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Analysis of Lightning Data
The objective of this project is to allow for automated
analysis of FORTE
data using algorithms developed in MATLAB. Once this is complete,
I will analyze the effects of signal degradation in the FORTE signatures
due to lossy compression, and help determine the suitability of the compression
algorithm - a wavelet transform subband coder adapted from image compression
techniques. The MATLAB analysis will further provide statistical
information which can be databased for later use. The following parameters
were determined:
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The average power of the pre-whitened, optimally de-chirped signal.
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The line-of-sight-integrated total electron content (slant TEC).
-
The peak pre-whitened, optimally de-chirped power.
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The contrast or peak-to-median power.
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The power-autocorrelation 1/e width.
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The power-autocorrelation lag of the secondary peak.
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The power-autocorrelation signal-to-noise ratio of the secondary peak.
By comparing how well these seven parameters are preserved
at various compression levels, it can shown how suitable the compression
algorithm is for use in the FORTE project.
Process of Sorting the Lightning Signals
The process of sorting involves six steps:
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Conversion of the binary data into a spectrogram.
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Pre-whitening of the spectrogram to supress any carrier frequencies.
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Straightening (de-chirping) the spectrogram
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Determing the Total Electron Content.
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Integrating with respect to time to determine power.
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Performing an autocorrelation function on the power spectrum.
Once these six step are complete, the statistical information
can be extracted, analysized, and archived.
Process of Signal Compression
The processs of compression involes several steps:
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Running compression algorithm on raw binary signal for each of the eight
target entropies.
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Generating jpeg image files for each six steps in the sorting process.
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Extracting the information on each of the seven parameters as applicable.
Process of Generating Statistics
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Parsing information on the parameters derived in the experiments.
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Computing the mean relative error of the seven parameters.
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Computing the standard deviation of relative errors of the seven parameters.
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Graphically displaying these errors for each signal versus the target entropy.
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Analysing and commenting on these results (including development of this
web page).
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CIC - 3 | c3webmeister@c3.lanl.gov
| LANL | Copyright
© UC 1998 | Disclaimer
| 25 June 1998
Shane Crockett <m991368@nadn.navy.mil>
and C M Brislawn <brislawn@lanl.gov>