Average linear least squares positioning: Preliminary results
Michler O, Khalaf-Allah M (2020)
Publication Type: Conference contribution, Original article
Publication year: 2020
Publisher: IEEE Computer Society
Book Volume: 2020-October
Pages Range: 163-166
Conference Proceedings Title: Proceedings International Radar Symposium
Event location: Warsaw
ISBN: 9788394942151
DOI: 10.23919/IRS48640.2020.9253911
Abstract
In this paper, a linear least squares (LLS) estimator to solve the range-based positioning problem is investigated. We show that the LLS estimation can use a subset of or the whole available information. The former yields many single set (SS) solutions and the later yields the full set (FS) solution. We also show that the FS solution can refine the SS solutions. An experiment with phase of arrival (PoA) measurements demonstrates that the FS and SS solutions have different accuracies. The FS solution corresponds to the average of the SS solutions. The FS solution was utilized to reduce the SS positioning errors by about 8-28%.
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Germany (DE)How to cite
APA:
Michler, O., & Khalaf-Allah, M. (2020). Average linear least squares positioning: Preliminary results. In Proceedings International Radar Symposium (pp. 163-166). Warsaw, PL: IEEE Computer Society.
MLA:
Michler, Oliver, and Mohamed Khalaf-Allah. "Average linear least squares positioning: Preliminary results." Proceedings of the 21st International Radar Symposium, IRS 2020, Warsaw IEEE Computer Society, 2020. 163-166.
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