کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
562329 | 1451948 | 2016 | 15 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Multi-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles Multi-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles](/preview/png/562329.png)
• A new sensor-selection solution for multi-target tracking.
• No need of prior knowledge of clutter distribution.
• No need of any knowledge of detection profile.
• Sequential Monte-Carlo implementation is presented.
• Works substantially faster than traditional methods.
A new sensor-selection solution within a multi-Bernoulli-based multi-target tracking framework is presented. The proposed method is especially designed for the general multi-target tracking case with no prior knowledge of the clutter distribution or the probability of detection, and uses a new task-driven objective function for this purpose. Step-by-step sequential Monte Carlo implementation of the method is presented along with a similar sensor-selection solution formulated using an information-driven objective function (Rényi divergence). The two solutions are compared in a challenging scenario and the results show that while both methods perform similarly in terms of accuracy of cardinality and state estimates, the task-driven sensor-selection method is substantially faster.
Journal: Signal Processing - Volume 119, February 2016, Pages 28–42