Array processing

Article summary

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) or "signal-to-interference-plus-noise ratio (SINR)" * track moving sources Array processing metrics are often assessed in noisy environments. The model for noise may be either one of spatially incoherent noise, or one with interfering signals following the same propagation physics.…

Key claims

1. date of foundation: 1968 — source: Wikipedia · confidence 0.95

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Bibliography

1. Wikipedia https://en.wikipedia.org/w/index.php?oldid=1378292740