Grid Design and Simulation Analysis of Airspace Raster Based on Optimized Ant Colony Algorithm

With the sustainable development of information technology, digital earth construction has become a popular trend. To integrate drone technology with advanced information technology, this paper explores the standardization and digitalization of airspace, introducing this concept into the design of drone flight routes. We optimize ant colony algorithm by proposing a new global pheromone initialization rule and enhancing the concentration of information elements in the best routes found in the solution set, aiming to better utilize information elements to guide high-quality routes. Simulation experiments demonstrate that utilizing the optimized ant colony algorithm proposed in this paper reduces the average path length by 7.6% and decreases the average iteration count by 52% compared to conventional ant colony algorithm path planning. These simulations clearly confirm the criticality of temporal attribute raster in airspace for optimizing flight routes.