Paper
12 May 2016 Investigation of correlation characteristics for random array collaborative beamforming using noise signals
David B. Alexander, Ram M. Narayanan, Braham Himed
Author Affiliations +
Abstract
The performance of different random array geometries is analyzed and compared. Three phased array geometries are considered: linear arrays with non-uniform randomized spacing between elements, circular arrays with non-uniform element radii, and ad hoc sensor networks with elements located randomly within a circular area. For each of these array geometries, computer simulations modeled the transmission, reflection from an arbitrary target, and reception of signals. The effectiveness of each array’s beamforming techniques was measured by taking the peak cross-correlation between the received signal and a time-delayed replica of the original transmitted signal. For each array type, the correlation performance was obtained for transmission and reception of both chirp waveforms and ultra-wideband noise signals. It was found that the non-uniform linear array generally produced the highest correlation between transmitted and reflected signals. The non-uniform circular and ad hoc arrays demonstrated the most consistent performance with respect to noise signal bandwidth. The effect of scan angle was found to have a significant impact on the correlation performance of the linear arrays, where the correlation performance declines as the scan angle moves away from broadside to the array.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David B. Alexander, Ram M. Narayanan, and Braham Himed "Investigation of correlation characteristics for random array collaborative beamforming using noise signals", Proc. SPIE 9829, Radar Sensor Technology XX, 98290I (12 May 2016); https://doi.org/10.1117/12.2224208
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Cited by 1 scholarly publication.
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KEYWORDS
Interference (communication)

Radar

Antennas

Signal attenuation

Phased arrays

Analytical research

Sensor networks

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