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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%.