Timeline for Reducing noise from the same frequency band as signal
Current License: CC BY-SA 3.0
34 events
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| Apr 29, 2019 at 8:10 | answer | added | rmac | timeline score: 1 | |
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| Apr 2, 2018 at 23:18 | answer | added | user28715 | timeline score: 0 | |
| S Mar 25, 2018 at 12:50 | history | bounty ended | CommunityBot | ||
| S Mar 25, 2018 at 12:50 | history | notice removed | CommunityBot | ||
| Mar 22, 2018 at 22:18 | answer | added | Filipe Pinto | timeline score: 0 | |
| Mar 20, 2018 at 21:46 | answer | added | Mark Borgerding | timeline score: 1 | |
| Mar 18, 2018 at 4:14 | comment | added | AnonSubmitter85 | Is there a model for generating the recorded signal? For example, can the "probing" be represented as a linear operator? | |
| Mar 17, 2018 at 23:16 | comment | added | LDPC | That is my impression as well. The pictures, however, are a poor choice (see my new EDIT). This is the performance we want to keep, with an SNR 10 to 100 times worse. I get there is not much room to play around since the only distinction of signal and noise are statistics (so I'm not even sure it is possible). | |
| Mar 17, 2018 at 23:15 | history | edited | LDPC | CC BY-SA 3.0 |
added 532 characters in body
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| Mar 17, 2018 at 21:20 | comment | added | Laurent Duval | The noise looks apparently so low on both domains.So most removal methods would probably result in minor SNR improvements | |
| Mar 17, 2018 at 16:46 | comment | added | LDPC | The signal is random, in the sense that there is no way to predict it. It functions somehow as a "fingerprint" of the sensing element, but without probing it first it is impossible to know the response of the system (with noise). Successive measurements, assuming no change in environmental conditions, will retrieve the same "noise-like" signal, though. Any perturbation will cause the signal to delay itself at some short section and suffer some deformation. | |
| Mar 17, 2018 at 16:25 | comment | added | AnonSubmitter85 | You said the signal resembles noise, but is it truly random? Is there any information about the system that generates the signal? For instance, can it be modeled as a linear operator? | |
| Mar 17, 2018 at 14:29 | comment | added | LDPC | It's also notable that I simulated a case with what we use as standard right now. So, we are happy with that performance. However, we would like to keep it for lower spatial resolutions (thus, smaller correlation window and worse SNR). Hence the question. | |
| Mar 17, 2018 at 14:24 | comment | added | LDPC | The measurement is one of local time delay and it is bounded by the Cramer Rao Lower Bound. The CRLB is a function of SNR, bandwidth and time window for correlation. Due to the way the system itself works and the way its sensitivity scales with these parameters as well, it ends up ultimately being limited by SNR and the correlation window. However, a larger correlation window is undesirable, as it affects the spatial resolution of our system. We want to reduce the size of the correlation window and attempt to maintain (or avoid losing too much) sensitivity, by processing, if possible. | |
| Mar 17, 2018 at 14:15 | comment | added | Cris Luengo | Looking at your first plot, I cannot imagine that the noise would affect any quantification you'd do with the signal. Where does the signal come from, what do you want to do with it, and why is this small amount of noise problematic? | |
| Mar 17, 2018 at 11:29 | comment | added | Royi | Both the Signal and Noise goes through the same filter? | |
| Mar 17, 2018 at 11:11 | history | tweeted | twitter.com/StackSignals/status/974966454415216640 | ||
| S Mar 17, 2018 at 11:09 | history | bounty started | Rodrigo de Azevedo | ||
| S Mar 17, 2018 at 11:09 | history | notice added | Rodrigo de Azevedo | Canonical answer required | |
| S Mar 15, 2018 at 10:06 | history | suggested | VMMF | CC BY-SA 3.0 |
Just English details
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| Mar 15, 2018 at 1:30 | review | Suggested edits | |||
| S Mar 15, 2018 at 10:06 | |||||
| Mar 15, 2018 at 1:28 | comment | added | VMMF | Very interesting question! If you could get independent samples from the noise source I think you could use an adaptive filter | |
| Mar 14, 2018 at 16:17 | comment | added | LDPC | For a matched filter, wouldn't I need to know my uncorrupted signal beforehand? The case I presented was a simulation. In general, I only have noisy signals after the acquisition. | |
| Mar 14, 2018 at 15:09 | history | asked | LDPC | CC BY-SA 3.0 |