1. 海軍軍官學校 「迎向海洋，逐夢啟航」學術研討會
Ant-colony-based Track Coordination for the Planning of Earth Observation Missions
R.O.C. NAVAL ACADEMY
○○○ 海軍官校資訊管理學系 ○○○ 國防大學理工學院國科所
Introduction
Ant-Colony-Based MTC Algorithm
Satellite imagery is becoming increasingly important in disaster relief and land monitoring. Unfortunately, the limited maneuverability of satellites and increased demand for these resources has meant that observation requests cannot be met by the available supply. Imaging scheduling technology has been developed to make better use of the limited resources of earth observation satellites (EOS), taking into account many constraints including thermal limitations, solid state recording, data transmission, and maneuverability. Satellite imaging scheduling is considered an NP-hard problem. The recent introduction of multiple satellites has shifted the study of EOS scheduling from single satellite optimization (SSO) to multi-satellite optimization (MSO) schemes, with a resulting increase in complexity.
(a) (b) (c)
Mission tracks for Satellite 3 and 24 randomly generated AOIs; (b) The solution determined by the TCPDF algorithm; (c) The solution determined by the proposed ACS algorithm
(d) (e)
(d) Scatter plot of the 10,000 solutions; (e) Approximated Pareto optimal solutions obtained from each ofthe scheduling algorithms
Results and Discussion
This paper proposes a novel imaging scheduling algorithm to enable multi-objective optimization for multiple satellites (MOO-MS) capable of providing real-world solutions. The proposed ACS algorithm considers a mission track as a single entity in the formulation of SSO and MSO as an uncorrelated parallel machine scheduling problem. This approach avoids excessive calculation and provides optimal solutions within a short period of time. For a given satellite mission track with many ground targets, a swarm of simulated ants are created to detect an efficient scenario with which to plan satellite imaging operations. Compared with two MTC-based schemes (UPDF and TCPDF), the proposed ACS scheme is more adaptive and practical for a wide range of applications involving the scheduling of satellite imaging tasks.
Objective