利用改进PAST算法的直扩信号PN码盲估计

摘要

针对直接序列扩频信号的伪随机(PN)码盲估计问题,提出了一种利用改进的投影逼近子空间(PAST)算法的PN码盲估计方法.该方法利用遗忘因子与收敛速度和精度的相关性构造基于跟踪误差的自适应遗忘因子,实现了收敛精度和收敛速度的同时优化;根据预期最低误码率约束估计精度变化范围确定迭代收敛的门限值,实现了迭代收敛的精确自动判读,消除了算法依赖人工判断收敛的固有限制,提高了算法的实际应用能力.仿真结果进一步验证了算法理论推导的正确性以及实际应用的可行性.%To solve the blind estimation problem of pseudo noise(PN) code for direct sequence spread spectrum(DS-SS) signals,a method based on improved Projection Approximation Subspace Tracking (PAST) algorithm is presented.The method uses the correlation of forgetting factor,convergent rate and convergence accuracy to propose an adaptive forgetting factor,optimizing convergent rate and accuracy at the same time.According to the variation range of convergence accuracy based on minimum bit error rate, the threshold of iterative convergence is proposed to determine whether iterates stop automatically,so as to improve the applicability of algorithm.Simulation result validates the correctness of theoretical derivation and the feasibility for practical application.