基于最大似然的同频混合信号联合定时估计算法

针对同频干扰下的混合信号时延估计问题进行研究，提出了一种基于最大似然准则的联合定时估计算法。该算法在推导似然函数的基础上，采用分级搜索方法估计信号时延，能同时实现干扰信号与有用信号的联合定时。相比传统的单信号时延估计，该算法需要有更长的观测数据长度；算法对频偏误差不敏感，在归一化频偏（相对于符号速率）小于2％时性能损失很小。仿真结果验证了算法的有效性。

ML-based joint timing estimation algorithm for co-frequency signals

A maximum likelihood (ML) based algorithm for joint timing estimation of both useful signal and co-channel interference is proposed. The likelihood function is first derived, and then the timings of two signals are identified in the two dimensional timing space by using a scale searching method. Compared with the traditional algorithm for single signal timing estimation, the proposed algorithm requires more observation data. The algorithm is little sensitive to frequency offsets and shows small performance attenuations for a frequency shift of 2% of the symbol rate. The simulation results verify the effectiveness of the proposed algorithm.