Joint DOA and Polarization Estimation via Canonical Polyadic Decomposition With Constant Modulus Constraints

• Published in: IEEE access Vol. 7; pp. 167521 - 167533
• Main Authors: Yang, Jin-Wei, Gong, Xiao-Feng, Xu, Chen-Yu, Lin, Qiu-Hua, Xu, You-Gen, Liu, Zhi-Wen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algebra; Algorithms; canonical polyadic decomposition; constant modulus; Decomposition; Direction of arrival; Direction-of-arrival estimation; Estimation; Mathematical analysis; Optimization; Polarization; Sensor arrays; Signal processing algorithms; tensor; Tensors; Transmission line matrix methods
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2950732

We consider the joint estimation of direction-of-arrival (DOA) and polarization of constant modulus (CM) signals based on an electromagnetic vector-sensor (EMVS) array. Two algebraic algorithms for canonical polyadic decomposition (CPD) with CM constraint are proposed in two scenarios, in which the source signals are fully and partially CM, respectively. The proposed algorithms use the analytic CM algorithm in the first step to calculate the source matrix, and then exploit the CPD structure of the data tensor to compute the remaining factor matrices, from which the DOA and polarization parameters can finally be obtained. Due to the algebraic nature, the proposed algorithms are faster and more stable than the optimization based algorithms, and can be used to effectively initialize the latter. We have shown that the proposed algorithms have more relaxed uniqueness conditions than unconstrained CPD, and thus can be applied in highly underdetermined cases where the number of source signals greatly exceeds that of the EMVSs. Simulation results are provided to illustrate the performance of the proposed algorithms.