URAV Simulation Training System Based on Aerosim and Google Earth


In order to solve the difficulties of traditional simulation training method on unmanned reconnaissance aerial vehicle, such as the low environment fidelity, difficulty of modeling and long cycle of development, a simulation training method based on Google Earth is put forward. The 6-DOF motion system of URAV is established through Matlab/Simulink. The visual simulation environment which is close to real scenes is formed though GE and software of SketchUp, and the visualization of flight data and elevation information of the region are also obtained through the software of GMS Aircraft Instrument and Measurement Studio. Experiments show that the method has satisfactory effects and its functions also can be strengthened, therefore it provides reference to related researchers.

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Z. Li, X. Li, J. Lv and Y. Li, "URAV Simulation Training System Based on Aerosim and Google Earth," Journal of Signal and Information Processing, Vol. 3 No. 2, 2012, pp. 169-174. doi: 10.4236/jsip.2012.32022.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] T. J. Hing and P. Y. Oh, “Development of an Unmanned Aerial Vehicle Piloting System with Integrated Motion Cueing for Training and Pilot Evaluation,” Journal of Intelligent and Robotic Systems, Vol. 54, No. 13, 2009, pp. 3-19. doi:10.1007/s10846-008-9252-3
[2] Y. Wang, W. Zhang, S. Wu and Y. Guo, “Simulators for Driving Safety Study—A Literature Review,” Lecture Notes in Computer Science, Vol. 45, No. 1, 2007, pp. 584-593. doi:10.1007/978-3-540-73335-5_63
[3] B. Ji, G. L. Shan and H. Chen, “Visual Simulation Method Based on VRML and Target Track,” Journal of System Simulation, Vol. 23, No. 9, 2011, pp. 1900-1904.
[4] G. D. Jin, L. B. Lu and Y. L. He, “URAV Real-Time Simulation System,” Journal of System Simulation, Vol. 19, No. 13, 2007, pp. 2932-2935.
[5] B. J. Yao, H. Zhao, C. L. Li and M. C. Chen, “3D Huge Terrain Generation in Flight Scene Simulation,” Journal of System Simulation, Vol. 21, No. 6, 2009, pp. 1633-1636.
[6] Z. H. Qi, D. W. Hu, A. L. Liu and X. P. Hu, “Airborne IMU Simulation Based on Simulink and Flight Gear,” Journal of Chinese Inertial Technology, Vol. 16, No. 4, 2008, pp. 400-403.
[7] J. Li, X. M. Li, K. C. Qian and H. X. Zhou, “Motion State Estimation for Micro UAV Using Inertial Sensor and Stereo Camera Pair,” Acta Aeronautica et Astronautica Sinica, Vol. 32, No. 12, 2011, pp. 2310-2317.
[8] J. N. Wu and W. Wang, “Research of a Kind of New UAV Training Simulator Based on Equipment Simulation,” Computer Measurement & Control, Vol. 19, No. 12, 2011, pp. 3105-3107.
[9] C. D. Edwards, “Nonlinear Six Degree-of-Freedom Simulator for a Small Unmanned Aerial Vehicle,” Mississippi State University, Mississippi, 2010.
[10] G. Ye, Z. F. Tian and C. L. Yan, “Flight-Test Data Visualization of Aircraft’s Flight Course Based on OpenGL,” Acta Aeronautica et Astronautica Sinica, Vol. 32, No. 6, 2011, pp. 1050-1057.
[11] E. Sun, A. Nieto and Z. Li, “GPS and Google Earth Based 3D Assisted Driving System for Trucks in Surface Mines,” Mining Science and Technology, Vol. 20, No. 1, 2010, pp. 138-142.
[12] Google Earth COM API Documentation. http://earth google.com/comapi/
[13] Keyhole Markup Language Documentation Introduction. http://code.google.com/api/kml/documentation/
[14] J. Ma, “Ground Monitor and Control System for Unmanned Aerial Vehicle Based on Google Earth,” Nanjing University of Aeronautics and Astronautics, Nanjing, 2011.
[15] J. P. Dai, “3D Visualization Technology Based on Google SketchUp,” Science of Surveying and Mapping, Vol. 36, No. 5, 2011, pp. 231-233.

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