AEROTECH V: Progressive Aerospace Research
Paper Title Page
Traditionally, Kalman Filter is used for the purpose of mixing several input signals and extracting a more reliable output, which greatly benefits aircraft navigation. This paper considers a fusion of four sensor systems: Global Positioning System (GPS), accelerometer, gyroscope and magnetometer. The resultant device, known as Starfish Main Tracking Unit (MTU), is a Flight Data Monitoring (FDM) / Tracking System equipment that uses General Packet Radio Service (GPRS) / Iridium / ICS (Internet Communications Services), which provides low cost telemetry as well as multiple solutions for global flight following and flight data transfer between aircraft and ground. Users from ground are able to monitor their fleet, configure their systems and also generate various flight reports from a single web-based interface, named the Starfish Fleet Management system. This developed system complements the Black Box by downloading limited aircraft data to the ground, provides real time tracking and assist in Search and Rescue (SAR) mission.
This paper presents an overview of the research activities performed to develop a new scaled variant of the Laser Obstacle Avoidance and Monitoring (LOAM) system for small-to-medium size Unmanned Aircraft (UA) platforms. This LOAM variant (LOAM+) is proposed as one of the non-cooperative sensors employed in the UA Sense-and-Avoid (SAA) system. After a brief description of the LOAM system architecture, the mathematical models developed for obstacle avoidance and calculation of alternative flight path are presented. Additionally, a new formulation is adopted for defining the uncertainty volumes associated with the detected obstacles. Simulation case studies are carried out to evaluate the performances of the avoidance trajectory generation and optimisation algorithms, which demonstrate the ability of LOAM+ to effectively detect and avoid fixed low-level obstacles in the intended path.