A unified approach to cooperative and non-cooperative sense-and-avoid

Cooperative and non-cooperative Sense-and-Avoid (SAA) capabilities are key enablers for Unmanned Aircraft Vehicle (UAV) to safely and routinely access all classes of airspace. In this paper state-of-the-art cooperative and non-cooperative SAA sensor/system technologies for small-to-medium size UAV are identified and the associated multi-sensor data fusion techniques are introduced. A reference SAA system architecture is presented based on Boolean Decision Logics (BDL) for selecting and sorting non-cooperative and cooperative sensors/systems including both passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). After elaborating the SAA system processes, the key mathematical models associated with both non-cooperative and cooperative SAA functions are presented. The analytical models adopted to compute the overall uncertainty volume in the airspace surrounding an intruder are described. Based on these mathematical models, the SAA Unified Method (SUM) for cooperative and non-cooperative SAA is presented. In this unified approach, navigation and tracking errors affecting the measurements are considered and translated to unified range and bearing uncertainty descriptors, which apply both to cooperative and non-cooperative scenarios. Simulation case studies are carried out to evaluate the performance of the proposed SAA approach on a representative host platform (AEROSONDE UAV) and various intruder platforms. Results corroborate the validity of the proposed approach and demonstrate the impact of SUM towards providing a cohesive logical framework for the development of an airworthy SAA capability, which provides a pathway for manned/unmanned aircraft coexistence in all classes of airspace

Towards localisation with Doppler radar

In this thesis the author introduces a novel method for Geo Localisation via Doppler Radar. The area of research is in the three dimensional space using amplitude and magnitude measurements. Geo Localisation in mobile applications is a useful technology that enables monitoring and gathering information about objects of interest

Aeronautical engineering: A continuing bibliography with indexes (supplement 318)

This bibliography lists 217 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1995. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Next generation flight management systems for manned and unmanned aircraft operations - automated separation assurance and collision avoidance functionalities

The demand for improved safety, efficiency and dynamic demand-capacity balancing due to the rapid growth of the aviation sector and the increasing proliferation of Unmanned Aircraft Systems (UAS) in different classes of airspace pose significant challenges to avionics system developers. The design of Next Generation Flight Management Systems (NG-FMS) for manned and unmanned aircraft operations is performed by addressing the challenges identified by various Air Traffic Management (ATM) modernisation programmes and UAS Traffic Management (UTM) system initiatives. In particular, this research focusses on introducing automated Separation Assurance and Collision Avoidance (SA&CA) functionalities (mathematical models) in the NG-FMS. The innovative NG-FMS is also capable of supporting automated negotiation and validation of 4-Dimensional Trajectory (4DT) intents in coordination with novel ground-based Next Generation Air Traffic Management (NG-ATM) systems. One of the key research contributions is the development of a unified method for cooperative and non-cooperative SA&CA, addressing the technical and regulatory challenges of manned and unmanned aircraft coexistence in all classes of airspace. Analytical models are presented and validated to compute the overall avoidance volume in the airspace surrounding a tracked object, supporting automated SA&CA functionalities. The scientific basis of this approach is to assess real-time measurements and associated uncertainties affecting navigation states (of the host aircraft platform), tracking observables (of the static or moving object) and platform dynamics, and translate them to unified range and bearing uncertainty descriptors. The SA&CA unified approach provides an innovative analytical framework to generate high-fidelity dynamic geo-fences suitable for integration in the NG-FMS and in the ATM/UTM/defence decision support tools