Abstract
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimation by obtaining more accurate target and false alarm likelihoods. Target amplitude feature is well know to improve data association in conventional tracking filters (such as the PDA, MHT), and results in better tracking performance of low SNR targets. The advantage of using the target amplitude approach is that targets can be identified earlier through the enhanced discrimination between target and false alarms. We illustrate this approach in the context of multiple targets of unknown and different signal to noise ratios in the framework of the Probability Hypothesis Density filter. The simulation results demonstrate the significant improvement in performance particulary in the estimate of the number of targets.
Original language | English |
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Title of host publication | Proceedings of the 11th International Conference on Information Fusion, FUSION 2008 |
DOIs | |
Publication status | Published - 2008 |
Event | 11th International Conference on Information Fusion - Cologne, Germany Duration: 30 Jun 2008 → 3 Jul 2008 |
Conference
Conference | 11th International Conference on Information Fusion |
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Abbreviated title | FUSION 2008 |
Country/Territory | Germany |
City | Cologne |
Period | 30/06/08 → 3/07/08 |
Keywords
- Multi-object estimation
- PHD filters
- Target amplitude feature
- Tracking