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Multiobjective Optimal Design of MEMS-Based Reconfigurable and Evolvable Sensor Networks for Space Applications

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6 Author(s)

In this paper, the multiobjective optimal design of space-based reconfigurable sensor networks with novel adaptive MEMS antennas is investigated by using multiobjective evolutionary algorithms. The non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain multi-criteria Pareto-optimal solutions, which allows system designers to easily make a reasonable trade-off choice from the set of non-dominated solutions according to their preferences and system requirements. As a case study, a cluster-based satellite sensing network is simulated under multiple objectives. Most importantly, this paper also presents the application of our newly designed adaptive MEMS antennas together with the NSGA-II to the multiobjective optimal design of space-based reconfigurable sensor networks.

Published in:

Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007)

Date of Conference:

5-8 Aug. 2007