Multisensor probabilistic multihypothesis tracking using dissimilar sensors

Details Multisensor probabilistic multihypothesis tracking using dissimilar sensors Multisensor probabilistic multihypothesis tracking using dissimilar sensors

Jun 1997

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997spie.3086..129k&link_type=abstract

Proc. SPIE Vol. 3086, p. 129-138, Acquisition, Tracking, and Pointing XI, Michael K. Masten; Larry A. Stockum; Eds.

Computer Science

Performance

Scientific paper

A difficult problem in multisensor and multi-tracking is that of data association. A multitarget tracking algorithm, probabilistic multi-hypothesis tracking (PMHT), overcomes this problem by estimating the measurement-to-target assignments and the target states simultaneously. We have previously developed two multi-sensor variations of this algorithm, the multi-sensor PMHT and the general multi- sensor PMHT. In this paper, we apply the multi-sensor PMHT algorithm to non-simultaneous radar and optical real data, recorded from a testbed consisting of a radar and optical sensor. Its performance in a multi-target environment is compared to that of a multi-sensor variable update rate Kalman filter.

Affiliated with

Also associated with

No associations

Rating

Multisensor probabilistic multihypothesis tracking using dissimilar sensors does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Multisensor probabilistic multihypothesis tracking using dissimilar sensors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Multisensor probabilistic multihypothesis tracking using dissimilar sensors will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1481560