Landing Risk Evaluation of Carrier-Based Aircraft Based on BP Neural Network

To realize quantitative forecast of carrier-based aircraft landing risk, this paper proposes a risk evaluation method implement the state description based on BP neural network, with "Wave-Off Surplus Distance: WOSD" as reference index. According to the establishment of wave-off system with integrated control of military power and fuzzy elevator, the WOSD is defined with reference of wave-off envelope division for "Ramp-Strike Risk". The burden of neural network training is reduced by establishment of "State Risk Modeling Area: SRMA" based on limit wave-off envelope, finally the quantitative expression of "Ramp-Strike Risk" in any flight states is realized through the design of BP neural network approaching risk evaluation function. Simulation results show that the outputs of BP network model designed basically accord with the expected ones, and the design of risk-evaluation method is feasible. This method can predict the "Ramp-Strike Risk" in any flight states of carrier-based airplane, in addition provide early-warning and auxiliary rectification for safe landing.