Range-Independent TDOA Localization Using Stepwise Accuracy Enhancement Under Speed Uncertainty

被引：3
|
作者：
Liu, Ying [1 ]
Chen, Cheng [1 ]
Wang, Yingmin [1 ]
Liu, Chenxi [2 ]
机构：
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Peoples R China
[2] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Peoples R China
来源：
IEEE SIGNAL PROCESSING LETTERS | 2023年 / 30卷
基金：
中国国家自然科学基金;
关键词：
Constrained quadratic optimization (QCQP); modified polar representation (MPR); source localization; time difference of arrival (TDOA); MAXIMUM-LIKELIHOOD; PROPAGATION SPEED; POSITION; DIFFERENCE; ALGORITHM;
D O I：
10.1109/LSP.2023.3320574
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This study proposes a stepwise accuracy enhancement (SAE) method for jointly estimating signal propagation speed, near-field position, and far-field direction-of-arrival (DOA) without requiring prior source range knowledge. Time difference of arrival (TDOA) methods excel at near-field localization but are limited in the far field by the thresholding effect. The modified polar representation (MPR) framework mitigates this limitation by unifying near and far field localization. However, previous MPR-based studies assumed known propagation speed, often impractical. SAE overcomes this by treating propagation speed as an unknown parameter to be concurrently estimated with source location. SAE formulates this joint estimation as a quadratically constrained quadratic optimization (QCQP) problem, then mitigates the parameter estimation bias by minimizing the impact of TDOA measurement errors. Simulations validate the effectiveness of SAE for joint estimation irrespective of source range, achieving the Cramer-Rao lower bound (CRLB) in small noise.
引用
收藏
页码：1372 / 1376
页数：5
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