Research on Multi-sensor Cooperative Tracking Mission Planning of Aerospace Hypersonic Vehicles
Qiang Fu, Chengli Fan, Gang Wang, Xiangke Guo
Available Online June 2017.
- https://doi.org/10.2991/caai-17.2017.44How to use a DOI?
- Aerospace hypersonic vehicles; multi-sensors; cooperative tracking; mission planning; self-adapting clonal genetic algorithms
- Aimed at aerospace hypersonic vehicles (AHV) with the characteristics of high velocity, maneuverability, Radar Cross-section (RCS) weak, the single sensor is difficult to effectively track, therefore proposed multi-sensor collaborative workflow, construct cooperative tracking mission planning framework based on multi-agent system (MAS), and then multi-sensor cooperative optimization model is established. Proposed collaborative tracking mission planning algorithm based on Self-adaptive clonal genetic algorithm (SCGA). Simulation results validate the model, algorithm to establish is rationality and superiority.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Qiang Fu AU - Chengli Fan AU - Gang Wang AU - Xiangke Guo PY - 2017/06 DA - 2017/06 TI - Research on Multi-sensor Cooperative Tracking Mission Planning of Aerospace Hypersonic Vehicles BT - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017) PB - Atlantis Press SP - 201 EP - 206 SN - 1951-6851 UR - https://doi.org/10.2991/caai-17.2017.44 DO - https://doi.org/10.2991/caai-17.2017.44 ID - Fu2017/06 ER -