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Array processing

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Array processing is signal processing of the outputs of an array of sensors to:

Array processing is used in radar, sonar, seismic exploration, anti-jamming and wireless communications. One of the main advantages of using array processing along with an array of sensors is a smaller foot-print. The problems associated with array processing include the number of sources used, their direction of arrivals, and their signal waveforms.[1][2][3][4]

There are four assumptions in array processing. The first assumption is that there is uniform propagation in all directions of isotropic and nondispersive medium. The second assumption is that for far field array processing, the radius of propagation is much greater than size of the array and that there is plane wave propagation. The third assumption is that there is a zero mean white noise and signal, which shows uncorrelation. Finally, the last assumption is that there is no coupling and the calibration is perfect.[1]

Applications

In radio astronomy because of background noise from modern communications it is difficult to achieve a good signal to noise ratio. Even for strong astronomical radio emission it is typical for SNR levels to be below 0 decibel. To counter this problem exposure of the antenna to the source over large periods of time are needed just as in visible sky viewing. Array gain is done by using multiple, even dozens of radio receivers to collect as much signal as possible.

NORSAR is an independent geo-scientific research facility that was founded in Norway in 1968. NORSAR has been working with array processing ever since to measure seismic activity around the globe.[5] They are currently working on an International Monitoring System which will comprise 50 primary and 120 auxiliary seismic stations around the world. NORSAR has ongoing work to improve array processing to improve monitoring of seismic activity not only in Norway but around the globe.[6]

See also

References

  1. ^ a b Torlak, M. Spatial Array Processing. Signal and Image Processing Seminar. University of Texas at Austin.
  2. ^ J Li, P Stoica (Eds) (2009). MIMO RADAR SIGNAL PROCESSING. USA: J Wiley&Sons.
  3. ^ P Stoica, R Moses (2005; Chinese Edition, 2007). SPECTRAL ANALYSIS OF SIGNALS (PDF). NJ: Prentice Hall. {{cite book}}: Check date values in: |year= (help)CS1 maint: year (link)
  4. ^ J Li, P Stoica (Eds) (2006). ROBUST ADAPTIVE BEAMFORMING. USA: J Wiley&Sons.
  5. ^ http://www.norsar.no/
  6. ^ "Improving IMS array processing". Norsar.no. Retrieved 2012-08-06.

Sources

  • Johnson, D. H.; Dudgeon, D. E. (1993). Array Signal Processing. Prentice Hall.
  • Van Trees, H. L. (2002). Optimum Array Processing. New York: Wiley.
  • Krim, H.; Viberg, M. (1996). "Two Decades of Array Signal Processing Research" (PDF). IEEE Signal Processing Magazine: 67โ€“94. Retrieved 8 December 2010. {{cite journal}}: Unknown parameter |month= ignored (help)
  • S. Haykin and K.J.R. Liu (Editors), "Handbook on Array Processing and Sensor Networks", Adaptive and Learning Systems for Signal Processing, Communications, and Control Series, 2010.
  • E. Tuncer and B. Friedlander (Editors), "Classical and Modern Direction-of-Arrival Estimation", Academic Press, 2010.
  • A.B. Gershman, array processing courseware