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13 Spectral Estimation Methods
for
Signal Analysis
Rainbow (tm) program calculates a Power Spectral Density (PSD) estimate from 1 of several Steve Kay's Estimators. Kay's modern Estimators have shed new light on signal detection. Detecting a signal 50+ dB down is now -very- possible.
Rainbow (tm) has a menu of Spectral estimators from Steve Kay's textbook, titled "Modern Spectral Estimation", 1988. The results differ dramatically from one estimator to another. Plus, varying input parameter(s) and/or number of points may show discrepancies.
Estimation methods in Rainbow include Autocorrelation, Covariance, Prony, Akaike, Burg, Recursive Maximum Likelihood Estimation, Modified Yule-Walker Equations and others.
This picture/plot shows a PSD plot for one of the thirteen methods available to choose from. The methods can vary dramatically in their results. Try several before choosing which estimation is best to represent your PSD.
Manufacturing companies take note! Some estimators can detect signals 50 to 100 dB from main signal. See documented example! The unwritten rule of '30 dB is okay (i.e. hidden) is no longer true.
See how zero padding effects ones results. Ability to change array sizes on the fly and thus show zero padding effect is/was main reason for writing this software.
If interested in a Spectral Analysis class click here.
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(Click Any Image To Enlarge)
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Power Spectral Density (PSD) Plot
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PSD 3D Plot
A 3D plot of ones spectrum as time goes on is achieved by calculating new PSD plots every delta_print time; i.e. every 'second' or two calculate another PSD plot. Then stand them up side by side so you get a plot like the one below.
(x = Frequency, y = Time, z = PSD Amplitude in dB)
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Download this Shareware Program?
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Note: Rainbow program works on -all- Windows OS Platforms.
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