An Improved Interacting Multiple Model Algorithm Used in Aircraft Tracking

There are some problems in traditional interacting multiple model algorithms (IMM) when used in target tracking systems. For instance, the mode transition matrix is inaccurate and cannot be determined when the sojourn times are not known. To solve these problems, an optimal mode transition matrix IMM (OMTM-IMM) algorithm is proposed in this paper. The linear minimum variance theory is used to calculate the mode transition matrix which depends on the continuous system state rather than the sojourn times in this algorithm. Moreover, the correlation of the subfilter is considered; hence the covariance matrices are utilized to compute mode transition matrix. In this algorithm, the model probability is defined as a diagonal matrix which is combined with the filters outputs; thus the effects produced by each state can be distinguished. Finally, to verify the superiority of the new algorithm, the theoretical proof and simulation results are given. They show that the OMTM-IMM algorithm can improve the tracking accuracy and can be utilized in the complex environment.