Abstract
A particle filter based on the similarity of the observation path is presented. When the likelihood has a bimodal nature, the particle filter leads to more accurate state estimates than SIR, APF, RPF and GPF.
| Original language | English |
|---|---|
| Pages (from-to) | 1275-1277 |
| Number of pages | 3 |
| Journal | Electronics Letters |
| Volume | 44 |
| Issue number | 21 |
| DOIs | |
| Publication status | Published - 2008 |
| Externally published | Yes |