超宽带系统中基于稀疏恢复的TOA和DOA联合估计方法

A Joint TOA and DOA Estimation Method Based on Sparse Recovery in UWB System

针对稀疏表示框架下进行超宽带系统中到达时间(Time of Arrival,TOA)和波达方向(Direction of Arrival,DOA)联合估计的问题,提出了一种基于稀疏恢复的TOA和DOA联合估计方法。采用l范数作为稀疏约束条件,并利用联合正交匹配追踪算法获取TOA估计值,解决了TOA配对问题,最后根据两副天线的时延差与DOA之间的关系获得信号的DOA估计。所提算法考虑了离网格信号参数估计问题,并通过联合稀疏恢复进行补偿。仿真结果表明,所提算法的参数估计性能优于传统的压缩感知算法、传播算子算法、矩阵束算法以及借助旋转不变性的信号参数估计技术(Estimating Signal Parameters via Rotational Invariance Techniques,ESPRIT)算法,同时计算复杂度更低。

For the problem in the joint estimation of time of arrival(TOA)and direction of arrival(DOA)in ultra-wideband(UWB)system under the framework of sparse representation,a joint estimation method of TOA and DOA based on sparse recovery is proposed.In this algorithm,the norm l is used as the sparse constraint condition,and the TOA estimation is obtained by using the joint orthogonal matching pursuit algorithm,and the TOA pairing problem is solved.Finally,the DOA estimation of the signal is obtained according to the relationship between the delay difference of two antennas and the DOA.The proposed algorithm considers the parameter estimation of off-grid signals and compensates them through joint sparse recovery.The simulation results show that the proposed algorithm has better parameter estimation performance than the traditional compressed sensing algorithm,the traditional propagation operator algorithm,matrix beam algorithm and estimating signal parameters via rotational invariance techniques(ESPRIT),and also reduces the computational complexity.