Meteors occur when the meteoroid (space rock) reaches the E layer where the atmospheric density is high enough to heat the rock to incandescence and produce a trail of ions and free electrons. The recombination rate of electrons is relatively slow and allows reflection of radio waves up to a number of minutes. The trail lasts longer as frequency goes lower. Meanwhile the ion trail drifts with the resident winds resulting in a Doppler shift in the incident radio wave which is large enough to be seen relative to the trace of the incident signal on a waterfall display. Figure 1 is from my 30m grabber showing the fskcw signal from KD5SSF along with a typical meteor ping and airplane reflection.
|Figure 1. Meteor Ping on KD5SSF's FSKCW QRSS Signal|
During the recent Geminids I was doing an experiment with WD4AH to look for meteor pings from his signal with no thought of using the signal of KD5SSF. While looking for pings from WD4AH I could not help but notice the frequent pings on SSF whose frequency was about 10 Hz away. I archive my 10 minute grabs and had available six days of data before, during and after the Geninids and decided to count all the pings and see if data could be presented in some way to yield information about the shower. And lo and behold it did, as I shall now describe.
Pings vary from just a brief smudge to a lengthy, bright feature. I considered only whether or not a ping was noted on a given 10 minute grab and made no effort to distinguish multiple pings on that frame. I also tried to account for the stronger pings by assigning values of 1 for the regular ones and 2 and 3 for the progressively stronger ones.
Interference can produce "false pings" due to airplane reflections, other QRSS signals and pulses that come from Lord knows where, The false pings can be identified relatively easily by their characteristic shapes. For example, airplane reflections have a constantly curving shape which is sharp and distinct. Likewise the keying characteristics of other QRSS stations will be different from that of KD5SSF. Most noise pulses will usually be spread across the frequency axis. A possible ping was rejected when I could not be certain. If anything I think I under estimated the number of pings. The fsk keying of SSF's signal was a help also since the ping would follow the up and down shifts which the other QRM would not.
A total of 122 ping events was counted and entered into a Google spreadsheet and grouped in several ways. Figure 2 is a count of pings for each day. Figure 3 is a histogram plot of pings versus time of day by dividing the 24 hours of time into 11 bins and totaling the number of pings in each bin for the six day period. The scale is a little strange since it is divided 24 by 11 but you can see clearly that the maximum number of pings over the six day period was greatest between roughly 0900z to 1130z which is about 2 or 3 hours before Sunrise local time.
|Figure 2. Pings for Each Day|
|Figure 3. Pings vs Time of Day|
|Figure 4. Pings per Four Hour Period|
I then counted the pings in successive four hour periods from the beginning to the end of the recording period, Figure 4. I think the large spike on the 15th was augmented by the way I assigned higher numbers to stronger events. That suggests there was a number of big rocks during that time.
It was a bit tedious examining all the 10 minute grabs in detail. It took about 2 hours and 2 Salty Dogs. I put on my reading glasses and got close to the screen to better judge each frame for pings and distinguish them from QRM. I counted the pings using Notepad with four columns for UTC time and a "1" for a ping, a note on small, medium or large and in the fourth column the final adjusted ping number. The final table was saved then entered into Google Sheets for analysis. The analysis was easy and fun with Google Sheets doing all the work.
The main thing you need for a similar project is a nearby QRSS station at just the right distance or antenna orientation to give a clean, stable, not too strong signal so you can see the fuzzy pings