scholarly journals Robust adaptive multi‐target tracking with unknown measurement and process noise covariance matrices

2021 ◽  
Author(s):  
Peng Gu ◽  
Zhongliang Jing ◽  
Liangbin Wu
Keyword(s):  
Target Tracking ◽  
Covariance Matrices ◽  
Process Noise ◽  
Multi Target Tracking ◽  
Noise Covariance ◽  
Robust Adaptive

scholarly journals Strong Tracking PHD Filter Based on Variational Bayesian with Inaccurate Process and Measurement Noise Covariance

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1126
Author(s):  
Zhentao Hu ◽  
Linlin Yang ◽  
Yong Jin ◽  
Han Wang ◽  
Shibo Yang
Keyword(s):  
Real Time ◽  
Gaussian Mixture ◽  
Measurement Noise ◽  
Tracking Accuracy ◽  
Process Noise ◽  
Probability Hypothesis Density ◽  
Measurement Noise Covariance ◽  
Multi Target Tracking ◽  
Noise Covariance ◽  
Fading Factor

Assuming that the measurement and process noise covariances are known, the probability hypothesis density (PHD) filter is effective in real-time multi-target tracking; however, noise covariance is often unknown and time-varying for an actual scene. To solve this problem, a strong tracking PHD filter based on Variational Bayes (VB) approximation is proposed in this paper. The measurement noise covariance is described in the linear system by the inverse Wishart (IW) distribution. Then, the fading factor in the strong tracking principle uses the optimal measurement noise covariance at the previous moment to control the state prediction covariance in real-time. The Gaussian IW (GIW) joint distribution adopts the VB approximation to jointly return the measurement noise covariance and the target state covariance. The simulation results show that, compared with the traditional Gaussian mixture PHD (GM-PHD) and the VB-adaptive PHD, the proposed algorithm has higher tracking accuracy and stronger robustness in a more reasonable calculation time.

Multi-target tracking with an event-based vision sensor and a partial-update GMPHD filter

2019 ◽  
Vol 2019 (13) ◽  
pp. 127-1-127-7
Author(s):  
Benjamin J. Foster ◽  
Dong Hye Ye ◽  
Charles A. Bouman
Keyword(s):  
Target Tracking ◽  
Vision Sensor ◽  
Multi Target Tracking ◽  
Event Based

Shared-memory parallel multi-target tracking

2009 ◽  
Vol 28 (9) ◽  
pp. 2303-2305
Author(s):  
Xiao-gang WANG ◽  
Xiao-juan WU ◽  
Xin ZHOU ◽  
Xiao-yan ZHANG
Keyword(s):  
Target Tracking ◽  
Shared Memory ◽  
Multi Target Tracking
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