Abstract: For the time delay difference tracking estimation methods based on particle filter in wireless sensor network(WSN) , the key issue is to generate an accurate proposal distribution for particle filter. An time delay difference estimation algorthm based on improved unscented particle filter (IUPF) is proposed to overcome the degeneracy phenomenon of particles. The least square method is used to achive the initial target position, and then the unscented particle filter (UPF) and Gauss-Newton rule are used to incorporate the most current observations and provide more accurate importance density function for the particle filter by introducing a scaled correction factor．Finally, IUPF is applied to the time delay difference localization estimation methods in WSN. The simulation results show that, when the particle number is limited, the proposed algorithm can improves the target tracking accuracy and achieve faster convergence speed under non-Gauss noise environment in WSN.

Key words: information processing technology, wireless sensor network, particle filter, unscented Kalman filter, time delay difference