Fusion and Optimality of Fuze and Seeker Target Detection Information Based on The Neural Networks

摘要

Based on the complementarities of ground-to-air missile fuze and seeker target detection information, the feasibility of their fusion and optimality is analyzed. This paper proposes an multi-layer feed forward neural network OBP (optimal-back-propagation) algorithm, and structures a fusion and optimality model of target detection information. Simulation result shows the detection information can be controlled in the required range well through fusion and optimality, which can reach the requirements for the optimal delay time and the optimal detonation azimuth in high precision.