Abstract

UAVs have the potential for autonomous airborne remote sensing applications that require rapid response to natural hazards (e.g.. volcano eruptions, earthquakes). As these applications require very accurate positioning, such as airborne Synthetic Aperture Radar, tightly coupled Global Positioning System (GPS) Precise Point Positioning (PPP) Inertial Navigation Systems (INS) are an attractive method to perform real-time aircraft positioning. In particular, PPP can achieve a level of positioning accuracy that is similar to Real-Time Kinematic (RTK) GPS, without the need of a relatively close GPS reference station. However, the PPP method is known to converge to accurate positioning more slowly when compared to RTK, a drawback of PPP that is amplified whenever the receiver platform is faced with GPS challenged environments, such as poor satellite visibility and frequent phase breaks. Unfortunately, these challenging conditions occur more often when the platform being positioned is an aircraft that experiences abrupt changes in attitude. In this paper we present the use of a simulation environment to characterize the position estimation performance sensitivity of PPP/INS through a Monte Carlo analysis that is considered under various conditions, such as: the intensity of multipath errors, the number of phase breaks that occur in a flight, satellite geometry, atmospheric conditions, noise characteristics and grade of the inertial sensor, and accuracy of GPS orbit products.

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