Quadratically Constrained Beamforming Robust Against Direction-of-Arrival Mismatch

It is well known that the performance of the minimum variance distortionless response (MVDR) beamformer is very sensitive to steering vector mismatch. Such mismatches can occur as a result of direction-of-arrival (DOA) errors, local scattering, near-far spatial signature mismatch, waveform distortion, source spreading, imperfectly calibrated arrays and distorted antenna shape. In this paper, an adaptive beamformer that is robust against the DOA mismatch is proposed. This method imposes two quadratic constraints such that the magnitude responses of two steering vectors exceed unity. Then, a diagonal loading method is used to force the magnitude responses at the arrival angles between these two steering vectors to exceed unity. Therefore, this method can always force the gains at a desired range of angles to exceed a constant level while suppressing the interferences and noise. A closed-form solution to the proposed minimization problem is introduced, and the diagonal loading factor can be computed systematically by a proposed algorithm. Numerical examples show that this method has excellent signal-to-interference-plus-noise ratio performance and a complexity comparable to the standard MVDR beamformer

A Novel Beamformer Robust to Steering Vector Mismatch

It is well know that the performance of the minimum variance distortionless response (MVDR) beamformer is very sensitive to steering vector mismatch because of the signal cancellation. Such mismatches can occur as a result of direction-of arrival (DOA) errors, local scattering, near-far spatial signature mismatch, waveform distortion, source spreading, imperfectly calibrated arrays and distorted antenna shape. In this paper, an adaptive beamformer which is robust against the DOA mismatch is proposed. This method imposes two quadratic constraints such that the magnitude responses of two steering vectors exceed unity. Then a diagonal loading method is used to force the magnitude responses within a range of the arrival angles to exceed unity. The diagonal loading factor can be computed systematically by a proposed algorithm. Numerical examples show that this method has a significantly better SINR performance compared to previously published methods (including the MVDR), and a complexity comparable to the standard MVDR beamformer

Acoustic pressure and particle velocity for spatial filtering of bottom arrivals

This paper discusses the advantages of using a combination of acoustic pressure and particle velocitymotion for filtering bottom arrivals. A possible area of application is reflection seismology where, traditionally, the seismic image is extracted from the bottom-reflected broadband acoustic signals received on hydrophones. Since hydrophones are omnidirectional in nature, the received bottom returns are often contaminated by waterborne signals, sea surface reflections, and noise. A substantial part of the processing of the data is dedicated to filtering out these unwanted signals. Today, vector sensors allow us to measure both acoustic pressure and particle velocity motion in a single and compact sensor. The combination of pressure and particle velocity measured at a single location or particle velocity and particle velocity gradient at closely spaced locations allows for spatial beam steering to predetermined directions and filter out unwanted replicas from other directions. Moreover, this can be done at the sensor level, dramatically decreasing the offline processing. The spatial filtering capabilities of various pressure-pressure, particle velocity-particle velocity, and pressure-particle velocity combinations are analyzed in view of filtering the bottom arrivals. It is shown that the combination of pressure and vertical particle velocity and, particularly, the combination of vertical particle velocity and particle velocity gradient enhance bottom arrivals. Moreover, a simple steering procedure combining pressure and particle velocity components of a triaxial sensor allows us to determine the tridimensional structure of the acoustic field and the separation of the bottom reflections. The spatial selectivity of the various sensor combinations is shown with simulations and verified with experimental data acquired with 10 cm separated vector sensors in the 800-1250-Hz band, during the Makai 2005 sea trial, off Kauai Island, HI, USA.This work was supported by the European Union H2020 Research Program under WiMUST Project (Contract 645141).info:eu-repo/semantics/publishedVersio

Signals and Images in Sea Technologies

Life below water is the 14th Sustainable Development Goal (SDG) envisaged by the United Nations and is aimed at conserving and sustainably using the oceans, seas, and marine resources for sustainable development. It is not difficult to argue that signals and image technologies may play an essential role in achieving the foreseen targets linked to SDG 14. Besides increasing the general knowledge of ocean health by means of data analysis, methodologies based on signal and image processing can be helpful in environmental monitoring, in protecting and restoring ecosystems, in finding new sensor technologies for green routing and eco-friendly ships, in providing tools for implementing best practices for sustainable fishing, as well as in defining frameworks and intelligent systems for enforcing sea law and making the sea a safer and more secure place. Imaging is also a key element for the exploration of the underwater world for various scopes, ranging from the predictive maintenance of sub-sea pipelines and other infrastructure projects, to the discovery, documentation, and protection of sunken cultural heritage. The scope of this Special Issue encompasses investigations into techniques and ICT approaches and, in particular, the study and application of signal- and image-based methods and, in turn, exploration of the advantages of their application in the previously mentioned areas

Effects of errorless learning on the acquisition of velopharyngeal movement control

