Reduced state estimation with biased and out-of-sequence measurements from multiple sensors

摘要

This invention relates to state estimation after processing time-delayed measurements with unknown biases that may vary arbitrarily in time within known physical bounds. These biased measurements are obtained from systems characterized by state variables and by multidimensional parameters, for which the latter are also unknown and may vary arbitrarily in time within known physical bounds. If a measurement is time-late, apply the measurements to an out-of-sequence filter using a mean square optimization criterion that accounts for all sources of uncertainty and delay time, to produce estimates of the true states of the system. If the measurement is not time-late, apply the measurements to an in-sequence filter using a mean square optimization criterion that accounts for all sources of uncertainty to produce estimates of the true states of the system. The estimates are applied to one of (a) making a decision, (b) operating a control system, and (c) controlling a process.