Angle of arrival measurement using wideband linear phased array

Liou, L.L.; Lin, David M.; Tsui, J.B.Y.; Buck, J.; Longbrake, Matthew B.; McCann, Joshua C; Buxa, Peter; Dalrymple, Thomas

doi:10.1109/naecon.2009.5426635

Cited by 4 publications

(6 citation statements)

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“…Characterization and identification of the threat signals by bounding the angle of arrival (AOA) to specific interval enables location of the source of threat signal [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…This channelization can be implemented to have wideband coverage [2]. For a phased array system, implementation requires similar set of components following each antenna element, which may be impractical.…”

Section: Introductionmentioning

confidence: 99%

“…For a phased array system, implementation requires similar set of components following each antenna element, which may be impractical. This system needs a controller to scan through channels to function as a wideband receiver [2]. Phased array receiver system is the extensively used modern day technology.…”

Section: Introductionmentioning

confidence: 99%

“…Phased array receiver system is the extensively used modern day technology. The multiple antenna elements provide not only the spatial-temporal capability, but also an extra gain due to coherence and less confounding compared to single antenna receiver system [2].…”

Section: Introductionmentioning

confidence: 99%

“…Likewise, the peak FFT component in the spatial FFT bin contains the direction and power information of the input signal. Applications involving direction surveillance, the phased array is usually scanned through a range of positive and negative angles [2]. Applications involving direction surveillance, the phased array is usually scanned through a range of angles.…”

Section: Introductionmentioning

confidence: 99%

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Hyper-fuzzy modeling and control for bio-inspired radar processing

Salim

Abdel-Aty-Zohdy

Zohdy

2010

Proceedings of the IEEE 2010 National Aerospace &Amp; Electronics Conference

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Modern RF Radar signal processing has been receiving much attention for wide range of domains that include industrial, environmental, and military applications.Inherently, the received raw spatial-temporal signals can be 1-D, 2-D, or 3-D and are usually of uncertain nature, because of changing conditions and optical background variations. In this paper, we apply novel concepts for hyper-neural theory that allow for incorporation of variables attribute definitions and uncertainties for the purpose of effective evidential learning and subsequent key output features determination in the radar processing. Application to wide-band angle of arrival data sets at several carrier frequencies has been carried out in order to illustrate the strengths as well weakness of the approach. Using interval set-based operations together with segmentation of the data is proved useful and gave good sensitivity of detection.

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“…Characterization and identification of the threat signals by bounding the angle of arrival (AOA) to specific interval enables location of the source of threat signal [1,2].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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