一种基于循环稀疏表示的同频带干扰抑制及发射源定位方法

A Method of Co-Channel Interference Suppression and Transmitter Localization Method Based on Cyclic Sparse Representation

针对无线通信中的同频信号干扰问题,受信号稀疏表示及循环平稳特性启发,本文通过建立位置坐标的样本集合,构造字典矩阵,采用优化方法在循环频域实现稀疏信号重建,利用接收到信号的循环谱切片直接估计发射源位置.仿真结果表明,该所提算法的定位误差接近于推导的克拉美劳下界,在低信噪比和信干比条件下优于现有的频域直接定位和两步定位算法,具有更高的定位精度.

Toward the co-channel signal interference problem in wireless communications,inspired by sparse representation and cyclostationary characteristics,the dictionary matrix is constructed by establishing the sample set of position coordinates,and the sparse signal is reconstructed in cyclic frequency domain using optimization method.Then,the position of the transmitter is directly determined from the cyclic spectrum slice of the received signal.Simulation results show that the localization performance of the proposed algorithm is close to the derived Cramer-Rao lower bound,and outperforms the existing frequency domain direct localization algorithm and two-step localization algorithm,especially in cases of low signal-to-noise ratios and signal-to-interference ratios.