一种适用于低信噪比环境下的差分相关捕获方法

摘要

Acquisition is a key technology in DSSS system.The differential correlation is usually employed to eliminate the effect of frequency deviation.However,as the length of pseudo-code grows and the decrease of the SNR,the traditional differential acquisition algorithms will result in great loss of SNR.This paper presents an improved differential acquisition method,named as MUACDF.In the proposed method,the input signal is multiplied by the complex conjugate of the pseudo-code to eliminate its effect.After that,the product is applied to the M-orders Unbiased Auto-Correlation to compensate the SNR loss caused by the differential process.By means of mathematical model to analyze its acquisition performance.MUAC-DF acquisition algorithm is compared with the differential coherent and non-coherent acquisition algorithms through simulation.The simulation results indicate that this algorithm is approximately 4～5 dB superior to the traditional differential acquisition algorithms in improving acquisition sensitivity and more adaptive to work under low SNR.%直接扩频系统中的捕获是一项非常关键的同步技术.常用差分处理来消除频偏对峰值的影响,然而一般差分捕获算法随着伪码的增长、信噪比的降低都会导致信噪比的损失很大.提出一种改进的差分捕获算法,基于差分相关的M阶无偏自相关捕获算法(MUAC-DF),将信号和伪码相乘消除伪码信息后做M阶无偏差分自相关,在一定程度上弥补了差分带来的信噪比损失,提高了抗噪性能;详细介绍了其数学模型,并且从理论上分析了MUAC-DF算法性能;最后在相同条件下进行仿真验证.实验结果表明,MUAC-DF捕获算法比一般的差分非相干码捕获技术性能更加优越,其捕获性能有4～5 dB的改善,更适应于低信噪比条件下工作.