Multi-Dimensional Parameter Estimation in Polarimetric ULA with Cross-Distribution Dipole Pairs

Author:

Zhong TiantianORCID,Tao Haihong,Lan Lan

Abstract

This paper investigates the estimation of parameters—including the elevation angle, azimuth angle, polarization auxiliary angle, polarization phase difference, frequency and range of near-field sources in a Polarimetric Uniform Linear Array (P-ULA) with defective electromagnetic vector sensors. The cross-distribution dipole pairs are alternately placed in the xoy plane and yoz plane, respectively, and the whole array is divided into two subarrays, where subarray 1 consists of all of the dipole pairs placed in the xoy plane, while the dipole pairs placed in yoz plane are gathered in subarray 2. Specifically, the polarization auxiliary angle and the polarization phase difference, as well as the elevation and azimuth angles of the sources, are firstly estimated based on the Fourth-Order Cumulant (FOC) matrix in each subarray. Moreover, a decoupling method is developed to obtain the elevation and azimuth. Subsequently, the frequency and range are estimated based on the FOC matrix. Then, the parameter pair matching method is performed in order to match the pairs. Finally, an analysis of the Cramér-Rao Bound (CRB) is provided, and comparisons of the root mean square error with respect to the different input signal-to-noise ratios and number of snapshots, among different estimation methods, are implemented in the environment of additive white gaussian noise. The simulation results are provided in order to verify the effectiveness and feasibility of the proposed method for multi-dimensional parameter estimation.

Funder

National Natural Science Foundation of China

Innovation Project of Science and Technology Commission of the Central Military Commission

National Key Laboratory Foundation

China Postdoctoral Science Foundation

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A RARE-MUSIC Algorithm for Near-Field Target Localization with COLD-FDA-MIMO Radar;2023 IEEE International Radar Conference (RADAR);2023-11-06

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