An innovative integrated framework for cooperative search and track of moving emitters in areas with obstacles

Document Type : Research Article

Authors

Department of Aerospace Engineering, Sharif University of Technology, Tehran, Iran

Abstract

In this paper, the problem of detection and tracking of emitters by multiple flying-vehicles, working in a cooperative manner, is considered. The radio sensor on each vehicle is capable of measuring the distance of the vehicle to the radio emitter. The goal is to detect the presence of such emitters, localize, and then track them. Meanwhile, the emitter can be moving or stationary, and may go beyond some environmental obstacles that prevent it from being sensed. The proposed procedure optimizes the routes and tasks of the employed flying-vehicles by minimizing a suitably-defined cost function. Moreover, the appropriateness level of the assigned routes and tasks is continuously assessed, so that
if it drops below an acceptable threshold due to the dynamics of the scenario, optimization is performed again and the routes and tasks are renewed. The simulations, as well as the complexity discussion, verify e ectiveness of the proposed method, considering the applied requirements and limitations.

Keywords

Main Subjects


References:
1. Zhang, H., Xin, B., Dou, L., et al. "A review of cooperative path planning of an unmanned aerial vehicle group", Frontiers of Information Technology and Electronic Engineering, 21(12), pp. 1671-1694 (2020). https://doi.org/10.1631/FITEE.2000228.
2. Sargolzaei, A., Abbaspour, A., and Crane, C., "Control of cooperative unmanned aerial vehicles: Review of applications, challenges, and algorithms", Optimization, Learning, and Control for Interdependent Complex Networks, 1123(1), pp. 229-255 (2020). https://doi.org/10.1007/978-3-030-34094-0-10.
3. Alotaibi, E., Alqefari, S., and Koubaa, A., "Lsar: Multi-uav collaboration for search and rescue missions", IEEE Access, 7, pp. 55817-55832 (2019). https://doi.org/10.1109/ACCESS.2019.2912306.
4. Scherer, J., Yahyanejad, S., Hayat, S., et al. "An autonomous multi-UAV system for search and rescue", Proceedings of the First Workshop on Micro Aerial Vehicle Networks, Systems, and Applications for Civilian Use, (2015). https://doi.org/10.1145/2750675.275068.
5. Minaeian, S. and Liu, J., and Son, Y. "Vision-based target detection and localization via a team of cooperative UAV and UGVs", IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(7) (2015). https://doi.org/10.1109/TSMC.2015.2491878.
6. Capitan, J., Merino, L., and Ollero, A. "Cooperative decision-making under uncertainties for multi-target surveillance with multiples UAVs", Journal of Intelligent and Robotic Systems, 84, pp. 371-386 (2016). https://doi.org/10.1007/s10846-015-0269-0.
7. Shaferman, V. and Shima, T. "Tracking multiple ground targets in urban environments using cooperating unmanned aerial vehicles", Journal of Dynamic Systems, Measurement, and Control, 137(5) (2015). https://doi.org/10.1115/1.4028594.
8. Xia, C., Yongtai, L., Liyuan, Y., et al. "Cooperative task assignment and track planning for multi-UAV attack mobile targets", Journal of Intelligent and Robotic Systems (2020). https://doi.org/10.1007/s10846-020- 01241-w.
9. Mainwaring, A., Culler, D., Polastre, J., et al. "Wireless sensor networks for habitat monitoring", ACM international workshop on Wireless sensor networks and applications (2002). https://doi.org/10.1145/570738.570751.
10. Hirsch, M. and Schroeder, D. "Dynamic decentralized cooperative control of multiple autonomous vehicles with multiple tasks for urban operations", AIAA Guidance, Navigation, and Control Conference (2012). https://doi.org/10.2514/6.2012-4788.
