Name
Abstract | ||
|---|---|---|
There exist the low data rate, low detection probability, low measurement precision problem and multi-path effects of ionosphere in the Over the Horizon Radar (OTHR) multi-target tracking. The exponential mixture density probability hypothesis density filter (EMDs-PHDF) based on random finite set (RFS) is proposed. The approach sets a separate PHD filter for each propagation path of ionosphere to predict and update independently. Then the EMDs algorithm is utilized to achieve the global integration of multi-path PHDs, which can effectively utilize all the information of the multi-path, and avoid the number of targets over-estimate problem. The simulation results show that the proposed algorithm can estimate target state and target number accurately for OTHR target tracking. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICInfA.2016.7831837 | 2016 IEEE International Conference on Information and Automation (ICIA) |
Keywords | Field | DocType |
Over the Horizon Radar,Multi-path,Low detection probability,Probability hypothesis density | Mixture distribution,Multi target tracking,Finite set,Radar tracker,Exponential function,Computer science,Algorithm,Data rate,Measurement precision,Over-the-horizon radar | Conference |
ISBN | Citations | PageRank |
978-1-5090-4103-9 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feng Yang | 1 | 18 | 4.42 |
| Hao Chen | 2 | 0 | 0.34 |
| Pengyan Zhang | 3 | 0 | 0.34 |
| Keli Liu | 4 | 0 | 0.34 |