This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.
|Translated title of the contribution||Mobility tracking in cellular networks with sequential Monte Carlo filters|
|Title of host publication||2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||107 - 114|
|Number of pages||8|
|Publication status||Published - Jul 2005|
|Event||8th International Conference on Information Fusion - Philadelphia, PA, United States|
Duration: 1 Jul 2005 → …
|Conference||8th International Conference on Information Fusion|
|Period||1/07/05 → …|
Bibliographical noteRose publication type: Conference contribution
Sponsorship: This research is supported by the the UK MOD Data and Information
Fusion Defence Technology Center and in part by the
Bulgarian Foundation for Scientific Investigations under grants I-
1202/02 and 1-1205/02.
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- mobility tracking
- Monte Carlo methods
- wireless networks
- hybrid systems
- Singer model