Target tracking in wireless sensor networks using particle filter with quantized innovations

Due to the bandwidth constraint of wireless sensor networks, there can be physical limitations in the communication links from sensors back to fusion center, or between sensors. In such cases, local data quantization/compression is not only a necessity, but also an integral part of the design of the sensor networks. In this paper, a target tracking approach using particle filter with quantized innovations in wireless sensor networks is proposed. The posterior Cramer-Rao lower bound for quantized innovation information received by fusion center is also given. The simulation results show the good performance of our proposed tracking approach. With a moderate small number of particles sampled at each step, we found that the tracking performance of particle filter is much better than the EKF, especially when the emitted power of each sensor is small.