Tag Archives: signal

Meteor showers and different types of meteor trails

Okay, so the Perseid meteor shower has passed and I didn’t detect as many meteors as I expected, so I did a little bit of an internet search and found that the Perseid meteor shower is actually a Northern Hemisphere shower. The radiant (the point from which meteors seem to originate from) doesn’t get as high up in the sky for us and thus the Southern Hemisphere does not  get as many meteors. On top of that, they were coming from the North, while my antenna is pointing South so this seems to explain why I detected no difference in my meteor count.

However, I found a website which gives a list of meteor showers for the Southern Hemisphere, so I will be referring to this from now on and see if what I am getting is matching with what is written here.

Now, how do I know that my radio signal is reflecting off a meteor trail?

According to the research paper, “Forward scattering of radio waves off meteor trails, 1995” by Jean-Marc Wislez, in classical theory of meteor scatter, there are two extreme cases of meteor trails that can occur – the “underdense” meteor trail and the “overdense” meteor trail. When a meteoroid enters our atmosphere, the atoms in the atmosphere become ionised, thus creating a trail of free electrons and ions. It is the free electrons that contribute the most to the scattered signal. If the line density (i.e. the number of electrons per unit of length of the meteor trail) of ionisation is low, then the incident wave penetrates the meteor trail and the electrons absorb the energy of the wave. This makes them oscillate and thus they re-emit the radio wave in all directions. The radio signal that is scattered in this way is said to have scattered off an “underdense” meteor trail. If the line density of ionisation is high, then we assume that the meteor trail acts like a metallic cylinder whose radius is much larger than the wavelength of the radio wave. This approximation assumes that the incident waves scatter off the surface of the cylinder since the radio waves cannot penetrate the central part of the trail. This type of trail is called an “overdense” meteor trail. However, the “metallic cylinder” approximation has flaws, as it does not take into account any low density part of the meteor trail, and it assumes that the power of the scattered signal in the perpendicular direction to the meteor trail is directly proportional to the radius of the cylinder.

Here is a simulation of a power-time graph, based on theory, of an underdense and a short overdense meteor trail (taken from the “Forward scattering of radio waves off meteor trails” paper):

Power-time graph of an underdense and a short overdense meteor trail. Reference: Forward scattering of radio waves off meteor trails - Jean Marc Wislez

Power-time graph of an underdense and a short overdense meteor trail. Reference: Forward scattering of radio waves off meteor trails – Jean Marc Wislez

And here are examples of some of my observations:

As it can be seen in the graphs, the power-time graphs of the underdense and short overdense meteor trails almost perfectly match the predicted simulations. The only difference is that some of the fluctuations that I got could be due to the signal itself as I am using an FM radio signal, whereas in the research paper they used a constant amplitude signal. However, these signals are both quite short so I think it’s safe to assume that in these two moments the signal was very close to being constant in amplitude and thus they seem to fit the theory.

an underdense and short overdense meteor trails

Now, there is also a third type of power-time graph that can happen, and this meteor trail is called a long overdense trail. In the research paper that I keep referring back to, there isn’t a simulation to predict this type of meteor trail, however it was detected and this is the observation that they made:

Power-time graph of a long overdense meteor trail. Reference: Forward scattering of radio waves off meteor trails - Jean Marc Wislez

Power-time graph of a long overdense meteor trail. Reference: Forward scattering of radio waves off meteor trails – Jean Marc Wislez

And here is an example of a long overdense signal that I detected. As it can be seen,
all three types of graphs seem to fit predictions or observations that have already been made and thus I conclude that what I am detecting really are meteors. The only one that is difficult to say that it was reflected off a meteor trail for sure is the long overdense meteor trail as it lasts much longer than the others, and thus the signal itself can fluctuate in power as it is an FM radio signal. It is very difficult to remove the actual signal fluctuations to compare to the long overdense meteor trail observation.

