The target tracking method based on censoring and quantization is proposed in the resource-constrained wireless sensor networks. Both the quantized innovations and the information conveyed by missing data due to data censoring are used to estimate the state of the target. Each local sensor maintains a cubature Kalman filter(CKF) to perform the data censoring. The fusion center runs an auxiliary particle filter(APF). To save the energy and bandwidth of the node, the innovations of the selected data are quantized and transmitted to the fusion center. The fusion center makes use of the information contained in the missing data which leads to the improvement of the estimation accuracy. The simulation results show the effectiveness of the proposed method.