Mission scheduling of multi-sensor collaborative observation for space surveillance network  

作　　者：LONG Xi CAI Weiwei YANG Leping WANG Tianyu 

机构地区：[1]College of Aerospace Science and Engineering,National University of Defense Technology,Changsha 410073,China [2]School of Traffic and Transportation Engineering,Central South University,Changsha 410073,China

出　　处：《Journal of Systems Engineering and Electronics》2023年第4期906-923,共18页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(11802333);the Scientific Research Program of the National University of Defense Technology(ZK19-31)。

摘　　要：With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally important.The multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and high-conflict complex combinatorial optimization problem that is nondeterministic polynomial(NP)-hard.This research establishes a sub-time window constraint satisfaction problem(STWCSP)model with the objective of maximizing observation profit.Considering the significant effect of genetic algorithms(GA)on solving the problem of resource allocation,an evolution heuristic(EH)algorithm containing three strategies that focus on the MCOS problem is proposed.For each case,a task scheduling sequence is first obtained via an improved GA with penalty(GAPE)algorithm,and then a mission planning algorithm(heuristic rule)is used to determine the specific observation time.Compared to the model without sub-time windows and some other algorithms,a series of experiments illustrate the STWCSP model has better performance in terms of total profit.Experiments about strategy and parameter sensitivity validate its excellent performance in terms of EH algorithms.

关 键 词：multi-sensor observation resource scheduling subtime window evolution heuristic algorithm 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程] V52[航空宇航科学与技术—人机与环境工程]