Path Planning and Target Allocation for a Group of Cooperative UAVs in a Noise Jamming Mission

In this research we are looking for finding a way to suppress radars of an integrated air defense system with the help of a group of cooperative UAVs using noise jamming. The purpose of this research is to propose a target allocation and path planning algorithm so that they can fly closer to their target without the risk of being detected. Objective of optimization is to reduce usage of resources including operation time, increase noise level in radars’ receivers and reduce probability of UAVs being detected by search radars. probability of detection depends on relative position and attitude of UAVs and each radar and the number of UAVs jamming each radar. To simplify the computational complexity of solving the path planning problem on a continuous domain, we discretize airspace and use a honeycomb sampling method instead of a uniform sampling method. This discretization reduces the path planning to a constrained shortest path problem over a finite graph. In this method we sample more points in regions where the optimal path is more likely to deviate from a straight-line. The target allocation problem too can be turned into a finite graph and solved using pulse algorithm. Eventually with the help of Computer simulation, the effectiveness of the proposed algorithms is examined in a typical mission of cooperative UAVs jamming an integrated air defense system.