TY - JOUR
T1 - A Gaussian-sum based cubature Kalman filter for bearings-only tracking
AU - Leong, Pei H.
AU - Arulampalam, Sanjeev
AU - Lamahewa, Tharaka A.
AU - Abhayapala, Thushara D.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84876127973&partnerID=8YFLogxK
U2 - 10.1109/TAES.2013.6494405
DO - 10.1109/TAES.2013.6494405
M3 - Article
SN - 0018-9251
VL - 49
SP - 1161
EP - 1176
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 2
M1 - 6494405
ER -