Distributed Fusion Filter for Discrete-time Stochastic Linear Systems with Unknown Sensor Inputs
Shuli Sun · Science Technology and Engineering · 2008
An unbiased state filter in the linear minimum variance sense is developed for discrete-time stochastic linear systems with unknown sensor inputs and correlated noises,where there is not any prior information for the unknown inputs. When there are multiple sensors,the cross-covariance matrix of filtering errors between any two sensors is derived. Further,the distributed scalar-weighted fusion state filter is given based on the multi-sensor optimal fusion algorithm in the linear minimum variance sense. A simulation example shows the effectiveness.