A multi-step optimization method for UAV swarm area coverage based on ant colony algorithm
An ant colony algorithm and area coverage technology, which is applied to the multi-step optimization of area coverage of UAV swarms and track planning problems, to achieve the optimal effect of real-time coverage area
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[0026] refer to figure 1 , is a flow chart of a multi-step optimization method for regional coverage of unmanned aerial vehicles based on an ant colony algorithm of the present invention; wherein the multi-step optimization method for regional coverage of unmanned aerial vehicles based on ant colony algorithm comprises the following steps:
[0027] Step 1. Set up the system simulation environment: first, set the monitoring area S of the UAV group, the feasible flight area A of the UAV group, and the maximum turning angle when each UAV is overloaded during the turning process. more than θ m In the case of , the UAV swarm needs to maximize the coverage of the surveillance area S of the UAV swarm without flying out of the feasible area A of the UAV swarm, θ m Indicates the maximum turning angle of the UAV speed; then, set the airborne radar operating parameters, including the peak power and antenna gain of the airborne radar, and then set the number of UAVs included in the UAV g...
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