Advances in Sonar Technology

The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here

Multi-algorithm Swath Consistency Detection for Multibeam Echosounder Data

It is unrealistic to expect that any single algorithm for pre-filtering Multibeam Echosounder data will be able to detect all of the “noise in such data all of the time. This paper therefore presents a scheme for fusing the results of many pre-filtering sub-algorithms in order to form one, significantly more robust, meta-algorithm. This principle is illustrated on the problem of consistency detection in regions of sloping bathymetry. We show that the meta-algorithm is more robust, adapts dynamically to sub-algorithm performance, and is consistent with operator assessment of the data. The meta-algorithm is called the Multi-Algorithm Swath Consistency Detector

Seafloor depth estimation by means of interferometric synthetic aperture sonar

The topic of this thesis is relative depth estimation using interferometric sidelooking sonar. We give a thorough description of the geometry of interferometric sonar and of time delay estimation techniques. We present a novel solution for the depth estimate using sidelooking sonar, and review the cross-correlation function, the cross-uncertainty function and the phase-differencing technique. We find an elegant solution to co-registration and unwrapping by interpolating the sonar data in ground-range. Two depth estimation techniques are developed: Cross-correlation based sidescan bathymetry and synthetic aperture sonar (SAS) interferometry. We define flank length as a measure of the horizontal resolution in bathymetric maps and find that both sidescan bathymetry and SAS interferometry achieve theoretical resolutions. The vertical precision of our two methods are close to the performance predicted from the measured coherence. We study absolute phase-difference estimation using bandwidth and find a very simple split-bandwidth approach which outperforms a standard 2D phase unwrapper on complicated objects. We also examine advanced filtering of depth maps. Finally, we present pipeline surveying as an example application of interferometric SAS

Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Multi-Algorithm Swath Consistency Detection for Multibeam Echosounder Data

It is unrealistic to expect that any single algorithm for pre-filtering Multibeam Echosounder data will be able to detect all of the “noise" in such data all of the time. This paper therefore presents a scheme for fusing the results of many pre-filtering sub-algorithms in order to form one, significantly more robust, meta-algorithm. This principle is illustrated on the problem of consistency detection in regions of sloping bathymetry. We show that the meta-algorithm is more robust, adapts dynamically to sub-algorithm performance, and is consistent with operator assessment of the data. The meta-algorithm is called the Multi-Algorithm Swath Consistency Detector.No es realista esperar que cualquier simple algoritmo, para filtrar previa mente los datos procedentes de un Sondador Acüstico Multihaz, podrâ detectar todo el “ruido" contenido en dichos datos todo el tiempo. Este documento présenta pues un esquema que utilizarâ los resultados de muchos subalgoritmos de pre-filtrado para formar uno solo, significativamente mâs robusto, un meta-algoritmo. Este principio queda demostrado en el problema de la detecciôn de una coherencia en regiones de batimetna de retroceso. Mostramos que el meta-algoritmo es mâs robusto, se adapta de forma dinâmica al funcionamiento de un subalgoritmo y es coherente con la evaluaciôn de los datos por el operador. El meta-algoritmo es denominado Detector de Coherencia de Muiti-algoritmos por Bandas.Il n'est pas réaliste de s'attendre à ce que chaque algorithme pour le pré-filtrage des données des échosondeurs multifaisceaux puisse détecter tous les «bruits» de ces données, à chaque moment. Cet article présente donc un projet de fusion des résultats de nombreux sous-algorithmes de pré-filtrage afin de constituer un seul méta-algorithme, bien plus robuste. Ce principe est illustré avec le problème de la détection de cohérence dans les régions à bathymétrie en pente. Nous montrons que le méta-algorithme est plus robuste, que sa dynamique s'adapte au fonctionnement du sous-algorithme et qu'il est cohérent avec l'évaluation des données effectuée par l’opérateur. Le méta-algorithme est appelé «détecteur multi-algorithme de cohérence dans une bande»

Scattering statistics of rock outcrops: Model-data comparisons and Bayesian inference using mixture distributions

The probability density function of the acoustic field amplitude scattered by the seafloor was measured in a rocky environment off the coast of Norway using a synthetic aperture sonar system, and is reported here in terms of the probability of false alarm. Interpretation of the measurements focused on finding appropriate class of statistical models (single versus two-component mixture models), and on appropriate models within these two classes. It was found that two-component mixture models performed better than single models. The two mixture models that performed the best (and had a basis in the physics of scattering) were a mixture between two K distributions, and a mixture between a Rayleigh and generalized Pareto distribution. Bayes' theorem was used to estimate the probability density function of the mixture model parameters. It was found that the K-K mixture exhibits significant correlation between its parameters. The mixture between the Rayleigh and generalized Pareto distributions also had significant parameter correlation, but also contained multiple modes. We conclude that the mixture between two K distributions is the most applicable to this dataset.Comment: 15 pages, 7 figures, Accepted to the Journal of the Acoustical Society of Americ

Towards autonomous localization and mapping of AUVs: a survey

Purpose The main purpose of this paper is to investigate two key elements of localization and mapping of Autonomous Underwater Vehicle (AUV), i.e. to overview various sensors and algorithms used for underwater localization and mapping, and to make suggestions for future research. Design/methodology/approach The authors first review various sensors and algorithms used for AUVs in the terms of basic working principle, characters, their advantages and disadvantages. The statistical analysis is carried out by studying 35 AUV platforms according to the application circumstances of sensors and algorithms. Findings As real-world applications have different requirements and specifications, it is necessary to select the most appropriate one by balancing various factors such as accuracy, cost, size, etc. Although highly accurate localization and mapping in an underwater environment is very difficult, more and more accurate and robust navigation solutions will be achieved with the development of both sensors and algorithms. Research limitations/implications This paper provides an overview of the state of art underwater localisation and mapping algorithms and systems. No experiments are conducted for verification. Practical implications The paper will give readers a clear guideline to find suitable underwater localisation and mapping algorithms and systems for their practical applications in hand. Social implications There is a wide range of audiences who will benefit from reading this comprehensive survey of autonomous localisation and mapping of UAVs. Originality/value The paper will provide useful information and suggestions to research students, engineers and scientists who work in the field of autonomous underwater vehicles