A long overdense meteor trail

I should also point out that these examples I showed are the “perfect” examples I found. There are signals that I have detected whose power-time graphs aren’t exactly as what is predicted, but still follow the similar patterns. The variations in the graph could be due to the fact that my signal is not constant in amplitude, but also these simulations count on ideal conditions and make approximations and assumptions that do not always happen in real life. Meteor trails can be in any size and shape, depending on the size of the meteor, its speed, direction and also wind, therefore the radio wave reflections can be quite different from these ideal predictions.

 

I have good news and bad news. Bad news is that I only started my data collection at around 11.40pm on 27th July, which is later than I was hoping, and good news is that everything is working perfectly!

There are a couple of reasons I ended up starting so late, and one of the reasons is actually because of the other. So, I was originally copying and pasting my files from the Ardmore computer onto my laptop, but this turned out to be very slow and time consuming, so instead I installed the Dropbox and set up SDR# so that it automatically uploaded the files onto it once the signal was recorded. While copying and pasting, I remained connected to the computer, but when I started using the Dropbox, I started disconnecting. This is because the internet connection in Ardmore is generally weak and slow and everything would significantly slow down when I was still connected while the files were uploading. I also installed the Dropbox onto my own laptop and when files arrived, I’d put them into another folder to keep the Dropbox space free, and I’d remain disconnected, waiting for more files to arrive as they were being recorded and uploaded to the Dropbox. However, the files just wouldn’t arrive, so I’d connect again and see that nothing was recorded. This always led me to the conclusion that my settings weren’t good enough and I kept missing the signals, so I would change the settings, wait until a signal was detected and recorded to make sure that the setting was good, and then I would disconnect again, to wait for the files to arrive.

This was the first mistake – even when I had recorded signals before, they were recorded with a different setting, so every time I changed something I was pretty much starting all over again. Now, this went on for a few days – almost a week actually. Then I started to notice a pattern. I’d disconnect overnight, hoping for signals to get recorded and that I’d wake up with a full Dropbox, (because everything I have read about meteors said that most meteors enter our atmosphere between midnight and 7am), and I’d be disappointed every single time, thinking how it doesn’t make sense that there was absolutely nothing overnight (which contradicts my readings), especially when we are nearing a meteor shower. So then I would go on to change the settings, but before I did, I would just stay connected for a little bit and wait to see if anything happened. Now, if my setting was accidentally made so sensitive that even the noise level would trigger recording, then all of a sudden SDR# would start recording almost immediately. This also didn’t make sense to me. Why wasn’t the noise level triggering recording overnight, if it’s doing so now?

After a few days of this happening, no matter what setting I changed to (and honestly, I was running out of ideas of how to combine all the settings in a way that I didn’t try before), it finally clicked. Every time I disconnected, the program basically paused and didn’t record anything. That means, that not only was I constantly changing settings, I wasn’t consistently even recording the signals. This is the big mistake I made in my way of thinking – I assumed that everything was still working after I disconnected. This should have been the first thing I checked, even before starting any recordings. I don’t even want to think about how many signals I’ve missed, how many perfect settings I may have gotten and then changed, and how much sooner my data acquisition would have started if I had just checked this first. I guess this is what research is about and sometimes, something that seems so trivial doesn’t even enter the thought process.

I found a way now to disconnect without stopping the program, and I found a good setting that works perfectly, and everything over the last few days has been exactly the way I expected, with a few minor exceptions. One of those is that the program crashed one time, but luckily SDR# saves the last setting so I just had to restart it (but if there was a signal during those few seconds, it was missed). Another thing that happens a lot is that the whole noise floor jumps up for a split second and triggers recording. The only idea that I have at the moment to reason with this is that there may have been a spark somewhere nearby. This is something I have to look into and ask about. If it’s not a spark, I would like to find out what it is, because sometimes the noise floor only slightly twitches, and then sometimes it jumps up incredibly high. At the moment it seems random, although I will look into it to see if there is a pattern (i.e. maybe it happens every hour, or at the same time every day, etc).

Here is a picture of what I mean, so that it makes more sense:

A representation of where the noise floor normally is and how much stronger the Auckland ZM radio station is on the left, at 91.0MHz.

