ISSNIP

Power Efficient State Estimation using Multiple Sensors

Investigators
Staff:

Subhra Dey;
Post Doctoral Research Fellow: Alex Leong.

Student:
Collaborations
Description
Introduction: We consider state estimation of scalar linear systems using analog forwarding with multiple sensors, for both multiple access and orthogonal access schemes. Optimal state estimation can be achieved at the fusion centre using a time varying Kalman filter.
Significance:
Applications:
Challenges: In many situations, it is shown that the error covariance decays at a rate of 1/M when the number of sensors M is large. Optimal allocation of transmission powers subject to constraints on the error covariance or sum power is considered, and compared with simpler schemes such as equal power allocation.
Publication
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