Update with out-of-sequence measurements

Abstract

Out-of-sequence measurements (OOSMs) can create difficulties for discrete time filtering. A number of procedures have been developed for extending the Kalman filter to handle these different types of delay. A common characteristic of these methods is the policy of always incorporating, or fusing delayed measurements at the time they finally become available. In this paper, we proposed a selective threshold (ST) to determine the value of the OOSMs, and based on a proposed information filter (ST-IF) to update the estimate with the useful OOSMs. By the simulation, we show that selective fusion can reduce computational costs while maintaining a good performance.