Fundamentals of digital array processing

Dudgeon, Dan E.

doi:10.1109/proc.1977.10587

Cited by 136 publications

(55 citation statements)

References 23 publications

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“…Works [16], [17] discussed spatial aliasing effects for the case of linear arrays. Spatial aliasing in linear arrays prevented localization of all sources.…”

Section: Criteriamentioning

confidence: 99%

Lung sound localization using array of acoustic sensors

Salehin

Abhayapala

2008

2008 2nd International Conference on Signal Processing and Communication Systems

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Abstract-This paper presents a localization algorithm to detect lung sounds using an circular array of microphones. We use the natural basis functions of propagation waves in height invariant wavefields to form a spatial minimum variance (MV) problem in eigen space. We also derive a Nyquist criteria for localizing sources within a circular. Further, the Nyquist criteria shows that the radius of the region where sources can be localized is inversely proportional to the frequency of sound. The modified Nyquist criteria can be used for determining the number of sensors required for a required resolution, frequency range, and radius of the region for which sources need to be localized. The results are corroborated by computer simulations.

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“…Works [16], [17] discussed spatial aliasing effects for the case of linear arrays. Spatial aliasing in linear arrays prevented localization of all sources.…”

Section: Criteriamentioning

confidence: 99%

Lung sound localization using array of acoustic sensors

Salehin

Abhayapala

2008

2008 2nd International Conference on Signal Processing and Communication Systems

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“…This will occur when the rejection response I~(w) I is as close as possible to an ideal rejection response which consists of a train of impulses located at frequencies which correspond to integer multiples of the ratio of the element spacing on the array to the signal wavelength. [3].…”

Section: Beamforming Transducer Arraymentioning

confidence: 99%

Nondestructive Evaluation with Beamforming Transducer Arrays

Simaan

1983

Review of Progress in Quantitative Nondestructive Evaluation

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“…However, the higher latency of such frequency-domain methods is not well suited to real-time adaptive applications. Time-domain broadband beamforming methods [6,12,22,23,33] have mostly been derived from the early basic delay-and-sum concept [7] and, although they can be adapted in real time, the errors between the required exact time delays and the corresponding realized approximate time delays typically cause considerable distortion of the desired beamformed signal [17,18,22]. As a remedy, frequency-invariant broadband beamforming methods [25,26,[31][32][33] have been proposed, which extrapolate the conventional narrowband beamformer design methods at several different temporal frequencies over the desired frequency band using iterative optimization techniques.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Complex-Coefficient 2D FIR Trapezoidal Filters for Broadband Beamforming in Cognitive Radio Systems

Gunaratne

Bruton

2010

Circuits Syst Signal Process

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A novel design method is proposed for an adaptive discrete-domain beamformer for the beamforming of temporally broadband-bandpass signals in cognitive radio (CR) systems. The method is based on a complex-coefficient 2D finite impulse response (FIR) filter having a trapezoidal-shaped passband. The temporally broadband-bandpass signals are received by a 1D uniformly distributed antenna array (1D UDAA), where the outputs of the antennas are complex-quadrature sampled by the front end of the CR system. This CR system is based on a software defined radio (SDR) architecture and can be instantly reconfigured by the control system to select the appropriate frequency band and the required sampling rate. The subsequent beamforming enhances the spectral components of the desired temporally broadbandbandpass signals by arranging for the asymmetric trapezoidal-shaped passband of the 2D filter transfer function to closely enclose the region of support (ROS) of the spectrum of the desired signal, whereas the ROSs of the spectral components of the interfering signals are enclosed by the stopband. The proposed novel closed-form design method facilitates instant adaptation of the shape and orientation of the passband of the beamforming 2D FIR trapezoidal filter in order to match the time-varying frequency band and the time-varying bandwidth of the signal, as well as to track and enhance received signals with time-varying directions of arrival (DOAs). Simulated results confirm that, compared with previously reported methods, the proposed method achieves the best overall tradeoff with respect to the instantaneous adaptations of the operating frequency band, the bandwidth, and the time-varying DOAs, the distortion of the desired passband signal, and the stopband attenuation of interfering signals.

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Fundamentals of digital array processing

Cited by 136 publications

References 23 publications

Lung sound localization using array of acoustic sensors

Lung sound localization using array of acoustic sensors

Nondestructive Evaluation with Beamforming Transducer Arrays

Adaptive Complex-Coefficient 2D FIR Trapezoidal Filters for Broadband Beamforming in Cognitive Radio Systems

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