Abstract：A distributed robust moving horizon estimation method is proposed for distributed network systems with random packet loss. Each node in the system can transmit data over the network to its neighbors, and when a packet is lost it uses Zero-order hold data to compensate for the measurements. Based on moving horizon principle, sensor node transforms the state estimation problem into a quadratic optimization problem in a fixed window by using the local measurement data and the data from the adjacent nodes, the performance index is fused with the method of scalar weighted linear minimum variance. The method guarantees the consistency of the system and reduces the calculation time while the accuracy of the results is guaranteed. Finally, the stability of the estimator is analyzed and compared with other estimation methods in simulation. The results show that this method has better effect.
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