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Title: Power-aware improvement in signal detection.

Conference ·
OSTI ID:976518

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.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
OSTI ID:
976518
Report Number(s):
LA-UR-03-0420; TRN: US201017%%666
Resource Relation:
Conference: Submitted to: International Signal Processing Conference 2003, March 31, 2003 - April 3, 2003, Dallas, TX
Country of Publication:
United States
Language:
English