An ADMM approach for elliptic positioning in non-line-of-sight environments

Abstract: Elliptic positioning (EP) has recently emerged as a prevailing subject within localization research, holding significant relevance for a variety of multistatic systems including distributed multiple-input multiple-output radar, sonar, and wireless sensor networks. Mathematically, EP refers to estimating the location of a signal-reflecting/relaying target from the bistatic range (BR) measurements acquired by employing multiple spatially separated transmitters and receivers. BRs, as a specific type of range-based sensor observations, will however be positively biased when non-line-of-sight (NLOS) signal propagation occurs. Such a phenomenon is widespread across various localization scenarios, which can seriously degrade the positioning accuracy if not properly addressed. Through the alternating direction method of multipliers, this contribution introduces a computationally efficient iterative algorithm designed for error-mitigated EP in NLOS environments. In addition to target position coordinates, we incorporate a non-negatively bounded balancing parameter into the formulation and perform joint estimation, thereby achieving NLOS bias error reduction in a simple yet impactful manner. Numerical simulations are conducted to validate the functionality of the presented EP approach in NLOS situations

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
Digital signal processing. - 154 (2024) , 104653, ISSN: 1095-4333

Classification
Elektrotechnik, Elektronik

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2024
Creator
Xiong, Wenxin
He, Jiajun
So, Hing Cheung
Leung, Chi-Sing

DOI
10.1016/j.dsp.2024.104653
URN
urn:nbn:de:bsz:25-freidok-2553677
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:45 AM CEST

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Associated

  • Xiong, Wenxin
  • He, Jiajun
  • So, Hing Cheung
  • Leung, Chi-Sing
  • Universität

Time of origin

  • 2024

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