Power-aware improvement in signal detection.
Abstract
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 ofmore »
- Authors:
-
- Scott D.
- Patrick M.
- Maya
- Jayashree
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 976518
- Report Number(s):
- LA-UR-03-0420
TRN: US201017%%666
- Resource Type:
- Conference
- 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
- Subject:
- 97 MATHEMATICAL METHODS AND COMPUTING; ACCURACY; ALGORITHMS; DECISION MAKING; DETECTION; PERFORMANCE; PROCESSING; REMOTE SENSING; SATELLITES; TESTING; TRANSIENTS; SIGNALS; Power Award Computing; Signal Detection
Citation Formats
Briles, S D, Shriver, P M, Gokhale, M, and Harikumar, J. Power-aware improvement in signal detection.. United States: N. p., 2003.
Web.
Briles, S D, Shriver, P M, Gokhale, M, & Harikumar, J. Power-aware improvement in signal detection.. United States.
Briles, S D, Shriver, P M, Gokhale, M, and Harikumar, J. 2003.
"Power-aware improvement in signal detection.". United States. https://www.osti.gov/servlets/purl/976518.
@article{osti_976518,
title = {Power-aware improvement in signal detection.},
author = {Briles, S D and Shriver, P M and Gokhale, M and Harikumar, J},
abstractNote = {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.},
doi = {},
url = {https://www.osti.gov/biblio/976518},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 00:00:00 EST 2003},
month = {Wed Jan 01 00:00:00 EST 2003}
}