Background
The Air Force is utilizing Unmanned Aerial Vehicles (UAVs) at an ever in-
creasing pace. Small autonomous vehicles have sparked great interest in the military
by providing an inexpensive system that increases capabilities and prevents placing
personnel in dangerous situations. Autonomous platforms that °y have a unique ap-
peal. They can traverse large distances quickly and provide a ird's eye view" of
the battlespace. Utilizing multiple vehicles enhances mission accomplishment with
redundancy, robustness, and increased coverage when compared to a single platform.
This research explores operating multiple UAVs for surveillance.
Multi-UAV surveillance holds many advantages over the other surveillance op-
tions in terms of proximity (close or far), speed (fast or slow), responsiveness, cost,
and overall personnel risk. Manned surveillance is close and responsive but slow and
places personnel at risk, traditional aircraft are fast and reasonably close but are ex-
pensive and also place personnel at risk. Space surveillance allows access to denied
areas but is very expensive, limited by the orbit for timing and placement, and far
from the target. Multi-UAV surveillance can reduce or remove personnel risk, be close
to the target, provide persistence over the target, and can cost very little compared
to manned aircraft and space options. Advances in the miniaturization of electron-
ics aided this interest in UAVs. As cost and size decreased, capability increased for
surveillance and autonomous technology. Consequently, research and development
blossomed in both academia and the aerospace industry.
The Air Force Institute of Technology (AFIT) has conducted many UAV re-
search projects, and vigorously continues to this day. The research conducted herein
continues an ongoing project at AFIT that focuses on utilizing UAVs for surveillance
and target engagement missions. To ¯ll the void in data for small aircraft, AFIT's re-
search began in 2006 with the work of Nidal Jodeh [8] modelling a 9.16 foot wingspan
radio controlled model airplane, the Sig Rascal, retro¯tted with an autopilot. The
stability and payload capacity of this airframe made it ideal for UAV research. Since
the Sig Rascal became the primary demonstration aircraft, Jodeh's model became
the base for many following projects. One UAV application focused on tracking and
engaging a moving target with on-board video. At AFIT, this application became
known as the Fleeting Target Program." The problem was broken up into creating a
path to the target in real time (Pathmaker) [19], °ying the vehicle to the target using
video feedback (Cursor On Target) [20], and integrating the hardware and software
into a usable package (Fleeting Target Controller) [17]. The research described herein
is the next iteration of the Fleeting Target Program.
For the current e®ort, the emphasis of research shifted away from target detec-
tion and engagement when Air Force Research Lab (AFRL) received an urgent need
request from the war¯ghter to develop a route surveillance capability. AFRL was
tasked to deliver a prototype system capable of monitoring many miles of road and
revisiting any point at ¯xed intervals [2]. The proposed system consists of multiple
UAVs with day and night sensors, a ground station with semi-autonomous control of
the UAVs, and an anomaly detection system. The primary purpose was to surveil
routes ahead of convoys to minimize risk to transportation operations. This need
became the primary drive for this research.
The Air Force is utilizing Unmanned Aerial Vehicles (UAVs) at an ever in-
creasing pace. Small autonomous vehicles have sparked great interest in the military
by providing an inexpensive system that increases capabilities and prevents placing
personnel in dangerous situations. Autonomous platforms that °y have a unique ap-
peal. They can traverse large distances quickly and provide a ird's eye view" of
the battlespace. Utilizing multiple vehicles enhances mission accomplishment with
redundancy, robustness, and increased coverage when compared to a single platform.
This research explores operating multiple UAVs for surveillance.
Multi-UAV surveillance holds many advantages over the other surveillance op-
tions in terms of proximity (close or far), speed (fast or slow), responsiveness, cost,
and overall personnel risk. Manned surveillance is close and responsive but slow and
places personnel at risk, traditional aircraft are fast and reasonably close but are ex-
pensive and also place personnel at risk. Space surveillance allows access to denied
areas but is very expensive, limited by the orbit for timing and placement, and far
from the target. Multi-UAV surveillance can reduce or remove personnel risk, be close
to the target, provide persistence over the target, and can cost very little compared
to manned aircraft and space options. Advances in the miniaturization of electron-
ics aided this interest in UAVs. As cost and size decreased, capability increased for
surveillance and autonomous technology. Consequently, research and development
blossomed in both academia and the aerospace industry.
The Air Force Institute of Technology (AFIT) has conducted many UAV re-
search projects, and vigorously continues to this day. The research conducted herein
continues an ongoing project at AFIT that focuses on utilizing UAVs for surveillance
and target engagement missions. To ¯ll the void in data for small aircraft, AFIT's re-
search began in 2006 with the work of Nidal Jodeh [8] modelling a 9.16 foot wingspan
radio controlled model airplane, the Sig Rascal, retro¯tted with an autopilot. The
stability and payload capacity of this airframe made it ideal for UAV research. Since
the Sig Rascal became the primary demonstration aircraft, Jodeh's model became
the base for many following projects. One UAV application focused on tracking and
engaging a moving target with on-board video. At AFIT, this application became
known as the Fleeting Target Program." The problem was broken up into creating a
path to the target in real time (Pathmaker) [19], °ying the vehicle to the target using
video feedback (Cursor On Target) [20], and integrating the hardware and software
into a usable package (Fleeting Target Controller) [17]. The research described herein
is the next iteration of the Fleeting Target Program.
For the current e®ort, the emphasis of research shifted away from target detec-
tion and engagement when Air Force Research Lab (AFRL) received an urgent need
request from the war¯ghter to develop a route surveillance capability. AFRL was
tasked to deliver a prototype system capable of monitoring many miles of road and
revisiting any point at ¯xed intervals [2]. The proposed system consists of multiple
UAVs with day and night sensors, a ground station with semi-autonomous control of
the UAVs, and an anomaly detection system. The primary purpose was to surveil
routes ahead of convoys to minimize risk to transportation operations. This need
became the primary drive for this research.
