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B How is noise removed in radio telescopes?

  1. May 22, 2018 #21

    Drakkith

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    No idea. I've never heard of that before. Sorry!
     
  2. May 22, 2018 #22
    I agree with Drakkith. The term noise is as commonly, widely and horribly misused in astrophotography to a similar extent of the the common practice of using the kg to measure weight is in everyday usage.

    All relevant signals when it comes digital sensors in astronomy are modeled as stochastic processes with a Poisson distribution. This means that the signal is equal to the number of photons/electrons detected by the sensor (this relates to the Nobel Price Einstein did receive on the photoelectric effect) and the noise is thus equal the square root of the signal (in statistics terms the noise is the variance of the signal).

    The main three signals are:
    1. Bias/offset/pedestal signal - a small constant signal added by the sensor circuits to every exposure to make sure the final number can't become negative.
    2. Dark current signal - electrons leaking into the "pixels" over time which is accelerated greatly by higher sensor temperatures. This is why serious astrocameras are both chilled and temperature regulated (to keep the variation down).
    3. Light signal - all the actual photons your sensor detects (or in the case of Vigenetting, photons it fails to detect but can be measured/modeled). This includes:
    + The actual object you want to observe
    + Cosmic rays
    + Vigenetting, dust bunnies, etc.
    + Zodiacal light
    + Air glow/Aurora
    + Atmospheric dispersion of light sources
    + Reflections/dispersion due to (nearby or not) light sources reaching the sensor even though they shouldn't due to the properties of the optics
    + Light pollution
    + Aircraft and satellite trails
    + other stuff I forgot to mention

    In serious astrocameras the digital output has a "unity" gain, this means that the ADU (Analog-Digital Units), more commonly known as the pixel value, is equal to the the number of electrons detected from all sources. Only the electrons from 3 are actually due to photons and you'd ideally want to avoid having to bother with both the spurious electrons from case 1/2 and many of the photons (you are after all only interested in the photons from the objects you want to observe) from case 3.

    There are limits in what we can do to avoid detecting the spurious electrons from 1 and 2 but in most relevant cases 1 only matters if your exposures are too short (and the signal but not the noise can be removed using bias frames) and 2 can be limited by cooling the sensor and if the temperature is steady you can easily remove the signal (but again not the noise) by using dark frame subtraction.

    For case 3 some of the signals can be reduced (and thus their inherent noise) by placing the telescope in the right spot (say high and dark), taking the image at the right time (no moon overhead, no aurora), using filters (very narrow-band filters works even from some of the most light polluted areas (I've seen amazing narrow-band images from amateurs in Rome and Athens)), etc. If the signal you want to avoid ever hits the sensor the best you might be able to do is to measure or model it (flat frames, background subtraction, etc.) but then you are again left with removing just the signal and not the noise.

    The techniques used to stack sub-exposures (average, median, Sigma-Kappa, etc.) then also have a impact on how the noise and spurious signals are controlled.
     
    Last edited: May 22, 2018
  3. May 22, 2018 #23

    davenn

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    Drakkith and you have said this several times and I really cannot make sense of what you are driving at ??
    You are not defining what you mean by the difference in terms of signal and noise
    How can you remove signal without removing the noise ? The noise IS a signal, just an unwanted one
     
  4. May 22, 2018 #24
    Again:
    All relevant signals when it comes digital sensors in astronomy are modeled as stochastic processes with a Poisson distribution. This means that the signal is equal to the number of photons/electrons detected by the sensor (this relates to the Nobel Price Einstein did receive on the photoelectric effect) and the noise is thus equal the square root of the signal (in statistics terms the noise is the variance of the signal).
     
  5. May 22, 2018 #25
    If this is enough you really need to look into the math of signal processing or at least a beginners book on astrophotography like "Making Every Photon Count" or similar. Just like kilograms and Newtons the terms signal and noise has precise technical definitions.

    The area involves mostly some specialized university level statistics (statistical processes), some knowledge about the workings of the photo electric effect and the design of digital senors and some rather basic signal processing. Still it is a much to large field to summarize in just a few pages. If you can read Swedish I have a summery on astronet.se of what I perceive as the absolute basic concepts.
     
    Last edited: May 22, 2018
  6. May 22, 2018 #26

    Drakkith

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    Sure we are. Noise is the random variation in the signal away from a theoretical 'ideal' value. If I take an image of a star and count the number of electrons generated in the sensor's pixels by that star's light, I'll get some value, X. I then take another identical image and count the electrons again. This time X is a bit more or less than before. I then take another identical image and do the same thing, again getting a slightly different value for X. Let's say I continue to take images and I also average the values after each image to get the mean electron count, Y. As the number of images taken increases towards infinity, Y approaches some particular value, which I'll call the signal's theoretical perfect value. This theoretical perfect value is the value I'd get for each X in a world without any sources of noise. But noise causes X to vary around Y's value in each image.

    Is that any clearer?
     
  7. Jun 5, 2018 #27

    JMz

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    "MAXENT" or "MEM" (maximum entropy method) processing has been used for decades in astronomy. As I recall, it was key to producing high-quality Hubble images before the optical defect in Hubble was fixed. Typically, it produces resolution improvements by 2x or so.

    Having said that, I do not know when, or for what kinds of imagery, it is commonly used now. Because the processing is nonlinear, I suspect people usually do not distribute MAXENT-processed data for further scientific analysis; they would expect that the user-scientists will apply whatever method is optimal for the research of interest (which may not be MAXENT).
     
  8. Jun 12, 2018 #28

    sophiecentaur

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    The thread has gone a bit off topic I think because the title is to do with Radio Telescopes. Nontheless, very similar basic processes are involved. If you know something about the nature of the signal you are looking for then life is much easier than if you are just 'listening'. In general, a Wanted Signal has some structure and it will have some degree of self corellation and that can be spotted against truly random noise, which has zero self corellation. radio astronomers have one big advantage over optical astronomers in that the signals they are receiving can be analysed in terms of amplitude and phase whereas received light can only be observed in terms of its amplitude. (Numbers of Photons per second)
     
  9. Jun 12, 2018 #29

    JMz

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    Yes, indeed! The same is true in acoustics, and for the same reason. The closest we can come in optics is probably holography, because that provides at least some phase information. But optical frequencies are simply to high to sample the waveform in real time and construct the phase information.
     
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