A novel adaptive lateral reentry guidance algorithm with complex distributed no-fly zones constraints

Aimed at complex distributed no-fly zones avoidance problems, a novel adaptive lateral reentry guidance algorithm is proposed. Firstly, by introducing the improved attractive and repulsive potential fields, an improved artificial potential field method is developed. Combined with the proposed judgment criterion for whether a no-fly zone has been avoided, the proposed improved artificial potential field method effectively solves the reference heading angle determination problem under the constraints of complex distributed no-fly zones. Then, based on the proposed no-fly zone's threat quantitative evaluation method and the reference heading angle determined by the proposed improved artificial potential field method, the heading corridor is improved to increase its sensitivity to the threat changes of the no-fly zones. Finally, for satisfying the requirements of complex distributed no-fly zones avoidance, a novel guidance logic via improved heading corridor is proposed to update the reference heading corridor adaptively in real time according to the threat and constraint changes of the no-fly zones, and the bank reversal logic is employed to control the lateral motion. The simulation results for nominal and dispersed cases indicate that the proposed guidance algorithm has high robustness, stability, and applicability, and is feasible and effective to deal with the complex distributed no-fly zones avoidance problems.