Name
Abstract | ||
|---|---|---|
The cardinality balanced multi-target multi-Bernoulli (CBMeMBer) recursion approximates the multi-target posterior density by a multi-Bernoulli probability density, and is based on the standard measurement model that targets are points. In reality, there are many other measurement models substantially different from this. This paper represents part of our theoretical studies on a CBMeMBer filter for nonstandard multitarget measurement models. The main contribution of our work lies in the establishment of the measurement-update equations for a CBMeMBer filter based on the unresolved-target model with continuous target number. |
Year | Venue | Keywords |
|---|---|---|
2014 | Fusion | target tracking,cbmember filters,cbmember filter,standard measurement,nonstandard multitarget measurement,measurement-update equations,nonstandard targets,multibernoulli probability density,unresolved targets,continuous target number,random finite set (rfs),cardinality balanced multitarget multibernoulli recursion,multitarget posterior density,recursive filters,multi-target tracking,probability,vectors,clutter,computational modeling,mathematical model |
Field | DocType | Citations |
Computer science,Artificial intelligence,Machine learning | Conference | 1 |
PageRank | References | Authors |
0.35 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guanghua Zhang | 1 | 1 | 0.69 |
| Feng Lian | 2 | 14 | 3.54 |
| Chongzhao Han | 3 | 446 | 71.68 |