NEW PROPOSED ALGORITHM FOR SINGLE SENSOR MULTI- TARGET TRACKING IN DENSE ENVIRONMENTS | ||||
| International Conference on Aerospace Sciences and Aviation Technology | ||||
| Article 53, Volume 10, 10th International Conference On Aerospace Sciences & Aviation Technology, May 2003, Page 793-804 PDF (1.76 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asat.2013.24699 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| A. H. El Bardawieny; K. A. El Barbary; A. Mamdouh; A. Mansour | ||||
| Egyptian Armed Forces. | ||||
| Abstract | ||||
| A significant problem in multi-target tracking (MU) is the observation-to-track data association. An observation is a signal received, from a target or background clutter, which provides positional information. If an observation is incorrectly associated with a track, that track could diverge and prematurely terminate or cause other tracks to also diverge. Mainly, there are two basic approaches used in data association: the nearest neighbor (NN) approach and the all-neighbors (AN) approach. In the NN approach, the track is updated by at most one observation but in the AN approach, weights are assigned for reasonable observations and a weight centroid of those observations is used to update the track. This paper introduces two techniques belonging to the AN approach: the probabilistic data association (PDA) technique and a new proposed technique. Examples are given to compare the PDA algorithm with the proposed algorithm for data association. | ||||
| Keywords | ||||
| Multi-target Tracking; data association | ||||
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