State Estimation of Multisensor With Out-of-Order Measurements

Networked control systems, facilitating state estimation through wireless multisensor data transmission, encounter challenges with spatial out-of-order issues, where data transmitted to the fusion center lack identifiable sources. This scenario, analogous to post office boxes receiving letters without addresses, complicates state estimation and affects system accuracy and reliability. To address this, we explore two spatial out-of-order scenarios, focusing on enhancing state estimation precision. For the random out-of-order scenario, characterized by unpredictable sensor data sequences, we propose an accumulative measurement approach and introduce two algorithms to restore data order, thereby improving state estimation accuracy. In the fixed out-of-order scenario, where a consistent but unknown pattern exists, our two algorithms efficiently restore measurement order within a limited time frame. Numerical examples and simulations substantiate the effectiveness of our methods, confirming their utility in maintaining accurate system state estimation.