This paper presents the cooperative strategies for salvo attack of multiple missiles based on the classical proportional navigation（PN） algorithm.The three-dimensional（3-D） guidance laws are developed in a quite simple formulation that consists of a PN component for target capture and a coordination component for simultaneous arrival.The centralized algorithms come into effect when the global information of time-to-go estimation is obtained, whereas the decentralized algorithms have better performance when each missile can only collect information from neighbors.Numerical simulations demonstrate that the proposed coordination algorithms are feasible to perform the cooperative engagement of multiple missiles against both stationary and maneuvering targets.The effectiveness of the 3-D guidance laws is also discussed.
为解决信息不完备条件下的无人作战飞机(UCAV,Unmanned Combat Air Vehicle)战术决策问题,提出一种基于灰色区间关联的UCAV自主战术决策方法.依照作战任务要求选取决策要素,建立UCAV决策推理的规则库.构建不完备信息模型,并基于灰色区间关联理论给出UCAV战术决策模型;设计冲突消解算法,有效解决不完备信息导致的推理失效问题.仿真实例模拟了决策过程,验证了该方法在解决UCAV战术决策问题上的可行性和在化解规则匹配冲突方面的有效性.仿真结果表明,该方法能够应对决策要素不确定性较大的情况,并给出合理的战术行为推理结果.
Abstract This paper presents the novel use of the particle swarm optimization （PSO） to generate the end-to-end trajectory for hypersonic reentry vehicles in a quite simple formulation. The velocity- dependent bank angle profile is developed to reduce the search space of unknown parameters based on the constrained PSO algorithm. The path constraints are enforced by setting the fitness function to be infinite on condition that the particles violate the maximum allowable values. The PSO algo- rithm also provides a much easier means to satisfy the terminal conditions by adding penalty terms to the fitness function. Furthermore, the approximate reentry landing footprint is fast constructed by incorporating an interpolation model into the standardized bank angle profiles. Numerical sim ulations demonstrate that the PSO method is a feasible and flexible tool to generate the end-to-end trajectory and landing footprint for hypersonic reentry vehicles.
The reentry trajectory optimization for hypersonic vehicle（HV）is a current problem of great interest.Some complex constraints,such as waypoints for reconnaissance and no-fly zones for threat avoidance,are inevitably involved in a global strike mission.Of the many direct methods,Gauss pseudospectral method（GPM）has been demonstrated as an effective tool to solve the trajectory optimization problem with typical constraints.However,a series of diffculties arises for complex constraints,such as the uncertainty of passage time for waypoints and the inaccuracy of approximate trajectory near no-fly zones.The research herein proposes a multi-phase technique based on the GPM to generate an optimal reentry trajectory for HV satisfying waypoint and nofly zone constraints.Three kinds of specifc breaks are introduced to divide the full trajectory into multiple phases.The continuity conditions are presented to ensure a smooth connection between each pair of phases.Numerical examples for reentry trajectory optimization in free-space flight and with complex constraints are used to demonstrate the proposed technique.Simulation results show the feasible application of multi-phase technique in reentry trajectory optimization with waypoint and no-fly zone constraints.
