Abstract:

To deal with the defects and the target tracking precision problem in the interacting multiple model (IMM) algorithm for multiple maneuvering targets tracking, a Gaussian mixture cardinalized probability hypothesis density (GMCPHD) filter algorithm based on variable structure multiple model (VSMM) is proposed. Compared with the IMM algorithm which only considers the fixed model collection, the GMCPHD filter algorithm is superior. Utilizing the adaptive and time varying which both are the characteristics of VSMM algorithm, this approach reaches the goal that the model collection matching the target motion model can be selected in certain time. In addition, the GMCPHD filter algorithm not only avoids the data association problem, but also propagates the radix distribution while propagates PHD function by using Gaussian distribution. Finally, a radar is chosen as the sensor and some simulation experiments on tracking a variety of maneuvering target are done. The simulation results prove that the VSMM algorithm is superior to IMM algorithm for multiple maneuvering targets tracking and illustrate that the VSMMGMCPHD filter algorithm can improve the maneuvering target tracking precision and reduce the tracking error.