Mobile Sensors for Target Tracking via Modified Particle Filter

• Main Authors: Wen Cheng Chen, 陳文正
• Other Authors: Luke K. Wang
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/75526855703780405712

碩士 === 國立高雄應用科技大學 === 電機工程系 === 97 === We propose an estimation algorithm for location tracking and dynamic motion model of mobile units in sensor network. Estimate the trajectories of moving targets by collecting the information from sensors measurements, and assume that sensors can be randomly moving within a limited radius r at every time step. The sensor nearest to the target is chosen to supply the distance measurements. Our proposed tracking algorithm is based on modified particle filter (MPF). MPF means PF with varying particle numbers. For a nominal PF algorithm, particle number is fixed and we defined the nominal one to be the so called fixed particle filter (FPF). Estimation of mobility states, which consist of position, velocity, and acceleration of the target, are accomplished through the processing of modified particle filter using the measurements through the radar sensors. The simulation results show what we proposed, mobility tracking and the associated algorithms, have excellent convergence properties, stability, and less computationally demanding that can be applied in a variety of sensor network applications.