Multisensor Detection Alliance Based on Improved Elephant Herding Optimization Algorithm

Aiming at the problems that the elements of the traditional Multi-sensor Detection alliance are not fully considered in the construction of the model, and the population optimization algorithm applied in the detection process of the alliance has many control parameters, weak global optimization ability and slow convergence speed, a detection alliance mathematical model considering the target threat, sensor detection accuracy, sensor energy consumption and constraints is proposed in this paper, Then, basic Elephant Herding Optimization algorithm is improved by alternately using Opposition-based learning strategy (OBL) and sine cosine algorithm (SCA), and applied to the target detection process of sensor detection alliance. Finally, simulation experiments show that the algorithm significantly enhances the global search ability and convergence speed, and verifies the feasibility of the alliance model.