A representation of where the noise floor normally is and how much stronger the Auckland ZM radio station is on the left, at 91.0MHz.

Noise floor jumping. Notice how it's almost the same height as the Auckland ZM radio station, at 91.0MHz

Noise floor jumping. Note how it’s almost the same height as the Auckland ZM radio station, at 91.0MHz

Anyway, I’m just happy that, although I started later than I was planning to with my data acquisition, I figured it out and got my project back on track, and  now that everything is working with it, I can start to focus on analysing all of it!

Update

Last week I wrote about how I didn’t have remote access to the computer in Ardmore anymore because of the storm. That has now been restored – I asked our IT service to help me, and it works now and everything is back on track.

As I mentioned in a previous blog post, I thought that my originally chosen frequency of 101.7MHz may have been too weak to detect and so I decided to change to a stronger frequency. This is showing up some results! Currently I am tuned into 91.3MHz, which is the ZM radio station in Christchurch. The way that the software records the signal is that it records the whole bandwith that I can see on my screen (from about 90.8MHz to approximately 91.4MHz), and not just the 91.3MHz frequency. That means that while I’m recording 91.3, I am also recording 91.0, which is ZM in Auckland (ZM plays current pop music), and 91.4 which is Radio Concert (which is classical music) in the Waikato area, as my antenna can easily pick up the radio stations from there.

What is interesting, is that sometimes, when I detect a signal at 91.3MHz, there is also a peak that shows up on the 91.2MHz frequency.
To help explain better, here is a screenshot from a signal that was recorded on 07/21/2015  at 04:14:07.

A screenshot of one of the signals I detected at 91.3MHz

A screenshot of one of the signals I detected at 91.3MHz

Here, we have the Auckland ZM station on the left, at 91.0MHz, and we have the Waikato Radio Concert station on the right at 91.4MHz.  In between, there is a signal at 91.3MHz, which is ZM in Christchurch (and I will explain why I’m so sure of it shortly), but there is also an unknown signal at 91.2MHz. Looking at the list of radio stations in NZ, I saw that a possible radio station at this frequency is Radio Concert in Nelson. Looking at the map of NZ, we can see that Nelson is between Auckland and Christchurch and so it is possible that if a meteor (or something else) happened to fly between us and Nelson, it could have reflected both frequencies from Nelson and Christchurch. Although, I still have to prove this to myself geometrically, rather than assume that it can happen.

Okay, so at first I was a little bit skeptical, as it seemed a little bit too good to be true – that I can actually detect two frequencies that have reflected off something in our atmosphere seems a bit lucky. However, these signals are so strong that you can actually hear the music. So when I played the signal I detected on 91.3MHz, I heard a part of a Miley Cyrus song that was recorded, and when I tuned into the 91.2MHz, I heard classical music. This was my initial confirmation that I have detected ZM from Christchurch and Radio Concert from Nelson. Now I needed confirmation that what I recorded actually came from those stations. Assuming that all transmitters of the same  radio station play the same stuff at the same time (except maybe the ads), I listened to the 91.0MHz frequency I recorded, (which, as I said before, is ZM in Auckland) and it was the exact same part of the song  that was recorded on 91.3. Then, I tuned into the 91.4MHz frequency, (which is Radio Concert in Waikato) and I heard the part of the piano that sounds exactly the same as what was recorded on 91.2MHz.

I checked the list of all the radio stations again, and saw that there is no other ZM station in NZ that is being broadcast at 91.3MHz, and no other Radio Concert station in NZ that is being broadcast at 91.2MHz. All of these reasons led me to conclude that I have actually recorded two signals from the South Island, that have been reflected off something in our atmosphere because they are both too far away to be received directly.

This still seems too good to be true to me. It just happened, by luck, that I can record all 4 radio stations and compare the recorded signals to the actual signals that I definitely know were being broadcast at the time of recording.

I have emailed one of the radio stations to confirm that they play the same songs at the same time everywhere in the country. Now, what I have left to do is to actually figure out how to interpret these signals.

How do I find out that these signals were reflected off a meteor? Well, that’s a post for next time 🙂