Power-aware improvement in signal detection [electronic resource].
- Published:
- Washington, D.C. : United States. Dept. of Energy, 2003.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy. - Physical Description:
- 15 unnumbered pages : digital, PDF file
- Additional Creators:
- Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Summary:
- Improvements in signal detection characteristics for a remote-sensing instrument can be achieved at the expense of computational effort and the power associated with that effort. DSP used in remote sensing scenarios usually involves the detection of a signal and the estimation of parameters as sociated with that signal . Fortunately, the algorithms used for parameter estimation are the same algorithms which, through postprocessing decision making, decrease the false alarm rate . This post processing allows for the reduction in the false alarm rate as seen at the end product of the instrument . The level of false alarm reduction must be balanced against the amount of additional power that is needed to produce this level . This paper will present quantitative results that demonstrate this tradeoff for a specific application . This paper focuses on the detection of transient radio frequency (RF) events (e.g., lighting) as observed from the FORTE satellite . However the methodology presented for power-aware improvement in signal detection is general enough to be applied to most remote-sensing scenarios . A suite of algorithms, which vary widely in their precision of estimated parameters, is presented in the paper . Equally wide in variation is the amount of power required by each of the algorithms. Power requirements of the algorithms were obtained by actual physical measurement for a mimic of a RAD750 processor . Algorithm performance was determined via Monte Carlo testing . Using that same Monte Carlo testing post-pro ce ssing, thresholds for each of the algorithms were developed for the reduction of the false alarm rate. A quantitative display of how each of the algorithms decreases the false alarm rate over the front-end analog detection is displayed versus the power required.
- Report Numbers:
- E 1.99:la-ur-03-0420
la-ur-03-0420 - Subject(s):
- Other Subject(s):
- Note:
- Published through SciTech Connect.
01/01/2003.
"la-ur-03-0420"
Submitted to: International Signal Processing Conference 2003, March 31, 2003 - April 3, 2003, Dallas, TX.
Gokhale, M.; Briles, S. D.; Shriver, P. M.; Harikumar, J.
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