Gaussian mixture importance sampling function for unscented SMC-PHD filter
The unscented sequential Monte Carlo probability hypothesis density (USMC-PHD) filter has been proposed to improve the accuracy performance of the bootstrap SMC-PHD filter in cluttered environments. However, the USMC-PHD filter suffers from heavy computational complexity because the unscented inform...
| Main Authors: | , , |
|---|---|
| Format: | Journal Article |
| Published: |
Elsevier BV
2013
|
| Online Access: | http://hdl.handle.net/20.500.11937/56017 |