A practical nondiverging filter
TZYH JONG TARN, J. Zaborszky · AIAA Journal · 1970
A Kalmaii filter, and in fact all filters based on the usual approaches, have the troublesome problem that although they are convergent if the models and the statistics of the disturbances are correctly known, divergence can result when such knowledge is not available. This paper describes a method to remedy this problem by weighing past observations by a progressively small number. The result is a filter with an algorithm which differs from the Kalman filter in just one additional multiplication by a fixed scalar at each observation time. Examples document the improvements obtainable with the modified filter.