Session 1pSC - Speech Communication: Cross-Linguistic Studies of Speech Sound Learning of the Languages of Hong Kong (Poster Session)The implicit motor learning literature suggests a benefit for learning if errors are minimized during practice. This study investigated whether the same principle holds for learning velopharyngeal movement control. Normal speaking participants learned to produce hypernasal speech in either an errorless learning condition (in which the possibility for errors was limited) or an errorful learning condition (in which the possibility for errors was not limited). Nasality level of the participants’ speech was measured by nasometer and reflected by nasalance scores (in %). Errorless learners practiced producing hypernasal speech with a threshold nasalance score of 10% at the beginning, which gradually increased to a threshold of 50% at the end. The same set of threshold targets were presented to errorful learners but in a reversed order. Errors were defined by the proportion of speech with a nasalance score below the threshold. The results showed that, relative to errorful learners, errorless learners displayed fewer errors (50.7% vs. 17.7%) and a higher mean nasalance score (31.3% vs. 46.7%) during the acquisition phase. Furthermore, errorless learners outperformed errorful learners in both retention and novel transfer tests. Acknowledgment: Supported by The University of Hong Kong Strategic Research Theme for Sciences of Learning © 2012 Acoustical Society of Americapublished_or_final_versio

Localization, Mapping and SLAM in Marine and Underwater Environments

The use of robots in marine and underwater applications is growing rapidly. These applications share the common requirement of modeling the environment and estimating the robots’ pose. Although there are several mapping, SLAM, target detection and localization methods, marine and underwater environments have several challenging characteristics, such as poor visibility, water currents, communication issues, sonar inaccuracies or unstructured environments, that have to be considered. The purpose of this Special Issue is to present the current research trends in the topics of underwater localization, mapping, SLAM, and target detection and localization. To this end, we have collected seven articles from leading researchers in the field, and present the different approaches and methods currently being investigated to improve the performance of underwater robots

Abstracts of manuscripts submitted in 1989 for publication

This volume contains the abstracts of manuscripts submitted for publication during calendar year 1989 by the staff and students of the Woods Hole Oceanographic Institution. We identify the journal of those manuscripts which are in press or have been published. The volume is intended to be informative, but not a bibliography. The abstracts are listed by title in the Table of Contents and are grouped into one of our five deparments, marine policy, or the student category. An author index is presented in the back to facilitate locating specific papers

Software-Defined architecture for QoS-Aware IoT deployments in 5G systems

[EN] Internet of Things (IoT), a ubiquitous network of interconnected objects, harvests information from the environments, interacts with the physical world, and uses the existing Internet infrastructure to provide services for information transfer and emerging applications. However, the scalability and Internet access fundamentally challenge the realization of a wide range of IoT applications. Based on recent developments of 5G system architecture, namely SoftAir, this paper introduces a new software-defined platform that enables dynamic and flexible infrastructure for 5G IoT communication. A corresponding sum-rate analysis is also carried out via an optimization approach for efficient data transmissions. First, the SoftAir decouples control plane and data plane for a software-defined wireless architecture and enables effective coordination among remote radio heads (RRHs), equipped with millimeter-wave (mmWave) frontend, for IoT access. Next, by introducing an innovative design of software-defined gateways (SD-GWs) as local IoT controllers in SoftAir, the wide diversity of IoT applications and the heterogeneity of IoT devices are easily accommodated. These SD-GWs aggregate the traffic from heterogeneous IoT devices and perform protocol conversions between IoT networks and radio access networks. Moreover, a cross-domain optimization framework is proposed in this extended SoftAir architecture concerning both upstream and downstream communication, where the respective sum-rates are maximized and system-level constraints are guaranteed, including (i) quality-of-service requirements of IoT transmissions, (ii) total power limit of mmWave RRHs, and (iii) fronthaul network capacities. Simulation results validate the efficacy of our solutions, where the extended SoftAir solution surpasses existing IoT schemes in spectral efficiency and achieves optimal data rates for next-generation IoT communication. (C) 2019 Elsevier B.V. All rights reserved.This work was supported by the US National Science Foundation (NSF) under Grant No. 1547353. A part of this work was supported by the Harry C. Kelly Memorial Fund, AC21 Special Project Fund (SPF), NC State 2019-2020 Internationalization Seed Grants and 2019 Faculty Research and Professional Development (FRPD) Program. The work of V. Pla was supported by Grant PGC2018-094151-B-I00 (MCIU/AEI/FEDER, UE).Tello-Oquendo, L.; Lin, S.; Akyildiz, IF.; Pla, V. (2019). Software-Defined architecture for QoS-Aware IoT deployments in 5G systems. Ad Hoc Networks. 93:1-11. https://doi.org/10.1016/j.adhoc.2019.101911S1119