A distributed state estimation algorithm based on sensor network is proposed for networked systems with random transmission delays.In order to save communication bandwidth,an adaptive probability quantization mechanism is introduced.Considering the existence of random transmission delays,an improved Unscented Kalman Filter (UKF) algorithm is designed by using the data in the buffer to compensate for the delays.The fast covariance crossing method is used for fusion estimation after local estimation is completed, so as to obtain more accurate state estimation results.In addition,the boundedness of fusion estimation errors is analyzed.The effectiveness of the algorithm is verified by a numerical simulation example.