Application of APES to Adaptive Arrays on the CDMA Reverse Channel

Russell, Debbie J. F.; Palmer, Robert D.

doi:10.1109/tvt.2003.821991

Cited by 12 publications

(2 citation statements)

References 25 publications

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“…18 It is based on an adaptive narrowband filter-bank centered at the frequencies of interest. The approach was first introduced by Guo et al 16 to investigate data from borehole acoustic arrays.…”

Section: Velocity and Dispersion Processing Methods: A Reviewmentioning

confidence: 99%

Phase-based dispersion analysis for acoustic array borehole logging data

Assous

Elkington

Linnett

2014

The Journal of the Acoustical Society of America

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A phase-based dispersion analysis method for velocity (slowness) extraction from guided waves recorded by an acoustic borehole logging tool in a geological formation is presented. The technique consists of acquiring waveforms from an array of receivers distributed along the tool and constructing the dispersion characteristic by processing in the frequency domain and exploiting phase information to measure the travel time for each frequency component. The approach is nonparametric and completely data-driven and provides high resolution estimates that do not rely on velocity guesses or assumptions regarding the type of modes. Results are free of the aliases and spurious modes which are characteristic of some prior approaches. Examples of dispersion estimation curves are presented using synthesized flexural waves and field data from wireline dipole sonic tools; results are compared with those from the weighted spectral semblance (WSS) and amplitude and phase slowness estimation (APES) methods to demonstrate the effectiveness and utility of the proposed method.

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Section: Velocity and Dispersion Processing Methods: A Reviewmentioning

confidence: 99%

Phase-based dispersion analysis for acoustic array borehole logging data

Assous

Elkington

Linnett

2014

The Journal of the Acoustical Society of America

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“…is required. Amplitude and phase estimator (APES) is suggested in [17] and [18], which can accurately locate multiple sources using multiple snapshots. Although these methods can obtain accurate DOA estimation in the case of high signal-to-noise ratio (SNR) or numerous snapshots, their computational complexity is very high.…”

Section: Introductionmentioning

confidence: 99%

Non-Iterative DOA Estimation Using Discrete Fourier Transform Interpolation

Chen

Tam³

et al. 2019

IEEE Access

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A fast and accurate non-iterative direction-of-arrival (DOA) estimation algorithm for multiple targets in additive white Gaussian noise is devised in this paper. The proposed estimator makes use of the two highest magnitudes discrete Fourier transform (DFT) coefficients of the input data and two of their associated neighboring bins, resulting in a deterministic complexity of O(N (1 + log(N ))) with N being the number of sensors. The bias and mean squares error of the DOA estimates are analyzed. The simulation results are presented to validate the correctness of theoretical derivation and demonstrate the superiority of the devised estimator over several conventional DOA estimators.

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Adaptive Array Beamforming for Interference Mitigation for GRFS Systems

Progri¹

2011

Geolocation of RF Signals

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Application of APES to Adaptive Arrays on the CDMA Reverse Channel

Cited by 12 publications

References 25 publications

Phase-based dispersion analysis for acoustic array borehole logging data

Phase-based dispersion analysis for acoustic array borehole logging data

Non-Iterative DOA Estimation Using Discrete Fourier Transform Interpolation

Adaptive Array Beamforming for Interference Mitigation for GRFS Systems

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