I'm currently undertaking a year-long thesis project in my final year of electrical engineering at the University of Queensland. The topic is 'Passive Radar Detection', with a focus on algorithms, particularly on the synchronisation of multiple receivers and increasing the efficiency of the algorithm. It's heaps of fun because I get to go outside and hunt down good locations for viewing flight paths, and it's really cool that I'm able to detect aircraft without transmitting any signals.
These are explained in the next section.
This is a detection of an aeroplane that flew over my antenna during my sixth test. After all the initial noise disappears, you can see a little dot heading up and arcing to the right. That's the aeroplane. Click on the animation to view a version that you can zoom in on.
This is a detection of a helicopter that flew past my antenna during my first test. I made this gif with a slower frame rate to make it clear. The little dot moving through the horizontal line and upwards is the helicopter. Click on the animation to view a version that you can zoom in on.
A bit more of an explanation
How do I interpret these results?
Think of it as a plot, or a graph. The y-axis is Doppler shift, and the x-axis is sample delay. The x-axis tells us how far away an object is, and the y-axis tells us whether it is approaching or moving away from the antenna, along with its relative velocity.
So for example, in the aeroplane detection, it gets a bit noisy at the start, but at the end, we see a noticeable dot fly up and arc a bit to the right. This means that it's moving away from the antenna by moving up the y-axis, and it is getting further away by its slow arc parallel to the x-axis.
The constant horizontal line that you see is an artefact of the processing calculations. The next stage of the thesis is to try to remove that constant horizontal line and all the other noise, by techniques called 'clutter cancellation'.
What is passive radar?
This probably should be addressed earlier in the page, but I just think the results look so cool that they have to go first.
In active radar, an antenna basically transmits some electromagnetic waves in a diredction, and then they reflect off objects in the path of transmission, which end up being received back at the original antenna that transmitted them. Then one can perform some processing to discern relative velocities and ranges of targets. I'm sure we've all seen radar in movies with little moving dots going all around some screen.
The difference with passive radar is that a user doesn't transmit anything. Passive radar utilises electromagnetic waves that are already in the air, such as digital TV, digital radio, FM radio, satellite signals, WiFi, and the list goes on. This is what brings on the word 'passive', our little antenna just sits there, receiving, not actively transmitting anything. Often, transmitters can be large, heavy, and require a lot of power to work, whereas only operating a receiver can be very lightweight and physically small, especially given the advent and constant improvement of software defined radios. My current equipment is shown below, to demonstrate how cheaply and easily one could perform passive radar.
However, some downsides consist of the fact that you're at the mercy of what is currently being transmitted in an area, and the physical environment can change the nature of what you're receiving quite a bit. Despite that, many of these signals such as satellite and digital are ubiquitous in many geographical areas, and they have good characteristics for passive radar, making passive radar research an interesting and potentially useful undertaking.
What have you done so far?
The preliminary plots are called range-Doppler plots, because they show Doppler shift and delay on them, which can be converted to range. These are the first step to radar, so it's good that I at least got one step done! They are calculated by the use of the complex ambiguity function, which is basically frequency shifting and cross-correlation over and over. I would show the maths here, but I haven't gotten around to looking up the equation syntax for this version of markdown. I'll get to it when assessment isn't as hectic.
What is ahead?
Now that I've been able to successfully and repeatedly detect aircraft, my next goal is clutter cancellation, which as mentioned previously, is getting rid of all of the things like the constant horizontal line and all that other stuff on the y-axis. Ideally, when clutter cancellation is performed, just the target should remain, making it stand out from the rest.
Then, or in the meantime, I'm aiming to have two antennas with software defined radios running simultaneously, trained on the same airspace. They will be physically separated, and then I will try to synchronise them not only in time, but also in frequency and phase, as the receivers will have internal clocks with slightly different offsets. After that, I then want to try to use two physically separated receivers to resolve a coordinate in space for the aircraft.
I'll try to update this as I go. Thanks for having a look at all this; it's so much fun.
I've got a yagi antenna that picks up digital radio (DAB+) signals connected to an RTL (RTL2832U) based software defined radio. I record IQ samples with this and then perform all of my processing in python. I've also got a bladeRF that I may use down the road.