On strong tracking Kalman filter based on forgetting factor dynamic optimization

摘要: The fixed forgetting factor of state estimation error variance matrix in the strong tracking Kalman filter algorithm with suboptimal multi-fading factors is very important. When it takes a value too small, role current information will be emphasized excessively. As result, possible to cause time variant fading regulate overly. Conversely, weakened relatively. In fact, optimum performance can not achieved either case. This paper proposed an method on basis fuzzy factor. regulates according rules, by which logic controller monitoring similarity coefficient and variance. And then adjusts multiple improve precision algorithm. effectiveness proved simulation results.