Interpolation particle filter for tracking with out-of-sequence measurements

In multisensor tracking system, the center processor receives the out-of-sequence measurements (OOSMs) because of communication time delays. An improved particle filter for filtering out-of-sequence measurements with arbitrary lag was proposed. The interpolation filter is used to generate the proposal distribution for particle filter. The proposal distributions integrate the most current observation, thus greatly improving the filter performance. The detailed implementation steps of OOSM processing scheme based on OOSM-interpolation particle filter (OOSM-IPF) is deduced. The performance estimates of the OOSM-IPF obtained for ground moving target indicator (GMTI) is compared with similar performance estimates obtained from the OOSM extend Kalman filter (OOSM-EKF). Simulation results show that the tracking performance of OOSM-IPF is much improved than other schemes.