Using Photoshop Histograms to Quantify Meteor Scatter Data

The usual way to quantify meteors is "one ping at a time."  I have described a method I use on 30m by watching pings on a local QRSS station.  It works well but is labor intensive and subject to false returns from airplanes...the local airport is between us.

Recently I've looked at two other ways to observe pings.  The web site LiveMeteors.com uses a well established technique which listens to the carrier signal from a Canadian TV station with a VHF receiving station in Washington DC.  I've had good results in using the audio piped into a PC sound card then to a waterfall spectrum analyzer,  Spectrum Lab.  Figure 1 is a typical recording.

Figure 1.  Typical Ping Recording for One Hour

The question arises immediately, "How does one count or assess all these pings?"  There's just too many to deal with, varying from specks to large events.  Photoshop to the rescue!  There's a similar problem in photography to evaluate at the tonal variation in a photographic image or parts of the image using a histogram of the luminosity.  Figure 2 is an example.  It is a graph of number of pixels in each exposure bin from 0 to 255, left to right, or pure black to pure white.  The significance is the mean or average grayness and the standard deviation which is a measure of the spread.  It seems to me that the mean best represents the intensity of the image but I have also examined the SD.  Here's how I did it.

Figure 2.  Luminosity Histogram

The pings were recorded in one hour chunks or "grabs".  For each grab I used the selection tool to make a rectangle around the significant extent of the pings and determined the mean within this frame.  Then to account for the background I moved the frame keeping the length and width the same to an area just below to measure the mean of the noise which I subtracted from the ping frame.  These values I assume are proportional to the intensity of the meteor shower for each hour.   Figure 3 shows the measurement frames for pings.  The frame was moved down to an area with no pings for the background.  Note that there is an extra line of pings above the main one and it is not relative to this discussion.

Figure 3.  Frame Selection for Pings Histogram

This procedure was applied to a 24 hour set of grabs made in one hour increments during a recent meteor shower and plotted to produce Figure 4.  The results shows the expected variation with maximum pings around Sunrise and minimum around Sunset.

Figure 4.  Results Obtained with Mean Luminosity Assessment of Pings per Hour

It is by far the quickest way to analyze pings I have tried.  Once the workflow was established I found it took only a few minutes to determine the histogram data for each one hour grab. Any method of quantifying meteors is relative since any measurement scheme counts pings only in a given field of view.  What I like about this method it that it takes into account pings of all size and strength right down to the background noise..

A second method utilizes receiving stations on the KIWI network which are tuned to strong stations such as WWV and CHU.  The audio is fed into my PC as described above and produces similar output. .  Both stations emit strong, omnidirectional  signals which are on the air 24/7 day in and day out.  The KIWI receiver network consists of dozens of KIWI-SDR receivers located around the World and controllable by the user via an Internet connection.   Figure 5 is a compilation of several combinations made back in late April as a first look at the feasibility of the method.  I have lately explored this in more detail with CHU on 14700 kHz using the KIWI receiver of W1NT in New Hampshire.  The antenna at W1NT is a 500 foot Beverage aimed northeast

Figure 5.  Feasibility Study of Using KIWI Receivers to Measure Pings from WWV and CHU

 and does a most excellent job of pulling in the weak QRSS stations running typically 250 mW signals on 30 thru 160m.  It should do even better on 14700 kHz and apparently does based on signals received so far.  Figure 6 shows a one hour grab using DL4YHF's Spectrum Lab software while Figure 6 shows greater detail using that of G3PLX's SBSpectrum software.  I can see the possibility of using the Mean Luminosity technique to isolate and record pings moving towards, upper, and away, lower, from the receiver.

Note the two horizontal lines at the center shown at higher resolution in Figure 6 where we see there is actually a third line in between.  This is the well known and commonly seen effect of backscatter

Figure 6.  Bragg Effect Backscatter by Ocean Waves

from surface waves on a body of water due to the Bragg Effect.  The moving waves cause a Doppler shift in which the intensity is made stronger by the regular spacing of the waves.    The fainter center line is the incident wave either reflected from land or possibly transmitted via ground wave.  I don't think this applies to meteors but there it is.

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