A Stochastic Search Approach for UAV Trajectory Planning In Localization Problems

Author

Ghassemi, Farhad ; Krishnamurthy, Vikram

Author_Institution

Dept. of Electr. & Comput. Eng., British Columbia Univ., Vancouver, BC

Volume

3

fYear

2006

fDate

14-19 May 2006

Abstract

We discuss the off-line and on-line aspects of trajectory planning in bearings-only localization. Assuming that there are m(ges 1) moveable sensors (e.g. UAVs), which fly in closed trajectories, the aim is to determine the optimal shape of the trajectory. We investigate the properties of closed optimal trajectories in the off-line problem and show that these solutions are invariant under a scaling transformation of the problem parameters. This result is used to numerically derive a set of solutions for the normalized parameters. These solutions are then used in a stochastic search algorithm which randomly explores the trajectories but spends the largest amount of time in the optimal trajectory

Keywords

aircraft; remotely operated vehicles; search problems; sensors; stochastic processes; UAV trajectory planning; bearings-only localization; localization problems; moveable sensors; stochastic search approach; Acoustic sensors; Area measurement; Cost function; Covariance matrix; Optimization methods; Position measurement; Shape; Stochastic processes; Trajectory; Unmanned aerial vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660874

Filename

1660874