An Improved Planar Approximation Localization Method in Distributed Airborne Radars

In distributed airborne radar systems, the linear target localization method using time of arrival (TOA) is extensively studied due to its excellent robustness and simplicity in computation. Quadratic or higher-order terms related to range are disregarded in conventional linear methods, which results in compromised localization accuracy under high noise conditions. Considering the position uncertainty of moving platforms and a more realistic prior variance in target position estimation, an improved planar approximation algorithm is proposed, which refines target location iteratively. The spherical equations are approximated in each iteration as planar equations involving the current estimated target position. The error introduced by the planar approximation is recalculated and compensated for, enabling high-accuracy target location. In simulations, the proposed algorithm can reduce the average number of iterations by approximately 20%, and achieves a localization accuracy improvement of over 5 dB when the standard deviation of distance measurement error exceeds 1 km.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10889607
Citations
2
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
1.46

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article

An Improved Planar Approximation Localization Method in Distributed Airborne Radars

Demin Huang, Zehua Yu, Jinshan Ding, Liwu Wen et al.
2 citations
Indoor and Outdoor Localization Technologies
1.46
article

An Improved Planar Approximation Localization Method in Distributed Airborne Radars

Demin Huang, Zehua Yu, Jinshan Ding, Liwu Wen, Jing Li
article en
2 citations

Abstract

In distributed airborne radar systems, the linear target localization method using time of arrival (TOA) is extensively studied due to its excellent robustness and simplicity in computation. Quadratic or higher-order terms related to range are disregarded in conventional linear methods, which results in compromised localization accuracy under high noise conditions. Considering the position uncertainty of moving platforms and a more realistic prior variance in target position estimation, an improved planar approximation algorithm is proposed, which refines target location iteratively. The spherical equations are approximated in each iteration as planar equations involving the current estimated target position. The error introduced by the planar approximation is recalculated and compensated for, enabling high-accuracy target location. In simulations, the proposed algorithm can reduce the average number of iterations by approximately 20%, and achieves a localization accuracy improvement of over 5 dB when the standard deviation of distance measurement error exceeds 1 km.

Xidian University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Affordable and clean energy
Openalex Percentile: Top 19%
Indoor and Outdoor Localization Technologies
1.46
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