Reduced-dimensional parameter estimation algorithm based on coprime polarization sensitive array
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1.College of Electrical Engineering, Sichuan University,Chengdu 610065, China; 2.Beijing Institute of Remote Sensing Equipment,Beijing 100005, China; 3.Southwest Institute of Technical Physics,Chengdu 610045, China

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TN911.7

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    Abstract:

    A joint DOA and polarization parameters estimation algorithm based on modulus-constrained reduced-dimensional and root multiple signal classification (MUSIC) is proposed for coprime polarization sensitive arrays to address the high computational complexity and ambiguity pairing errors. Firstly, by reconstructing the three-dimensional spectral function, the DOA and polarization parameters are decoupled to achieve dimensionality reduction in the three-dimensional MUSIC method. Then, the DOA is solved using polynomial roots, and the beamforming method is used to solve the problem of ambiguity angle mismatch in the coprime array. Finally, the cost function is constructed using the modulus boundedness of the polarization vector to derive the closed form solution of the polarization parameters. The numerical simulation results have verified the effectiveness of the algorithm. The simulation results show that the parameter estimation performance of the proposed algorithm is better than that of the estimating signal parameter via rotational invariance techniques (ESPRIT), and is basically equivalent to the one-dimensional total spectral peak search MUSIC (1D-TSS-MUSIC) algorithm. However, our algorithm significantly reduces computational complexity and can still obtain reliable parameter estimation in multi source scenarios.

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  • Received:
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  • Online: June 05,2024
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