CAJ | 학술논문

为了解决窄带干扰条件下低信噪比直扩信号扩频序列(direct sequence spread spectrum，DSSS)的盲估计问题，提出一种基于双PN周期分解的扩频波形估计算法。该算法用2倍PN周期进行采样形成观测向量，利用特征分解法求各特征值及其向量，并利用特征向量消除窄带干扰，并求出 PN 码序列。结果表明：该算法在低信噪比条件下能完成对PN码序列的精确估计，能解决传统方法利用单PN周期分解时扩频序列连接的相位模糊等问题。
위료해결착대간우조건하저신조비직확신호확빈서렬(direct sequence spread spectrum，DSSS)적맹고계문제，제출일충기우쌍PN주기분해적확빈파형고계산법。해산법용2배PN주기진행채양형성관측향량，이용특정분해법구각특정치급기향량，병이용특정향량소제착대간우，병구출 PN 마서렬。결과표명：해산법재저신조비조건하능완성대PN마서렬적정학고계，능해결전통방법이용단PN주기분해시확빈서렬련접적상위모호등문제。
In order to solve the problem of blind estimation of direct sequence spread spectrum (DSSS) signal with narrowband interference in low SNR conditions, this paper proposes a spreading waveform estimation algorithm based on double PN decomposition. The algorithm obtains observation vector by sampling with twice PN cycle, and then getting the feature values and their vectors by feature value analysis. Using feature vectors to eliminate narrowband interference, and find the PN code sequence. The results show that the algorithm can complete the accurate estimation of PN code sequence in lower SNR conditions, and also can solve the phase ambiguity issues when PN spreading sequence connected in the traditional method using single cycle decomposition.