11. Nobahari, H., E ati, M., and Motie, M. "Cooperative search and localization of ground moving targets by a group of UAVs considering fuel constraint", Scientia Iranica (2019). https://doi.org/10.24200/sci.2018.21186.
12. Pitre, R., Li, X., and Delbalzo, R. "UAV route planning for joint search and track missions-An information-value approach", IEEE Transactions on Aerospace and Electronic Systems, 48(3), pp. 2551- 2565 (2012). https://doi.org/10.1109/TAES.2012.6237608.
13. Saghafi, F. and Esmailifar, S.M. "Searching and localizing a radio target by an unmanned  flying vehicle using bootstrap filtering", Journal of Dynamic Systems, Measurement, and Control, 137(2) (2015). https://doi.org/10.1115/1.4028313.
14. Esmailifar, S.M. and Saghafi, F. "Moving target localization by cooperation of multiple  flying vehicles", IEEE Transactions on Aerospace and Electronic Systems, 51(1), pp. 739-746 (2015). https://doi.org/10.1109/TAES.2014.130168.
15. Riehl, J., Collins, G., and Hespanha, J. "Cooperative search by UAV teams: A model predictive approach using dynamic graphs", IEEE Transactions on Aerospace and Electronic Systems, 47(4), pp. 2637-2656 (2011). https://doi.org/10.1109/TAES.2011.6034656.
16. Bansal, S., Goel, R., and Maini, R. "Ground vehicle and UAV collaborative routing and scheduling for humanitarian logistics using random walk based ant colony optimization", Scientia Iranica, pp. 632-644 (2022). https://doi.org/10.24200/sci.2021.58309.5664.
17. Fang, S., O'Young, S., and Rolland, L. "Online riskbased supervisory maneuvering guidance for small UAS detect-and-avoid systems", AIAA Journal of Guidance, Control, and Dynamics, 11, pp. 2588-2603 (2017). https://doi.org/10.2514/1.G003526.
18. Skolnik, M.I., Radar Handbook, IEEE (2008).
19. Bernardo, J. and Smith, A., Bayesian theory, John Wiley and Sons (2009).
20. Saho, K. and Masugi, M. "Performance analysis of  -fi- tracking filters using position and velocity measurements", EURASIP Journal on Advances in Signal Processing, 2015(1), p. 35 (2015). https://doi.org/10.1186/s13634-015-0220-321. Mayiatis, D. "Comparison of an alpha-beta and kalman filter in track while scan radars", Tech. rep., Naval Postgraduate School Monterey, (1979). 
22. Daum, F. "Nonlinear filters: Beyond the Kalman filter", IEEE Aerospace and Electronic Systems Magazine, 20(8), pp. 57-69 (2005). https://doi.org/10.1109/MAES.2005.1499276.
23. Anderson, J., Aircraft Performance and Design, McGraw-Hill (1999). 
24. Tang, K., Man, K., Kwong, S., et al. "Genetic algorithms and their applications", IEEE Signal Processing Magazine, 13(6), pp. 635-674 (1996). https://doi.org/10.1007/978-1-4471-7503-2 33.
25. Zhen, Z., Xing, D., and Gao, C. "Cooperative search-attack mission planning for multi-UAV based on intelligent self-organized algorithm", Aerospace Science and Technology, 76, pp. 402-411 (2018). https://doi.org/10.1016/j.ast.2018.01.035.
26. Esmailifar, S.M. and Saghafi, F. "Cooperative localization of marine targets by UAVs", Mechanical Systems and Signal Processing, 87, pp. 23-42 (2017). https://doi.org/10.1016/j.ymssp.2016.08.027.
27. Ankenbrandt, C. "An extension to the theory of convergence and a proof of the time complexity of genetic algorithms", Foundations of genetic algorithms, Elsevier, 1(1), pp. 53-68 (1991). https://doi.org/10.1016/B978-0-08-050684-5.50007-0.
Volume 32, Issue 5
Transactions on Computer Science & Engineering and Electrical Engineering
March and April 2025 Article ID:6850
  • Receive Date: 01 June 2022
  • Revise Date: 12 December 2022
  • Accept Date: 02 May 2023