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Cooperative Localization Based on Robust GPS and Radar Fusion for Multiple Aerial Vehicles

Xiaojie Zhao, Gang Wang*, and Shuzhi Sam Ge
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.732-742, 2017

Abstract : "This paper presents a localization framework for multiple aerial vehicles (AVs) based on sensor fusion of global positioning system (GPS) and the identification friend-or-foe (IFF) Radar system. The IFF-Radar play two roles: firstly, it detects the angle and the range between two AVs, and thus the path between the two vehicles can be modeled as a curve. Secondly, it detects which AV helps form the above curve, and receives the corresponding GPS information from the friend vehicle. Through the cooperation of the multiple AVs, not only GPS can work well with fewer satellites due to the block of canyon environments, but also differential GPS (DGPS) performance can be achieved when the place is beyond the coverage of the DGPS. Theoretical analysis shows that two GPS satellites are sufficient to obtain the location information with the help of two or more friend vehicles, and the performance is as accurate as DGPS with the help of two or more friend vehicles. Simulations show that the proposed approach can achieve better localization by the cooperation among multiple aerial vehicles than single aerial vehicle."

Keyword : Differential global positioning system (DGPS), extended Kalman filter (EKF), global positioning system (GPS), sensor fusion.

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