Cooperative control of MAVs for a hidden emitter localization

Miguel Gates; Rastko Selmic; Raul Ordonez

doi:10.1117/12.919445

3 May 2012 Cooperative control of MAVs for a hidden emitter localization

Miguel Gates, Rastko Selmic, Raul Ordonez

Proceedings Volume 8361, Radar Sensor Technology XVI; 83610I (2012) https://doi.org/10.1117/12.919445
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

This paper provides a summary of the development of a three state machine-based cooperative control algorithm that is applied to multiple Unmanned Aerial Vehicles (UAVs) or Micro-Aerial Vehicles (MAVs) control. We use MAVs for cooperative search of a hidden electromagnetic source (emitter) in a controlled environment. MAVs are equipped with wireless sensor nodes capable of sensing an electromagnetic (EM) field around them. Simultaneous control and sensing capabilities of these MAVs are presented. The algorithm uses a three-state machine to control the MAVs during the search process. The first state is a decentralized cooperative search that allows MAVs to obtain information about the environment and detect EM emissions from the target. The second state implements a gradient descent algorithm in which the MAVs converge towards the target based on the received signal strength, while still maintaining a proximal distance from each other. MAVs are positioned at the optimal distance of the detected EM source before fine-tuning of the emitter localization is carried out. The third state incorporates a technique called Position-Adaptive Direction Finding (PADF), where the MAVs adapt their positions in order to further improve localization of a hidden emitter using an estimated path loss exponent as a feedback. We present simulation and experimental data that illustrate the proposed approach.

Citation Download Citation

Miguel Gates, Rastko Selmic, and Raul Ordonez "Cooperative control of MAVs for a hidden emitter localization", Proc. SPIE 8361, Radar Sensor Technology XVI, 83610I (3 May 2012); https://doi.org/10.1117/12.919445

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KEYWORDS

Micro unmanned aerial vehicles

Unmanned aerial vehicles

Detection and tracking algorithms

Target detection

Received signal strength

Sensor networks

Computer simulations

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