Journal of Intelligent & Robotic Systems

, Volume 68, Issue 3–4, pp 359–371 | Cite as

UAV Mobile Ground Target Pursuit Algorithm

  • Xiaowei Fu
  • Huicheng Feng
  • Xiaoguang Gao


In this paper, we propose a comprehensive ground target pursuit algorithm for fixed-wing unmanned aerial vehicles (UAVs). Based on the division of two kinds of possible path patterns, the method generates waypoints step by step and steers the UAV to the latest waypoint. When it is time for waypoint correction, the tracking error will be recorded, and this error will be transferred to the next waypoint for synchronization purposes. An alarm mechanism is applied in case the target moves out of range of the UAV sensor. The noise in the measurement of the target parameters is considered and is processed by a least square estimator. Simulations with three different scenarios are performed, and the results demonstrate that the algorithm is stable, reliable, and computationally efficient.


UAV Ground target tracking Path patterns Alarm mechanism 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Theodorakopoulos, P., Lacroix, S.: A strategy for tracking a ground target with a UAV. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1254–1259Google Scholar
  2. 2.
    Ruangwiset, A.: Path generation for ground target tracking of airplane-typed UAV. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, pp. 1354–1358Google Scholar
  3. 3.
    Wise, R.A., Rysdyk, R.T.: UAV coordination for autonomous target tracking. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, 21–24 August 2006, Keystone, ColoradoGoogle Scholar
  4. 4.
    Monda, M.J., Woolsey, C.A., Konda Reddy, C.: Ground target localization and tracking in a riverine environment from a UAV with a gimbaled camera. In: AIAA Guidance, Navigation and Control Conference and Exhibit, 20–23 August 2007, Hilton Head, South CarolinaGoogle Scholar
  5. 5.
    Semerdjiev, E., Mihaylova, L., Rong Li, X.: An adaptive IMM estimator for sircraft tracking. In: Proc. 1999 International Conf. on Information FusionGoogle Scholar
  6. 6.
    Zengin, U., Dogan, A.: Target tracking by UAVs under communication constraints in an adversarial environment. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, 15–18 August 2005, San Francisco, CaliforniaGoogle Scholar
  7. 7.
    Yongyuan, Q., Hongyue, Z., Shuhua, W.: The principle of Kalman filter and integrated navigation (in Chinese). NPU Press, Xi’an (1998)Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.School of Electronics and InformationNorthwestern Polytechnical UniversityXi’anChina

Personalised recommendations