Why is directional noise correlated noise?

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In summary, the paper says that if there is directional noise in a room, then the noise at the two microphones is correlated. However, the directionality is not what's causing the correlation, but more the fact that the noise comes from a fan. Additionally, to mathematically describe noise that comes from a point source (described here as "directional"), treat it as if it were just another signal source term, albeit an undesirable one.
  • #1
CantorSet
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Hi everyone,

This is not a homework question but I question I have from reading a signals processing paper on acoustics.

Suppose there is a sound source in a room [tex]S(t)[/tex] and two microphones [tex]X_1(t)[/tex] and [tex]X_2(t)[/tex]. Then the standard acoustic propagation model has that

[tex] X_1(t) = a_1S(t-\tau_1)+n_1(t) [/tex]

and

[tex] X_2(t) = a_2S(t-\tau_1)+n_2(t) [/tex]

where [tex]a_i, \tau_i, n_i [/tex] account for signal attenuation due to distance, time delay due to distance and noise, respectively.

But the paper says that if we have directional noise in the room (like a ceiling fan), then the noise at the two microphones is correlated, that is [tex] Corr(n_1(t),n_2(t)) \neq 0 [/itex].

But it seems to me the directionality isn't what's causing the correlation, but more the fact that the noise comes from a fan. That is, if we had an "omnidirectional" fan in the center of the room, the noise between the two microphones would still be correlated.

Also, how does one mathematically represent noise that is directional?
 
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  • #2
In this context, I'd have to assume that by "directional", they simply mean the sound has one point source, as you say (and not that it is anisotropic!). On a side note, practically speaking there will be notable multipath, making things more difficult.

By the way, that Tau in the second equation should be tau sub 2, not Tau sub 1 (unless the microphones are the same distance from the sound source)

To mathematically describe noise that comes from a point source (described here as "directional"), treat it as if it were just another signal source term, albeit an undesirable one.
 
  • #3
fleem said:
In this context, I'd have to assume that by "directional", they simply mean the sound has one point source, as you say (and not that it is anisotropic!). On a side note, practically speaking there will be notable multipath, making things more difficult.

By the way, that Tau in the second equation should be tau sub 2, not Tau sub 1 (unless the microphones are the same distance from the sound source)

To mathematically describe noise that comes from a point source (described here as "directional"), treat it as if it were just another signal source term, albeit an undesirable one.

Thanks for your help, Fleem.
 

1. Why is directional noise correlated noise?

Directional noise is correlated noise because it exhibits a specific pattern or direction in its fluctuations. This means that the noise is not randomly distributed, but rather has a consistent relationship between its values at different points in space or time. This correlation can be observed through statistical analysis, where the noise values at different points are found to be related in some way.

2. What causes directional noise?

Directional noise can be caused by a variety of factors, including physical phenomena such as wind or water currents, electronic interference, or even human activities. In many cases, directional noise is a result of some type of movement or flow, where the noise is carried along with the movement and exhibits a consistent directionality.

3. How does directional noise affect data analysis?

Directional noise can significantly impact data analysis, as it introduces a systematic bias into the data. This means that the noise is not evenly distributed and can skew the results of statistical analysis. If directional noise is not properly accounted for, it can lead to incorrect conclusions or interpretations of the data.

4. Can directional noise be removed or reduced?

In some cases, directional noise can be removed or reduced through filtering techniques. This involves identifying the directionality of the noise and applying filters or algorithms that specifically target and remove it. However, in other cases where the noise is inherent in the system or cannot be easily identified, it may be difficult to completely eliminate directional noise.

5. How can directional noise be accounted for in scientific experiments?

To account for directional noise in scientific experiments, researchers must first identify its presence and directionality. This can be done through careful data analysis and statistical techniques. Once the noise is identified, it can be accounted for by applying appropriate filters or adjustments to the data. It is also important for researchers to acknowledge and report any potential directional noise in their findings to ensure transparency and accuracy in their results.

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