Subcommittee C – AVIONICS AND SYSTEM INTEGRATION
6.1 “TCAS Performance Monitoring” – Carl Jezierski, FAA
The Traffic Alert and Collision Avoidance System (TCAS) is an airborne system developed by the FAA in the 1980’s that operates independently from the ground-based Air Traffic Control (ATC) system. As TCAS has matured, modifications to the collision avoidance logic were made to optimize its performance. Further evolution is expected as we move into the NextGen environment. To satisfy the FAA Safety Management System (SMS) regarding the introduction of new systems, a need has been identified to monitor TCAS operations and performance via capture and analysis of resolution advisory (RA) related communications. This paper describes the TCAS RA Monitoring System (TRAMS), a new distributed ground-based system, consisting of 20 remote sites, that captures airborne RA communications and associated surveillance data in real-time and transmits this information daily to a central facility for analysis and archive. The overall goal of TRAMS is to enable analysis of TCAS performance and facilitate changes in the airspace.
6.2 “Robust Navigation and Attitude Determination Systems for Unmanned and Micro Aerial Vehicle Applications” – Demoz Gebre-Egziabher, Department of Aerospace Engineering & Mechanics University of Minnesota, Twin Cities Campus
Appropriately instrumented Uninhabited Aerial Vehicles (UAVs) or Micro Aerial Vehicles (MAVs) are being considered for use in many civilian remote sensing applications. Accurate attitude determination (i.e., orientation in three-dimensional space) and navigation is an indispensable requirement for these applications. Constraints on sensor size, weight and power consumption, however, makes the use of traditional attitude determination solutions impractical in these UAV and MAV applications. Conventional GPS solutions are also not sufficient for operations in urban canyons or indoor environments.
In this presentation, issues associated with the design of attitude determination and navigation systems for miniature aerial vehicles are discussed. The focus will be on algorithms and simulation tools used to design multi-sensor attitude determination and navigation systems. The tradeoffs involved in mechanizing these algorithms using different sensor fusion schemes will be discussed. It will be shown that system observability (hence, accuracy), simplicity, weight and power consumption are competing attributes when designing these attitude determination and navigation systems for UAV and MAV applications. Finally, simulation tools based on the open source flight simulator software FlightGear will be discussed and demonstrated.
6.3 “Micro Air Vehicle Flight in GPS-Denied Environments: Planning in
Information Space” – Nicholas Roy, MIT
Unmanned air vehicles (UAVs) rely heavily on accurate knowledge of their position for decision-making and control. As a result, considerable investment has been made towards improving the availability of global positioning infrastructure, including utilizing satellite-based GPS system and developing algorithms to leverage existing RF signals such as WiFi. However, most indoor environments and many parts of the urban canyon remain without access to external positioning systems. Autonomous UAVs thus currently have limited ability to fly through these areas.
I will describe the navigation system for a quadrotor helicopter flying autonomously without GPS using a laser range-finder capable of estimating position, yaw angle and altitude information by sensing the environment. I will also describe the Belief Roadmap algorithm and show how it can be used to plan trajectories through the environment that incorporate a predictive model of the limited field of view of the sensor, allowing the planner to accurately plan trajectories through indoor environments.