An adaptive sensor-switching framework for urban UAS navigation

Abstract

A robust and high-integrity navigation system is required for supporting Unmanned Aircraft System (UAS) operations in dense urban environments. Global Navigation Satellite System (GNSS) provides the primary means of navigation in civil aviation for manned and unmanned aircraft. GNSS however has failure modes that might be exacerbated in urban environments, leading to loss of navigation data or significant performance degradations. This paper presents a performance-based sensor switching strategy that allows fulfilling UAS navigation requirements in areas where GNSS is unavailable or exhibits degraded performance. An error analysis of GNSS is accomplished to inform the design of a performance evaluation module capable of predicting and assessing in real-time the current UAS navigation performance. In an integrated multi-sensor architecture based on GNSS (primary positioning sensor), Inertial Navigation System (INS) and Vision-Based Navigation (VBN), Adaptive Boolean Decision Logics (ABDL) are implemented to prioritise the various available navigation sensors to maintain the required level of performance. The designed architecture was tested in a virtual UAS test-bed to determine points at which sensor switching could be initiated. An UAS flight in an urban environment was simulated, along with different modes of individual sensor loss and degradation. The designed functionalities are targeted to address the challenging navigation performance requirements emerging in the UAS Traffic Management (UTM) context, enabling seamless and robust operation of UAS in the event of intermittent sensor accuracy, availability, continuity and integrity.