Motion-encoded Gravitational Search Algorithm for moving target search using UAVs

In this paper, a new algorithm called Motion Coding Gravitational Search Algorithm (MGSA) is proposed to find a moving target using a unmanned aerial vehicles (UAVs). Using the laws of physics and the properties of the earth, each dimension has its own equation of motion based on the type of variable. Many traditional exploratory methods can not achieve the desired solution in high-dimensional spaces to search for a moving target. The optimization process of the gravitational search algorithm, which is based on the gravitational interaction between particles, the dependence on the distance and the relationship between mass values, and the fit calculation, make this algorithm unique. In this paper, the proposed MGSA algorithm is proposed to solve the path complexity challenge problem in order to find the moving target through motion coding using UAVs. A set of particles in the path of search for the target will reach a near-optimal solution through the gravity constant, weight factor, force and distance, which evolved with many search scenarios in a GSA algorithm. This coded method of motion makes it possible to preserve important particle properties, including the optimum global motion. The results of the existing simulation show that the proposed MGSA improves the detection performance by 12% and the time performance by 1.71 times compared to APSO. It works better.