Jamming

摘要: 基于认知无线电中协作频谱感知的思想,提出了一种跳频通信中噪声跟踪干扰的检测算法。首先采用能量检测算法,研究了干扰条件下单跳信号的检测性能。在此基础上,应用“k out of n”准则,在决策融合模块实现对噪声跟踪干扰的检测,推导了AWGN信道下噪声跟踪干扰的检测性能。理论分析和仿真结果表明,随着信干噪比的逐渐减小,对于单跳信号和噪声跟踪干扰的检测概率均逐渐增大；而在相同信干噪比情况下,噪声跟踪干扰的检测概率较单跳信号的检测概率得到了提高。

Abstract: A novel detection algorithm of follower noise jamming for Frequency Hopping (FH) communication system was proposed based on the Cognitive Radio(CR). The detection performance of single hop was researched using the energy detection algorithm. Then the detection of follower noise jamming was realized in the data fusion center using the “k out of n” rule, the detection performance of follower noise jamming was deducted in additive white gaussian noise (AWGN) channel. The results analyzing and simulation show that the detection probability of single hop and Follower noise jamming(FNJ) were increased when the SINR was decreased. The detection probability of FNJ was more increased than the single hop when they were had the same SINR.