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Thinking about noise reduction I come up with low pass or band pass filters and using multiple microphones to correlate the signal. However I have no experience

Thinking about noise reduction I come up with low pass or band pass filters and using multiple microphones to correlate the signal. However I have no experience, at all. 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.

junkcollector 9y ago
Summing multiple measurements will grow the noise at the rate of the sum of the squares (also called the 2 norm) because noise is hopefully uncorrelated. The signal, because it is correlated, will sum simply so that with enough measurements your SNR will increase. These measurements can be done in space or time.
lowpro 9y ago
We did think of mufflers, but we didn't have them as we were using a dataset collected by another researcher, who used the same system in a quiet environment, then in a windy 'real world' environment. We used this data for training, testing and validation, but didn't have the equipment or time to make a new dataset :( 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.
- junkcollector 9y ago
  From a purely signal point of view, if you have a good characterization of the drone sound (your training set) and of the noise, then the appropriate filter would be something along the lines of a weiner type which statistically maximizes the SNR. Preventing your microphone from saturating when measuring the wind is very important as well, and a good use of a wind blocker or muffler. If your microphone saturates its input that will distort the spectrum of the signal you are measuring.

junkcollector 9y ago

Summing multiple measurements will grow the noise at the rate of the sum of the squares (also called the 2 norm) because noise is hopefully uncorrelated. The signal, because it is correlated, will sum simply so that with enough measurements your SNR will increase. These measurements can be done in space or time.

lowpro 9y ago

We did think of mufflers, but we didn't have them as we were using a dataset collected by another researcher, who used the same system in a quiet environment, then in a windy 'real world' environment. We used this data for training, testing and validation, but didn't have the equipment or time to make a new dataset :( 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.

junkcollector 9y ago
From a purely signal point of view, if you have a good characterization of the drone sound (your training set) and of the noise, then the appropriate filter would be something along the lines of a weiner type which statistically maximizes the SNR. Preventing your microphone from saturating when measuring the wind is very important as well, and a good use of a wind blocker or muffler. If your microphone saturates its input that will distort the spectrum of the signal you are measuring.