Smart Power Management for an Onboard Wireless Sensors and Actuators Network

The employment of wireless links for spacecraft onboard data communication is a new and challenging research topic. This new technology can be conveniently used for attitude determination and control sensors and actuators. Still, providing energy efficient data collection is of paramount importance to such an onboard wireless sensors and actuators network (OWSAN). This paper proposes a power management scheme based on estimation of the sensor measurements with a Kalman Filter. The power manager schedules the sleep periods on the node to lower the energy consumption of the wireless transmitter and the sensor. The simulation results show that there is a significant change in the energy consumption level of an onboard ADCS sensor.

[1]  Qi Han,et al.  Energy efficient data collection in distributed sensor environments , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[2]  Huang Lee,et al.  Wakeup scheduling in wireless sensor networks , 2006, MobiHoc '06.

[3]  Edward Y. Chang,et al.  Adaptive stream resource management using Kalman Filters , 2004, SIGMOD '04.

[4]  Halil Ersin Soken,et al.  Adaptive kalman filter with the filter gain correction applied to UAV flight dynamics , 2009, 2009 17th Mediterranean Conference on Control and Automation.

[5]  Jun Yang,et al.  Constraint chaining: on energy-efficient continuous monitoring in sensor networks , 2006, SIGMOD Conference.

[6]  Alex Borges Vieira,et al.  Efficient power management in real-time embedded systems , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[7]  J.A.P. Leijtens,et al.  Micro Digital Sun Sensor: System in a Package , 2004 .

[8]  C. W. de Boom,et al.  Micro Digital Sun Sensor: System in a Package , 2004, 2004 International Conference on MEMS, NANO and Smart Systems (ICMENS'04).

[9]  Jinli Cao,et al.  An energy-efficient data-driven power management for wireless sensor networks , 2008, DMSN '08.

[10]  W. Bärwald,et al.  Resumes of the Bird Mission , 2004 .

[11]  Anantha Chandrakasan,et al.  Dynamic Power Management in Wireless Sensor Networks , 2001, IEEE Des. Test Comput..

[12]  Kamesh Munagala,et al.  Energy-efficient monitoring of extreme values in sensor networks , 2006, SIGMOD Conference.

[13]  Robbert J. Hamann,et al.  New generations of spacecraft data handling systems: Less harness , more reliability , 2006 .

[14]  Luca Benini,et al.  Dynamic power management using adaptive learning tree , 1999, 1999 IEEE/ACM International Conference on Computer-Aided Design. Digest of Technical Papers (Cat. No.99CH37051).

[15]  Eberhard Gill,et al.  THE CHALLENGES OF INTRA-SPACECRAFT WIRELESS DATA INTERFACING , 2007 .

[16]  Edward Y. Chang,et al.  Adaptive sampling for sensor networks , 2004, DMSN '04.

[17]  Kay Römer,et al.  An Adaptive Strategy for Quality-Based Data Reduction in Wireless Sensor Networks , 2006 .