The quaternion coherence problem exists in the data model of the conventional dimensional reduced quaternion estimation of signal parameters via rotational invariance techniques(DRQ-ESPRIT), and DRQ-ESPRIT would lose degrees of freedom(DOFs)when it is used to implement the spatial smooth operation. An improved DRQ-ESPRIT algorithm based on 2-level nested vector-sensor array is proposed in this paper. The quaternion coherence problem is solved by switching the multiplication sequence of spatial direction vector and electric field. Meanwhile, nested array and Khatri-Rao subspace approach are used to increase the number of DOFs, thus the proposed algorithm can estimate more incident sources than DRQ-ESPRIT, and the estimations of direction of arrival(DOA)and polarization parameters are more accurate. Simulation results demonstrate the effectiveness of the proposed algorithm.
The quaternion multiple signal classification(Q-MUSIC)algorithm generally requires four-dimensional spectral peak search to estimate the direction of arrival(DOA)and polarization parameters,which would result in the huge computation burden.A dimension reduction Q-MUSIC algorithm(DRQ-MUSIC)based on L-shaped array is presented to reduce the computational complexity in this paper.The proposed algorithm divides the steering vector into three parts,and estimates each part separately,thus DOA and polarization parameters can be estimated only by N times one-dimensional spectral peak search,where N denotes the sources number.Besides,pair match is not required.Finally,simulation examples demonstrate the effectiveness and feasibility of the proposed algorithm.
全球卫星定位系统(global position system,GPS)接收机使用空时自适应处理能够增益信号并抑制干扰,但空时自适应处理结构影响GPS信号的定位精度。首先推导空时自适应处理后,GPS信号与参考信号的相关波形,分析了空时处理对码跟踪的影响。然后在码跟踪过程中改进本地参考信号以补偿相关波形的误差,减少空时自适应处理后的码跟踪精度损失。仿真和实测结果验证了算法的有效性。
