An adaptive Gaussian sum algorithm for radar tracking
Review articleOpen access

AbstractIn this paper, we propose a new radar tracking algorithm based on the Gaussian sum filter. To alleviate the computational burden associated with the Gaussian sum filter, we have developed a new systematic and efficient way to approximate a non-Gaussian and measurement-dependent function by a weighted sum of Gaussian density functions and we have also suggested a way to alleviate the growing memory problem inherited in the Gaussian sum filter. Our method is compared with the extended Kalman filter (EKF) and the converted measurement Kalman filter (CMKF) and it is shown to be more accurate in term of position and velocity errors.

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