Efficient Multi-Source Localization in Near-Field Using only Angular Domain MUSIC
Mehdi Haghshenas, Aamir Mahmood, Mikael Gidlund

TL;DR
This paper introduces a novel angular domain MUSIC-based method for near-field multi-source localization that significantly reduces computational complexity while maintaining high accuracy, outperforming existing modified algorithms.
Contribution
A new angular variation-based approach that localizes near-field sources efficiently without extensive grid searches, reducing complexity by over 370 times.
Findings
Outperforms Modified MUSIC in mean absolute error
Achieves accuracy comparable to standard MUSIC
Reduces computational complexity drastically
Abstract
The localization of multiple signal sources using sensor arrays has been a long-standing research challenge. While numerous solutions have been developed, signal space methods like MUSIC and ESPRIT have gained widespread popularity. As sensor arrays grow in size, sources are frequently located in the near-field region. The standard MUSIC algorithm can be adapted to locate these sources by performing a 3D search over both the distance and the angles of arrival (AOA), including azimuth and elevation, though this comes with significant computational complexity. To address this, a modified version of MUSIC has been developed to decouple the AoA and distance, enabling sequential estimation of these parameters and reducing computational demands. However, this approach suffers from reduced accuracy. To maintain the accuracy of MUSIC while minimizing complexity, this paper proposes a novel…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Speech and Audio Processing · Direction-of-Arrival Estimation Techniques
