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Hypersonic glide vehicles(HGVs) are launched by a solid booster and glide through the atmosphere at high speeds. HGVs will be important means for rapid long-range delivery in the future. Given that the glide is unpowered, the initial glide conditions(IGCs) are crucial for flight. This paper aims to find the optimal IGCs to improve the maneuverability and decrease the constraints of HGVs. By considering the IGCs as experiment factors, we design an orthogonal table with three factors that have five levels each by using the orthogonal experimental design method. Thereafter, we apply the Gauss pseudospectral method to perform glide trajectory optimization by using each test of the orthogonal table as the initial condition. Based on the analytic hierarchy process, an integrated indicator is established to evaluate the IGCs, which synthesizes the indexes of the maneuverability and constraints. The integrated indicator is calculated from the trajectory optimization results. Finally, optimal IGCs and valuable conclusions are obtained by using range analysis, variance analysis, and regression analysis on the integrated indicator.
Hypersonic glide vehicles (HGVs) were launched by a solid booster and glide through the atmosphere at high speeds. HGVs will be important for rapid long-range delivery in the future. Given that the glide is unpowered, the initial glide conditions (IGCs) are crucial for flight. This paper aims to find the optimal IGCs to improve the maneuverability and decrease the constraints of HGVs. By considering the IGCs as experiment factors, we design an orthogonal table with three factors that have five levels each by using the orthogonal experimental design method. After, we apply the Gauss pseudospectral method to perform glide trajectory optimization by using each test of the orthogonal table as the initial condition. Based on the analytic hierarchy process, an integrated indicator is established to evaluate the IGCs, which synthesizes the indexes of the maneuverability and constraints. The integrated indicator is calculated from the trajectory optimization results. Finally, optimal I GCs and valuable estimates are obtained by using range analysis, variance analysis, and regression analysis on the integrated indicator.