Gaussian mixture converted Doppler measurement Kalman filter
Zhengkun Guo, Gongjian Zhou Gongjian Zhou, Rongqing Xu · 2015
A new linear filter, the Converted Doppler Measurement Kalman Filter (CDMKF) has been previously presented to extract nonlinear pseudo-state from converted Doppler measurements (i.e., the product of the range measurements and Doppler measurements). Inherent in this filter is a nonGaussian and more complicated pseudo-states noise, although the pseudo-states evolve linearly in time. A Gaussian mixture estimation algorithm (GM-CDMKF) is developed in this paper to alleviate the deteriorated filtering performance due to the non-Gaussian process noise without too much computational expenses. Monte Carlo simulations are presented to demonstrate the effectiveness of the GMCDMKF.