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Proceedings Paper

Position-adaptive MAV in emitter localization mission using RSSI and path loss exponent metrics
Author(s): Miguel Gates; Rastko Selmic
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Paper Abstract

We consider a Micro-Aerial Vehicle (MAV), used as a mobile sensor node, in conjunction with static sensor nodes, in a mission of detection and localization of a hidden Electromagnetic (EM) emitter. This paper provides algorithms for the MAV control under the Position-Adaptive Direction Finding (PADF) concept. The MAV avoids obstructions or locations that may disrupt the EM propagation of the emitter, hence reducing the accuracy of the receivers’ combined emitter location estimation. Given the cross Path Loss Exponents (PLEs) between the static and mobile node, we propose a cost function for the MAV’s position adjustments that is based on the combination of cross PLEs and Received Signal Strength Indicators (RSSI). The mobile node adjusts current position by minimizing a quadratic cost function such that the PLE of surrounding receivers is decreased while increasing RSSI from the mobile node to the target, thereby, reducing the inconsistency of the environment created by echo and multipath disturbances. In the process, the MAV finds a more uniform measuring environment that increases localization accuracy. We propose to embed this capability and functionality into MAV control algorithms.

Paper Details

Date Published: 17 May 2013
PDF: 11 pages
Proc. SPIE 8741, Unmanned Systems Technology XV, 87410J (17 May 2013); doi: 10.1117/12.2014048
Show Author Affiliations
Miguel Gates, Louisiana Tech Univ. (United States)
Rastko Selmic, Louisiana Tech Univ. (United States)

Published in SPIE Proceedings Vol. 8741:
Unmanned Systems Technology XV
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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