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Full-Text Articles in Engineering
Novel Algorithms For Tracking Multiple Targets, Sheng-Yun Hou, Hsien-Sen Hung, Shun-Hsyung Chang, Jeng-Cheng Liu
Novel Algorithms For Tracking Multiple Targets, Sheng-Yun Hou, Hsien-Sen Hung, Shun-Hsyung Chang, Jeng-Cheng Liu
Journal of Marine Science and Technology
In this paper, two novel angle tracking algorithms are proposed for tracking multiple targets using an array of sensors with known locations. First, we present an extended Kalman particle filter (EKPF) which is capable of determining the direction-of-arrival (DOA) angles using a single snapshot of data during the interval between each time step. The proposed EKPF algorithm combines particle filtering with the extended Kalman filter (EKF) in order to prevent sample impoverishment during its resampling process. Next, we present a robust Kalman filter (RKF) tracking algorithm intended to improve tracking success rates of other existing algorithms for the case of …
Stochastic Stability Of The Discrete-Time Constrained Extended Kalman Filter, Levent Özbek, Esi̇n Köksal Babacan, Murat Efe
Stochastic Stability Of The Discrete-Time Constrained Extended Kalman Filter, Levent Özbek, Esi̇n Köksal Babacan, Murat Efe
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, stability of the projection-based constrained discrete-time extended Kalman filter (EKF) as applied to nonlinear systems in a stochastic framework has been studied. It has been shown that like the unconstrained EKF, the estimation error of the EKF with known constraints on the states remains bounded when the initial error and noise terms are small, and the solution of the Riccati difference equation remains positive definite and bounded. Stability results are verified and performance of the constrained EKF is demonstrated through simulations on a nonlinear engineering example.