RF emitter localization with robotic swarms

John A. Sauter; Kellen Bixler; Sarah Kitchen; Richard Chase

doi:10.1117/12.2557273

23 April 2020 RF emitter localization with robotic swarms

John A. Sauter, Kellen Bixler, Sarah Kitchen, Richard Chase

Proceedings Volume 11425, Unmanned Systems Technology XXII; 114250D (2020) https://doi.org/10.1117/12.2557273
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

Swarms of inexpensive, robotic sensors have the potential for revolutionizing intelligence gathering. They self-organize to provide wide apertures, redundancy, attritability, with low probability of detect over a wide area. Coordinating swarm behaviors to provide the necessary apertures and spatial configurations requires novel methods of distributed control that can maintain the positioning accuracy in the face of arbitrary threats and obstacles. In this paper we describe the algorithms to control a swarm of air vehicles with radio frequency receivers that cooperatively search an urban area for radio frequency emitters, self-organize into teams to localize each emitter, and perform coordinated maneuvers to maximize the information gain during the localization operation. The swarm is able to adapt to attrition, performs collision avoidance, and adjusts its trajectories based on the urban terrain. These behaviors were implemented in a ROS-based swarm deployment environment suitable for execution on a small drone and simulated in a 3D model of a small urban area. This paper describes the search and localization tactics employed, the algorithms for implementing those tactics in the swarm, and experimental results. Our companion paper describes the algorithms used for localization.

Conference Presentation

Citation Download Citation

John A. Sauter, Kellen Bixler, Sarah Kitchen, and Richard Chase "RF emitter localization with robotic swarms", Proc. SPIE 11425, Unmanned Systems Technology XXII, 114250D (23 April 2020); https://doi.org/10.1117/12.2557273

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available