Antinoise Robustness Scalable Joint Estimation of Frequency and DOA for Sparse Arrays

被引：0
|
作者：
Huang X.-D. [1 ,2 ]
Yang L. [1 ]
Yang M.-K. [1 ]
Huang G.-M. [2 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
[2] Science and Technology on Electronic Information Control Laboratory, Chengdu, 610036, Sichuan
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 01期
关键词：
Antinoise robustness; Direction of arrival estimation; Frequency estimation; Relaxed coprime array; Signal processing; Undersampling;
D O I：
10.3969/j.issn.0372-2112.2019.01.016
中图分类号：
学科分类号：
摘要：
To improve the antinoise robustness of frequency and direction of arrival in the temporal-spatial undersampling case, this paper presents two aspects of improvements. On one hand, in the configuration of sparse array arrangement, this paper constructs a relaxed coprime sparse array consisting of 3 sensors, whose element spacings are configured in terms of TRRNS (Towards Robustness in Residue Number System) reconstruction algorithm; On the other hand, in the design of recovery algorithm, the original CRT (Chinese Remainder Theorem) based algorithm is replaced by the TRRNS algorithm, from which the mechanism of the anti-noise robustness scalable adjustment will be derived and verified by numerical simulations. Compared to the original CRT based joint estimator, the proposed estimator at least achieves 9dB improvement of the SNR threshold without increasing the hardware complexity and system cost, which presents vast applications in radar, remote sensing and other passive sensing fields. © 2019, Chinese Institute of Electronics. All right reserved.
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页码：122 / 128
页数：6
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