PHD filtering with target amplitude feature

Daniel Clark, Branko Ristić, Ba N. Vo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)


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 languageEnglish
Title of host publicationProceedings of the 11th International Conference on Information Fusion, FUSION 2008
Publication statusPublished - 2008
Event11th International Conference on Information Fusion - Cologne, Germany
Duration: 30 Jun 20083 Jul 2008


Conference11th International Conference on Information Fusion
Abbreviated titleFUSION 2008


  • Multi-object estimation
  • PHD filters
  • Target amplitude feature
  • Tracking


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