Probability hypothesis density filtering with sensor networks and irregular measurement sequences
The problem of multi-object tracking with sensor networks is studied using the probability hypothesis density filter. The sensors are assumed to generate signals which are sent to an estimator via parallel channels which incur independent delays. These signals may arrive out-of-order (out-of-sequence), be corrupted or even lost due to, e.g., noise in the communication medium and protocol malfunctions. In addition, there may be periods when the estimator receives no information. A closed-form,...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of Fusion 2010|
|01_Bishop_Probability_hypothesis_density_2010.pdf||250.76 kB||Adobe PDF||Request a copy|
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