Potential applications of skip SMV with thrust engine

摘要

This paper investigates the potential applications of Space Maneuver Vehicles (SMV) with skip trajectory. Due to soaring space operations over the past decades, the risk of space debris has considerably increased such as collision risks with space asset, human property on ground and even aviation. Many active debris removal methods have been investigated and in this paper, a debris remediation method is first proposed based on skip SMV. The key point is to perform controlled re-entry. These vehicles are expected to achieve a trans-atmospheric maneuver with thrust engine. If debris is released at altitude below 80 km, debris could be captured by the atmosphere drag force and re-entry interface prediction accuracy is improved. Moreover if the debris is released in a cargo at a much lower altitude, this technique protects high value space asset from break up by the atmosphere and improves landing accuracy. To demonstrate the feasibility of this concept, the present paper presents the simulation results for two specific mission profiles: descent to predetermined altitude; descent to predetermined point (altitude, longitude and latitude). The evolutionary collocation method is adopted for skip trajectory optimization due to its global optimality and high-accuracy. This method is actually a two-step optimization approach based on the heuristic algorithm and the collocation method. The optimal-control problem is transformed into a nonlinear programming problem (NLP) which can be efficiently and accurately solved by the sequential quadratic programming (SQP) procedure. However, such a method is sensitive to initial values. To reduce the sensitivity problem, genetic algorithm (GA) is adopted to refine the grids and provide near optimum initial values. By comparing the simulation data from different scenarios, it is found that skip SMV is feasible in active debris removal and the evolutionary collocation method gives a truthful re-entry trajectory that satisfies the path and boundary constraints.