Herein is presented an efficient nonlinear filtering algorithm called the Gaussian-sum cubature Kalman filter (GSCKF) for the bearings-only tracking problem. It is developed based on the recently proposed cubature Kalman filter and is built within a Gaussian-sum framework. The new algorithm consists of a splitting and merging procedure when a high degree of nonlinearity is detected. Simulation results show that the proposed algorithm demonstrates comparable performance to the particle filter (PF) with significantly reduced computational cost.
A Gaussian-Sum Based Cubature Kalman Filter for Bearings-Only Tracking
IEEE Transactions on Aerospace and Electronic Systems ; 49 , 2 ; 1161-1176
2013-04-01
7088502 byte
Article (Journal)
Electronic Resource
English
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