page_title: Array processing
section_title: Example: spatial filtering
hierarchical_section_title: Array processing / Example: spatial filtering
caption_attribution_description: English: An array of radio telescopes with an incoming radio wave and RF interference
context_page_description: Array processing is a wide area of research in the field of signal processing that extends from the simplest form of 1 dimensional line arrays to 2 and 3 dimensional array geometries. Array structure can be defined as a set of sensors that are spatially separated, e.g. radio antenna and seismic arrays. The sensors used for a specific problem may vary widely, for example microphones, accelerometers and telescopes. However, many similarities exist, the most fundamental of which may be an assumption of wave propagation. Wave propagation means there is a systemic relationship between the signal received on spatially separated sensors. By creating a physical model of the wave propagation, or in machine learning applications a training data set, the relationships between the signals received on spatially separated sensors can be leveraged for many applications.
  Some common problem that are solved with array processing techniques are:
  determine number and locations of energy-radiating sources
  enhance the signal to noise ratio SNR "signal-to-interference-plus-noise ratio"
  track moving sources
  Array processing metrics are often assessed noisy environments.
context_section_description: In radio astronomy, RF interference must be mitigated to detect and observe any meaningful objects and events in the night sky.
caption: An array of radio telescopes with an incoming radio wave and RF interference
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