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Estimation of a Moving Vehicle’s Position and Orientation Using Probabilistic Data Association

[+] Author Affiliations
Yu Lei, Guang Lu

Tulane University

Paper No. IMECE2005-81234, pp. 493-502; 10 pages
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Dynamic Systems and Control, Parts A and B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 0-7918-4216-9 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME


This paper presents a computationally efficient algorithm for real-time vehicle tracking, by detecting the two taillights using a laser scanning radar (LIDAR) sensor. It is assumed that the two targets are constrained by fixed known separation distance 2l. To reject clutter, a Probability Data Association (PDA) based algorithm is proposed. The algorithm first predicts the orientation of the vehicle and the position of one of the two targets. Then it uses a two-dimensional PDA filter to estimate the position of this target. All the measurements whose distance from the estimated target is close to 2l are converted into orientation angles. This is followed by a one-dimensional PDA filter, which probabilistically combines calculated angles to estimate the orientation of the vehicle. Simulation results show significant improvement by this algorithm over other methods, in terms of orientation tracking.

Copyright © 2005 by ASME



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