Special Issue "Adaptive Sensing"

Guest Editor
Prof. Dr. Rolf Mueller
Department of Mechanical Engineering, Virginia Tech, Institute for Advanced Learning and Research, 150 Slayton Ave., Danville, VA 24540, USA
Website: http://www.me.vt.edu/people/faculty/Mueller.html
E-Mail:
Interests: bio-inspired technology and design patterns in nature; integration of structure and sensing; wave-based sensing; biosonar; bat-inspired autonomous robots

Dear Colleagues,

Over the past decades, an ever deepening understanding of the basic science principles behind sensor function combined with powerful engineering optimization methods has continuously pushed sensing capabilities forward. In many cases, fundamental physical limits have been reached - and sometimes even circumvented. Nevertheless, delivering satisfactory sensor performance remains an elusive goal for many critical applications scenarios. In the majority of these cases, the root cause for these difficulties lies in complex, dynamic signals of interest or likewise complex, dynamic environments in which these signals have to be sensed. In such situations, no single sensor configuration can be relied upon to continuously meet performance expectations. Adaptive sensing paradigms are designed to address these issues and hence hold great promise to extend technical sensing capabilities to meet the requirements of demanding and critical applications. To reach these goals requires advances in several key areas of sensors research. Examples are insights into the signals and the environments in which they are sensed, novel sensor designs that offer multiple levels of adaptation along with the necessary paradigms to control them, and methods for the interpretation of non-stationary sensor outputs. Making the most out of adaptive sensing strategies will also require intelligent integration of these aspects.

Prof. Dr. Rolf Mueller
Guest Editor

Submission

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• sensor adaptation
• adaptive sensor hardware
• signal understanding
• sensor control strategies
• system integration