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Iterative Implementation Method for Robust Target Localization in a Mixed Interference Environment
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AI
DOI：10.1109/TGRS.2021.3131327.png)
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Abstract
En 中文
For the problem of target localization under the multipath propagation environment, the existing methods are mainly restricted to the limited prior information of complex reflections, especially when the target is embedded in a mixed interference environment. They may suffer from performance degradation due to the shortage of target classification ability. To address this problem, we propose a target localization method based on iterative implementation with semiunitary constraint and eigen-decomposition technique, where a practical propagation scenario based on the spherical Earth model is considered. Compared to the previous works, the proposed method can automatically distinguish a real target from the mixed interference environment with improved localization accuracy. Neither additional decorrelation preprocessing nor prior information of the dynamic scenario is required. Both simulations and real data experiments validate the effectiveness and robustness of the proposed method.
Keywords:
Location awareness
Interference
Earth
Mathematical models
Radio frequency
Iterative methods
Direction-of-arrival estimation
Complex multipath propagation
direction-of-arrival (DOA) estimation
mixed interference
semi-unitary constraint
target classification and localization
Journal
IF:
8.6
Papers:
2.1W
Citations:
10.7W