To estimate the state of a maneuvering target in sensor networks, an interacting multiple model quantized unscented Kalman filter (IMM-QUKF) algorithm is proposed. In order to save the communication bandwidth, the measurement data of sensors are sent to the remote local estimator after probability quantization. Considering the error introduced by the quantization mechanism, an improved unscented Kalman filter algorithm is designed and combined with the interacting multiple model algorithm to obtain the local estimation. Numerical simulation results show that the algorithm has good tracking effect for maneuvering target.