Abstract: Strong tracking filtering (STF) sets small threshold to judge filtering divergence leading to fading factor with high probability, which causes excessive regulation of the filtering gain and makes the state estimation curve lack smoothness. By analyzing the operation mechanism of STF, improved STF (ISTF) is proposed. The proposed algorithm reduces probability of misjudging filter divergence by appropriately increasing the threshold. It determines the softening factor to suit different dimensions of the measurement equation, and thus avoids the disadvantages of the previous methods that determine the softening factor according to experiences. Simulation indicates that ISTF can maintain filtering accuracy and estimation smoothness, and is robust against sudden changes in the system state, showing its feasibility and effectiveness.

Key words: strong tracking filtering (STF), robustness, fading factor, softening factor