In this thesis, we investigate a decentralized data fusion system with improved
particle filters for target tracking. In many application areas, it becomes essential
to use nonlinear and non-Gaussian elements to accurately model the underlying
dynamics of a physical system. Particle filters have a great potential for solving
highly nonlinear and non-Gaussian estimation problems, in which the traditional
Kalman filter and extended Kalman filter may generally fail. To improve the tracking
performance of particle filters, initialization of the particles is studied. We
construct an initial state distribution by using least square estimation. In addition,
to enhance the tracking capability of particle filters, representation of target velocity
by another set of particles is considered. We include another layer of particle
filter inside the original particle filter for updating the velocity. In our proposed
architecture, we assume that each sensor node contain a particle filter and there
is no fusion center in the sensor network. Approximated a posteriori distribution
at the sensor is obtained by using the local particle filters with the Gaussian mixture
model (GMM), so that more compact representations of the distribution for
transmission can be obtained. To achieve information sharing and integration, the
GMM-covariance intersection algorithm is used in formulating the decentralized fusion
solutions. Simulation results are presented to illustrate that the performance
of the improved particle filter is better than standard particle filter. In addition,
simulation results of target tracking in the sensor system with three sensor nodes
are given to show the effectiveness and superiority of the proposed architecture.
Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0906109-030910 |
Date | 06 September 2009 |
Creators | Lin, Yu-Tsen |
Contributors | Jiann-Der Lee, Shiunn-Jang Chern, Jieh-Chian Wu, Chin-Der Wann |
Publisher | NSYSU |
Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
Language | Cholon |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906109-030910 |
Rights | campus_withheld, Copyright information available at source archive |
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