Reconstruction Model Optimization for Gravity Anomaly along Glide Trajectory

A fast computation scheme and its corresponding reconstruction model for the gravity anomalies along glide trajectories of a hypersonic vehicle are initially proposed. Further, the optimization algorithm for the reconstruction model is developed based on the multi-island genetic algorithm. To reduce the computational scale of optimization, an agent model is established based on the optimal latin hypercube method and RBF neural networks. Simulations indicate that the proposed reconstruction model possesses enough adaptability for multiple cases of involving several no-fly zones. Considering the limitation of the capability for onboard computers, the trajectory precision can be enhanced 10(4) times by taking account into gravity anomalies which are computed based on the reconstruction model. Based on the proposed optimization algorithm, the model with a lightest memory burden on the trajectory precision requirement and the model with a highest trajectory precision on the memory size requirement are both achieved.