Concepts for Automatic Positioning of Unmanned Aerial Vehicles to Optimize Time Difference of Arrival Geolocation Performance, 16-9375

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Principal Investigators
Brad Brown
Ben Abbott

Inclusive Dates:  01/01/03 - 06/30/04

Background - Unmanned Aerial Vehicles (UAVs) are in use by various United States military and Department of Defense agencies. Their uses range from surveillance to weapon platforms, and the size and flight characteristics of the various platforms vary greatly. Some UAVs resemble typical fixed wing aircraft, while others resemble hovercraft and parafoils. Most UAV platforms are relatively small and have fairly severe weight and power restrictions on any payloads. However, this disadvantage is countered by the ability of the UAV to loiter in hostile areas that are inaccessible to conventional aircraft. This loitering ability is especially useful for signal intelligence applications where the aircraft may need to remain on station for hours to collect the required information. In the past, most UAVs have flown pre-programmed flight paths or have allowed for limited flight path changes via ground station controllers. However, ground station controllers are not ideally suited for positioning UAVs to optimize geolocation performance. This internal research project explores the processing algorithm requirements for automatically repositioning UAV assets to optimize geolocation accuracy via Time Difference of Arrival (TDOA) methods.

Approach - The approach to this problem consists of four main efforts. The first effort is to define exactly what accuracy is required for various scenarios and determine what timing accuracy is required to support these scenarios. The second effort is to develop algorithms to determine where the platforms should be positioned for each successive TDOA measurement. The third effort is numerical simulation of the previously mentioned algorithms. The fourth part of the effort is a limited analysis of actual data collected by UAV platforms against a target transmitter.

Accomplishments - This research was performed as a multidivisional effort between the Signal Exploitation and Geolocation Division (16) and the Automation and Data Division (10). Division 16's SIGINT and TDOA expertise was combined with Division 10's knowledge of DARPA programs and expertise in software development and scheduling and path planning algorithms. Support from the Aerospace Electronics and Information Technology Division in the area of UAV flight control knowledge was also useful.

During this effort, an initial solution framework to the problem was developed, consisting of four main efforts. The first effort defined the accuracy required for various scenarios and determined what timing accuracy is required to support these scenarios. The second effort developed algorithms to determine where the platforms should be positioned for each successive TDOA measurement. The third effort evaluated numerical simulation of the fore-mentioned algorithms. The fourth part of this effort was a limited analysis of actual data collected by Vanderbilt UAV platforms against a target transmitter. The result of this project is an algorithm suitable for optimizing the positioning of a fleet of UAVs coordinated as a TDOA geolocation system.

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