An Innovative Approach for Data Collection and Handling to Enable Advancements in Micro Air Vehicle Persistent Surveillance
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The success of unmanned aerial vehicles (UAV) in the Iraq and Afghanistan conflicts has led to increased interest in further digitalization of the United States armed forces. Although unmanned systems have been a tool of the military for several decades, only recently have advances in the field of Micro-Electro-Mechanical Systems (MEMS) technology made it possible to develop systems capable of being transported by an individual soldier. These miniature unmanned systems, more commonly referred to as micro air vehicles (MAV), are envisioned by the Department of Defense as being an integral part of maintaining America?s military superiority. As researchers continue to make advances in the miniaturization of flight hardware, a new problem with regard to MAV field operations is beginning to present itself. To date, little work has been done to determine an effective means of collecting, analyzing, and handling information that can satisfy the goal of using MAVs as tools for persistent surveillance. Current systems, which focus on the transmission of analog video streams, have been very successful on larger UAVs such as the RQ-11 Raven but have proven to be very demanding of the operator. By implementing a new and innovative data processing methodology, currently existing hardware can be adapted to effectively present critical information with minimal user input. Research currently being performed at Texas A&M University in the areas of attitude determination and image processing has yielded a new application of photographic projection. By replacing analog video with spatially aware high-resolution images, the present MAV handheld ground control stations (GCS) can be enhanced to reduce the number of functional manpower positions required during operation. Photographs captured by an MAV can be displayed above pre-existing satellite imagery to give an operator a lasting reference to the location of objects in his vicinity. This newly generated model also increases the functionality of micro air vehicles by allowing for target tracking and energy efficient perch and stare capabilities, both essential elements of persistent surveillance.
Goodnight, Ryan David (2009). An Innovative Approach for Data Collection and Handling to Enable Advancements in Micro Air Vehicle Persistent Surveillance. Master's thesis, Texas A&M University. Available electronically from