A joint processing of direction of arrival (DOA) and signal separation for planar array is proposed in this paper. Through sensor array processing theory, the output data of a planar array can be reconstructed as a parallel factor (PARAFAC) model, which can be decomposed with the trilinear alternating least square (TALS) algorithm. Aiming at the problem of slow speed on convergence for the standard PARAFAC method, we introduce the propagator method (PM) to accelerate the convergence of the TALS method and propose a novel method to jointly separate signals and estimate the corresponding DOAs. Given the initial angle estimates with PM, the number of iterations of TALS can be reduced considerably. The experiments indicate that our method can carry out signal separation and DOA estimation for typical modulated signals well and remain the same performance as the standard PARAFAC method with lower computational complexity, which verifies that our algorithm is effective.

中文翻译：

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使用快速PARAFAC分解的平面阵列DOA估计和信号分离的联合处理

本文提出了一种平面阵列到达方向(DOA)和信号分离的联合处理方法。通过传感器阵列处理理论，可以将平面阵列的输出数据重构为并行因子（PARAFAC）模型，该模型可以通过三线性交替最小二乘（TALS）算法进行分解。针对标准PARAFAC方法收敛速度慢的问题，我们引入了传播器方法（PM）来加速TALS方法的收敛，并提出了一种联合分离信号和估计相应DOA的新方法。给定 PM 的初始角度估计，TALS 的迭代次数可以大大减少。