Name
Abstract | ||
|---|---|---|
The principal difficultly in tracking in an urban terrain is the presence of multipaths. However by using proper modelling and signal processing techniques these multipaths can be used favourably. In this paper we consider a more robust model of the urban terrain by not assuming exact wall locations but rather allowing for small deviations. This is achieved by introducing a random phase shift to the radar equation. A MCMC based particle filter which uses an adaptive kernel to improve the mobility of the Markov Chain is proposed with supporting simulation results. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6638884 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
Markov processes,Monte Carlo methods,adaptive filters,particle filtering (numerical methods),radar signal processing,radar tracking,random processes,MCMC particle filter,Markov chain,adaptive kernel,multipath environment,radar equation,random phase shift,small deviations,urban terrain tracking,wall locations,MCMC,kernel,multipath,particle filter | Radar,Mathematical optimization,Markov process,Radar tracker,Markov chain Monte Carlo,Computer science,Particle filter,Markov chain,Adaptive filter,Kernel adaptive filter | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.40 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bentarage Sachintha Karunaratne | 1 | 4 | 1.30 |
| Mark R. Morelande | 2 | 6 | 1.86 |
| Bill Moran | 3 | 141 | 23.49 |