Abstract
The problem of maneuvering target tracking in the presence of glint noise is addressed in this paper. The main challenge in this problem stems from its nonlinearity and non-Gaussianity. In this work, the nonlinear Gaussian mixture Kalman filter (NL-GMKF) is applied to the problem of maneuvering target tracking in the presence of glint. The algorithm is based on the Gaussian mixture model for the posterior state vector distribution. The tracking performance of the NL-GMKF is evaluated and compared to the interacting multiple modeling (IMM) with extended Kalman filter (EKF), particle filter (PF) and the EKF. It is shown that the NL-GMKF outperforms other tested methods.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
