Anisotropic Estimator Design for Time Varying System with Measurement Dropouts

In this paper, the anisotropy-based filtering problem is studied for a class of linear discrete time varying finite horizon systems with measurement data packet dropout. The measurement packet dropout phenomenon is considered to be random, and is modeled as binary switching sequence of independent identically distributed scalar random variables. The estimator is designed to satisfy the upper bound constraint on the anisotropic norm chosen to quantitatively describe the performance index of the input-to-error system over the finite horizon. Given the measurements and estimates of the system outputs, the filter parameters are parameterized by means of the solution to a set of discrete linear (with a minor exception of one) matrix inequalities.