Real-time object tracking based on an adaptive transition model and extended Kalman filter to handle full occlusion

2019 ◽  
Vol 36 (4) ◽  
pp. 701-715 ◽  
Author(s):  
Mohammad Zolfaghari ◽  
Hossein Ghanei-Yakhdan ◽  
Mehran Yazdi
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Transition Model ◽  
Full Occlusion

Real-Time Signal Denoising Algorithm in Wheel Force Transducer

2014 ◽  
Vol 615 ◽  
pp. 244-247
Author(s):  
Dong Wang ◽  
Guo Yu Lin ◽  
Wei Gong Zhang
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Unscented Kalman Filter ◽  
Force Transducer ◽  
Time Signal ◽  
Signal Denoising ◽  
Observation Function ◽  
Simulation Results ◽  
Wheel Force Transducer

The wheel force transducer (WFT) is used to measure dynamic wheel loads. Unlike other force sensors, WFT is rotating with the wheel. For this reason, the outputs and the inputs of the transducer are nonlinearly related, and traditional Kalman Filter is not suitable. In this paper, a new real-time filter algorithm utilizing Quadrature Kalman Filter (QKF) is proposed to solve this problem. In Quadrature Kalman Filter, Singer model is introduced to track the wheel force, and the observation function is established for WFT. The simulation results illustrate that the new filter outperforms the traditional Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF).

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