Calibration as parameter estimation in sensor networks

  title={Calibration as parameter estimation in sensor networks},
  author={Kamin Whitehouse and David E. Culler},
We describe an ad-hoc localization system for sensor networks and explain why traditional calibration methods are inadequate for this system. Building upon previous work, we frame calibration as a parameter estimation problem; we parameterize each device and choose the values of those parameters that optimize the overall system performance. This method reduces our average error from 74.6% without calibration to 10.1%. We propose ways to expand this technique to a method of autocalibration for… CONTINUE READING
Highly Influential
This paper has highly influenced 19 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 754 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 262 extracted citations

Sparsity Based Efficient Cross-Correlation Techniques in Sensor Networks

IEEE Transactions on Mobile Computing • 2017
View 8 Excerpts
Highly Influenced

A Novel Distributed Sensor Positioning System Using the Dual of Target Tracking

IEEE Transactions on Computers • 2008
View 4 Excerpts
Method Support
Highly Influenced

Calibration of sensors in sensor networks

2005 IEEE Conference on Emerging Technologies and Factory Automation • 2005
View 4 Excerpts
Highly Influenced

Tracking moving targets in a smart sensor network

View 5 Excerpts
Method Support
Highly Influenced

755 Citations

Citations per Year
Semantic Scholar estimates that this publication has 755 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.