Technical Program

Paper Detail

Paper:SPTM-P13.3
Session:Detection and Classification
Time:Friday, May 21, 15:30 - 17:30
Presentation: Poster
Topic: Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps.
Title: A GLRT AND BOOTSTRAP APPROACH TO DETECTION IN MAGNETIC RESONANCE FORCE MICROSCOPY
Authors: Pei-Jung Chung; University of Michigan, Ann Arbor 
 José Moura; Carnegie Mellon University 
Abstract: Magnetic resonance force microscopy (MRFM) is a technology that will potentially enable microscopy of molecules and proteins at atomic--scale detail. Physicists are pursuing MRFM and single electron spin microscopy (SESM). Many technological challenges exist for MRFM and SESM to deliver on the promise of ``visualizing'' a single electron spin. The forces of interest are in the subattoneNewton and attoneNewton range ($10^{-18}$N). In this paper we consider the problem in MRFM and SESM of detecting extremely weak signals buried in noise with SNR in the range of -15~dB to -40~dB. We describe a model that, although simplistic, captures the features of the problem.We present a GLRT and bootstrap approach that incorporates a bank of Viterbi algorithms, and show by simulations that, with physically realistic parameter values, the detector can achieve probability of detection $\beta=0.9$ with false alarm rate $\alpha=0.05$, at SNR$=-20$ dB.
 
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