Path Planning by Unmanned Air Vehicles for Engaging an Integrated Radar Network
AIR FORCE RESEARCH LAB WRIGHT-PATTERSON AFB OH
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A growing concept in the field of unmanned air vehicles UAVs is the idea of using a team of cooperating vehicles to participate in electronic countermeasures, defined here as jamming or deception techniques. A UAV may be tasked to engage a radar using noise jamming to mask its radar return or that of another vehicle. Similarly, a UAV may be assigned to deceive a radar by directing a delayed signal toward the victim radar, which has the effect of producing a radar phantom perceived by the radar as an object at a false range andor bearing. Previous work focused on generating a set of waypoints for the UAV to follow in order the countermeasures to be successful. This paper addresses the path planning required to meet the temporal, spatial, and UAV flight dynamics constraints associated with employing these electronic countermeasures, especially between jamming and deception activities. The UAVs are assigned simplified flight dynamics and performance constraints in two-dimensions, assuming constant altitude flight over a flat-surfaced earth. All tracking radars are given simplified detection properties. A single UAV is provided a pre-determined series of goal positions. The goal positions may lie along a countermeasures pre-planned course or they may be established such that the UAV moves from the final waypoint of one countermeasure to the starting point of the next countermeasure. Therefore the UAV must autonomously navigate to a given goal position, subsequently perform a simple, associated task countermeasure, if required, then navigate the next goal position in the series. The will be required to arrive at these waypoints with a specific state, depending on the task at hand. Algorithms for optimal autonomous navigation of this nature were formulated to effectively guide the UAVs to their goal positions to meet the necessary temporal and spatial requirements.
- Flight Control and Instrumentation
- Operations Research