【摘要】 针对未知频偏下的直扩信号,通过将载频吸收至扩频波形中,提出了一种有效的基于协方差矩阵子空间分解的扩频序列估计算法。通过信号子空间分解,提高了含有未知频偏信息的扩频波形估计的信噪比,从而降低了载频估计难度。在随机信号模型条件下,还推导了扩频波形估计器的克拉美劳界。在低信噪比条件下,仿真验证了该算法的有效性。更多还原

【Abstract】 In this paper,by absorbing the carrier frequency into the spreading waveform,an efficient algorithm to estimate the spreading sequence of direct sequence spread spectrum(DSSS) signals with unknown carrier offset is proposed.The proposed algorithm is based on the subspace decomposition of covariance matrix.The signal to noise ratio(SNR) of the spreading waveform estimation with unknown carrier offset is improved by signal subspace decomposition,which reduces the difficulty in carrier frequency estimation.Under the stochastic signal model assumption,we also derive the Cramer-Rao lower bound(CRB) of spreading waveform estimators.Simulation results demonstrate the effectiveness of proposed algorithm in lower SNR situations.更多还原