Outlier-Robust Student’s-t-based IMM-VB Localization for Manned Aircraft Using TDOA Measurements

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 27
  • Download : 0
This article proposes a novel outlier-robust localization algorithm that is based on time difference of arrival measurements at an airport for multilateration surveillance. An outlier-robust filtering scheme is derived based on Student's-t-distribution, where the state, a scale matrix, and a degree of freedom parameter are estimated simultaneously using variational Bayesian (VB) inference. An interacting multiple model (IMM) filter with different system models is implemented to handle the multimodal dynamics of the aircraft, yielding the IMM-VB algorithm. Specifically, the likelihood function is newly derived using VB inference for the combination procedure in the proposed IMM-VB algorithm. The experimental results obtained from a flight test using a commercial aircraft at an airport demonstrate that the proposed IMM-VB algorithm has better localization accuracy and robustness to outlier measurements than the existing state-of-the-art approaches.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2020-06
Language
English
Article Type
Article
Citation

IEEE-ASME TRANSACTIONS ON MECHATRONICS, v.25, no.3, pp.1646 - 1658

ISSN
1083-4435
DOI
10.1109/TMECH.2020.2982009
URI
http://hdl.handle.net/10203/274712
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0