Path Planning by Unmanned Air Vehicles for Engaging an Integrated Radar Network

Abstract

A growing concept in the fleld of unmanned air vehicles (UAVs) is the idea of using a team of cooperating vehicles to participate in electronic countermeasures, deflned 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 efiect of producing a radar phantom perceived by the radar as an object at a false range and/or bearing. Previous work focused on generating a set of waypoints for the UAV to follow in order for the countermeasures to be successful. This paper addresses the path planning required to meet the temporal, spatial, and UAV ∞ight dynamics constraints associated with employing these electronic countermeasures, especially between jamming and deception activities. The UAVs are assigned simplifled ∞ight dynamics and performance constraints in two-dimensions, assuming constant altitude ∞ight over a ∞at-surfaced earth. All tracking radars are given simplifled detection properties. A single UAV is provided a pre-determined series of \goal positions. The goal positions may lie along a countermeasure’s pre-planned course or they may be established such that the UAV moves from the flnal 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 to the next goal position in the series. The UAVs will be required to arrive at these waypoints with a speciflc state, depending on the task at hand. Algorithms for optimal autonomous navigation of this nature were formulated to efiectively guide the UAVs to their goal positions to meet the necessary temporal and spatial requirements. Simulations were generated to test the path-planning and control strategies given UAV/radar network scenarios, and overall UAV navigational performance in each simulation was analyzed.