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High-resolution biosensor spectral peak shift estimation

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2 Author(s)
Karl, W.C. ; Electr. & Comput. Dept., Boston Univ., MA, USA ; Pien, H.

In this work we present a maximum likelihood (ML) approach to high-resolution estimation of the shifts of a spectral signal. This spectral signal arises in application of optically-based resonant biosensors, where high-resolution in the estimation of signal shift is synonymous with high-sensitivity to biological interactions. The underlying signal is nonuniformly sampled and exhibits Poisson noise statistics. Shift estimation accuracies orders of magnitude finer than the sample spacing are sought. The ML-based formulation leads to a solution approach different from typical resonance shift estimation methods based on polynomial fitting and peak (or ) estimation and tracking.

Published in:

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on  (Volume:2 )

Date of Conference:

9-12 Nov. 2003

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