Subjects: Astronomy submitted time 2024-01-05 Cooperative journals: 《天文学进展》
Abstract： Orbit measurement data collected by a space debris monitoring network is the basis of debris orbit cataloguing. With the vast number of debris objects but limited moni#2;toring facilities, data collection strategy and task programming are the key technologies to bring into full play of monitoring facilities and improve cataloguing capability and accuracy. The monitoring tasks include routine monitoring, important object monitoring and monitor#2;ing of emergent events. For the multi-task scheduling optimization problem of a monitoring network, this paper proposes a linear assignment model and a nonlinear assignment model considering move cost, respectively, in which the monitoring benefit is defined as the ob#2;jective function, and uses the improved LAPJV algorithm and improved 2-opt algorithm to solve them. The optimization experiments with ground-based simulated debris monitoring networks are carried out, in which the improved LAPJV algorithm and 2-opt algorithm have a solution time of 12.051 s and 162.071 s, respectively, and the total benefit is 289 399.07 and 285 333.79, respectively in term of the linear model and the nonlinear model with 4-hour task scheduling for 200 stations and 7 170 debris. The final results show that both the algorithms are able to solve near real-timely the monitoring task programming, and can be used as an effective solution to the network task scheduling optimization.
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