Sound Source Localization in a Multipath Environment Using Convolutional Neural Networks

The propagation of sound in a shallow water environment is characterized by boundary reflections from the sea surface and sea floor. These reflections result in multiple (indirect) sound propagation paths, which can degrade the performance of passive sound source localization methods. This paper proposes the use of convolutional neural networks (CNNs) for the localization of sources of broadband acoustic radiated noise (such as motor vessels) in shallow water multipath environments. It is shown that CNNs operating on cepstrogram and generalized cross-correlogram inputs are able to more reliably estimate the instantaneous range and bearing of transiting motor vessels when the source localization performance of conventional passive ranging methods is degraded. The ensuing improvement in source localization performance is demonstrated using real data collected during an at-sea experiment.Comment: 5 pages, 5 figures, Final draft of paper submitted to 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 15-20 April 2018 in Calgary, Alberta, Canada. arXiv admin note: text overlap with arXiv:1612.0350

Antenna array calibration in wireless communications

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Space time transceiver design over multipath fading channels

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A class of constant modulus algorithms for uniform linear arrays with a conjugate symmetric constraint

A class of constant modulus algorithms (CMAs) subject to a conjugate symmetric constraint is proposed for blind beamforming based on the uniform linear array structure. The constraint is derived from the beamformer with an optimum output signal-to-interference-plus-noise ratio (SINR). The effect of the additional constraint is equivalent to adding a second step to the original adaptive algorithms. The proposed approach is general and can be applied to both the traditional CMA and its all kinds of variants, such as the linearly constrained CMA (LCCMA) and the least squares CMA (LSCMA) as two examples. With this constraint, the modified CMAs will always generate a weight vector in the desired form for each update and the number of adaptive variables is effectively reduced by half, leading to a much improved overall performance. (C) 2010 Elsevier B.V. All rights reserved

The JDTDOA algorithm applied to signal recovery : a performance analysis

This article suggests a novel method to retrieve a narrowband signal sent in a multipath environment with a delay spread considering ISI between symbols. The proposed method does not require any preamble nor known signal. Using the joint direction and time delay of arrivals estimation algorithm developed in prior work, the directions and time delays of arrival in the multipath channel are jointly estimated and associated while keeping a low computational cost. In this process, a MVDR beamformed copy of each arriving signal is created. The quality of these “pseudo copies” is evaluated and compared to the original direct and reflected signals in this work. Another beamforming method, the Moore–Penrose pseudoinverse, with better retrieval of the direct and reflected signals is also proposed. Using a simple delay-and-sum operation on the previously beamformed copies, it is possible to substantially improve the the system’s performance in terms of bit error rate. An approach using oversampling on the array antenna is introduced to improve performance. Numerical simulations are discussed to support theory