Array processing

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

• Enhance the signal-to-interference-plus-noise ratio (SINR) compared to that of a single sensor using conventional or adaptive beamforming.
• Determine the number of emitting sources, the locations of these sources, their waveforms, and other signal parameters.
• Track multiple moving sources.

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]

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.^[2]

See also

• Phased Array
• Space Time Adaptive Processing

References

1. Torlak, M. Spatial Array Processing. Signal and Image Processing Seminar. University of Texas at Austin.
2. Torlak, M. Spatial Array Processing. Signal and Image Processing Seminar. University of Texas at Austin.

• 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: 67–94. 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