Kalman filtering with intermittent observations using measurements coding

This paper studies the state estimation problem of a stochastic discrete-time system over a lossy channel. The packet loss is modeled as an independent and identically distributed (i.i.d.) binary process. To reduce the effect of the random packet losses on the stability of the minimum mean square error estimator, we propose a linear coding method on the measurement of the system. In particular, the linear combination of the current and finite previous measurements is to be transmitted to the estimator over the lossy channel. Some necessary and sufficient conditions for the stability of the estimator are established, and the advantage of the linear coding method is exploited.