A NEW MANEUVERING TARGET TRACKING ALGORITHM WITH INPUT ESTIMATION

The paper proposes a new tracking algorithm that will treat the target acceleration as a nonrandom term, and consists of a constant velocity filter, an input estimator and a maneuver detector implemented in parallel. This method has the same advantages as the two-stage Kalman estimator which requires lesser amounts of computation and provides an even better performance when compared with an augmented state Kalman filter. The proposed method also uses a better tuning parameter and removes a difficulty in implementation of the two-stage Kalman estimator. The results show that the new filter is a better alternative to the two-stage Kalman estimator on tracking maneuvering targets.

• Supplemental Notes:
  • Full conference proceedings available on CD-ROM.
• Corporate Authors:

  Federal Transit Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Zhou, K
  • Wang, X
  • Tomizuka, M
  • Zhang, W B
  • Chan, C Y
• Conference:
  • Technical Information on Transit IVI Projects
  • Location: Las Vegas, Nevada
  • Date: 2002-10-28 to 2002-10-29
• Publication Date: 2002

Language

• English

Media Info

• Pagination: 6p

Subject/Index Terms

• TRT Terms: Algorithms; Detectors; Estimating; Intelligent vehicles; Kalman filtering; Maneuvering; Tracking systems; Transit buses; Velocity measurement
• Identifier Terms: Intelligent Vehicle Initiative
• Subject Areas: Operations and Traffic Management; Public Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 00936269
• Record Type: Publication
• Files: TRIS, USDOT
• Created Date: Jan 3 2003 12:00AM