基于粒子群算法的低轨重点卫星雷达协同探测任务规划方法OA北大核心CSTPCD

In order to improve the observation efficiency of orbital determination,imaging,target characteristic measurement and so on,a task scheduling method is proposed for radar observation of high-threat satellites situated in low earth orbit(LEO).Com-pared with the priority-oriented scheduling method,this method enables all satellites to be observed with a given frequency,satisfy-ing constraints such as radar's field of view,time window,transition time,etc.The factors of radar detection such as elevation an-gle,slant,and radar cross-section are utilized to construct the weight when defining the objective function based on time length of observation.Particle swam optimization(PSO)algorithm is employed to achieve the maximum total time length or quickest accom-plishment of observation.Simulation is conducted to verify the effectiveness of the proposed method.Two notional ground radars are used to observe 30 high-threat LEO satellites for 24 h～72 h.Results show that:all satellites are observed without missing and under the given conditions,and the maximum total time length and quickest accomplishment of observation are 18 622 s and 15 h 16 min,respectively(scenario time:24 h).Furthermore,when using the weighted objective function,it tends to obtain a larger elevation angle and smaller slant during the whole observation process,while the total time length of observation is basically con-sistent with that of using the non-weighted one.