Collaborative maneuvering target tracking in wireless sensor network with quantized measurements

Maneuvering target tracking in wireless sensor network (WSN) with quantized measurements is investigated. The measurement in each local sensor is quantized by uniform quantization scheme and then transmitted to a fusion center (FC). To estimate the state of the target in the FC, the quantized messages are first fused in a weighted average way. Then interactive multiple-model (IMM) scheme using sigma-point Kalman filtering (SPKF) is employed. Focuses are on tradeoff between bandwidth of each sensor and the global tracking accuracy. By performing a change of variable and Lagrange technique, the closed-form solution to the optimization problem for bandwidth scheduling is given, where the mean square error (MSE) incurred by weighted average fusion is minimized subject to a constraint on the total energy consumption. Simulation results reveal that the proposed scheme performs very closely to the clairvoyant IMM-SPKF that based on the analog-amplitude measurements, while obtaining average communication energy saving up to 51.2% and computational burden reduction 31%.