Hi everyone! I just finished this post, please enjoy it and let me know if you have questions or suggestions (especially regarding the math portions, of which I have a hard time understanding anything beyond year 2 calculus!).
The problem you are trying to solve here can be classically expressed as X'=Ax+Bu; Y = Cx + Du + Ev. Where Ax models the noise generating dynamics of the the drone, Bu models the control of the drone (typically random from your perspective), C,D,E model how the noise reaches and is processed by your microphone, and v is a random source simulating the wind.
In the most simple case, simply adding two slightly separated signals should not increase the noise. The problem is, the helicopter sound itself is very noisy, so I'm not sure this would work well. A lot of microphones might be needed, increasing the cost many times.
For low pass filtering, there are mufflers for microphones, did you have those?
Edit: and of course that's not really getting any points in the computer science department.
But this is probably the most practical solution, the data we have doesn't allow for it however. This could be used in the real world and the system could be more accurate, however in a crowded environment there will be other sounds the microphone will pick up, so some type of noise filter would be needed anyway.
If your microphone saturates its input that will distort the spectrum of the signal you are measuring.