Target Localization Using Multiple UAVs with Sensor Fusion via Sigma-Point Kalman Filtering

Author(s):  
Gregory Plett ◽  
Pedro DeLima ◽  
Daniel Pack
Navigation ◽  
2008 ◽  
Vol 55 (3) ◽  
pp. 167-177 ◽  
Author(s):  
YONG LI ◽  
CHRIS RIZOS ◽  
JINLING WANG ◽  
PETER MUMFORD ◽  
WEIDONG DING

2016 ◽  
Vol 88 (6) ◽  
pp. 791-798
Author(s):  
Xiaogang Wang ◽  
Wutao Qin ◽  
Yuliang Bai ◽  
Naigang Cui

Purpose Penetrator plays an important role in the exploration of Moon and Mars. The navigation method is a key technology during the development of penetrator. To meet the high accuracy requirements of Moon penetrator, this paper aims to propose two kinds of navigation systems. Design/methodology/approach The line of sight of vision sensor between the penetrator and Moon orbiter could be utilized as the measurement during the navigation system design. However, the analysis of observability shows that the navigation system cannot estimate the position and velocity of penetrator, when the line of sight measurement is the only resource of information. Therefore, the Doppler measurement due to the relative motion between penetrator and the orbiter is used as the supplement. The other option is the relative range measurement between penetrator and the orbiter. The sigma-point Kalman Filtering is implemented to fuse the information from the vision sensor and Doppler or rangefinder. The observability of two navigation system is analyzed. Findings The sigma-point Kalman filtering could be used based on vision sensor and Doppler radar or laser rangefinder to give an accurate estimation of Moon penetrator position and velocity without increasing the payload of Moon penetrator or decreasing the estimation accuracy. However, the simulation result shows that the last method is better. The observability analysis also proves this conclusion. Practical implications Two navigation systems are proposed, and the simulations show that both systems can provide accurate estimation of states of penetrator. Originality/value Two navigation methods are proposed, and the observability of these navigation systems is analyzed. The sigma-point Kalman filtering is first introduced to the vision-based navigation system for Moon penetrator to provide precision navigation during the descent phase of Moon penetrator.


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