Spectral feature classification of oceanographic processes using an autonomous underwater vehicle

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2000The thesis develops and demonstrates methods of classifying ocean processes using an underwater moving platform such as an Autonomous Underwater Vehicle (AUV). The "mingled spectrum principle" is established which concisely relates observations from a moving platform to the frequency-wavenumber spectrum of the ocean process. It clearly reveals the role of the AUV speed in mingling temporal and spatial information. For classifying different processes, an AUV is not only able to jointly utilize the time-space information, but also at a tunable proportion by adjusting its cruise speed. In this respect, AUVs are advantageous compared with traditional oceanographic platforms. Based on the mingled spectrum principle, a parametric tool for designing an AUVbased spectral classifier is developed. An AUV's controllable speed tunes the separability between the mingled spectra of different processes. This property is the key to optimizing the classifier's performance. As a case study, AUV-based classification is applied to distinguish ocean convection from internal waves. The mingled spectrum templates are derived from the MIT Ocean Convection Model and the Garrett-Munk internal wave spectrum model. To allow for mismatch between modeled templates and real measurements, the AUVbased classifier is designed to be robust to parameter uncertainties. By simulation tests on the classifier, it is demonstrated that at a higher AUV speed, convection's distinct spatial feature is highlighted to the advantage of classification. Experimental data are used to test the AUV-based classifier. An AUV-borne flow measurement system is designed and built, using an Acoustic Doppler Velocimeter (ADV). The system is calibrated in a high-precision tow tank. In February 1998, the AUV acquired field data of flow velocity in the Labrador Sea Convection Experiment. The Earth-referenced vertical flow velocity is extracted from the raw measurements. The classification test result detects convection's occurrence, a finding supported by more traditional oceanographic analyses and observations. The thesis work provides an important foundation for future work in autonomous detection and sampling of oceanographic processes.This thesis research has been funded by the Office of Naval Research (ONR) under Grants NOOOl4-95-1-1316, NOO0l4-97-1-0470, and by the MIT Sea Grant College Program under Grant NA46RG0434

Generative-Discriminative Complementary Learning

Majority of state-of-the-art deep learning methods are discriminative approaches, which model the conditional distribution of labels given inputs features. The success of such approaches heavily depends on high-quality labeled instances, which are not easy to obtain, especially as the number of candidate classes increases. In this paper, we study the complementary learning problem. Unlike ordinary labels, complementary labels are easy to obtain because an annotator only needs to provide a yes/no answer to a randomly chosen candidate class for each instance. We propose a generative-discriminative complementary learning method that estimates the ordinary labels by modeling both the conditional (discriminative) and instance (generative) distributions. Our method, we call Complementary Conditional GAN (CCGAN), improves the accuracy of predicting ordinary labels and can generate high-quality instances in spite of weak supervision. In addition to the extensive empirical studies, we also theoretically show that our model can retrieve the true conditional distribution from the complementarily-labeled data

Current velocity profiling from an autonomous underwater vehicle with the application of Kalman filtering

Thesis (S.M. in Oceanographic Engineering)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution); and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 74-78).The thesis presents data processing schemes for extracting Earth-referenced current velocity from relative current velocity measurement made by an Acoustic Doppler Current Profiler (ADCP) borne by an Autonomous Underwater Vehicle (AUV). Compared with conventional approaches, current profiling from an AUV platform has advantages including three-dimensional mobility, rapid response, high-level intelligent control, independence from ship motion and weather constraint, and shallow water operation. First, an acausal postprocessing scheme is presented for estimating the AUV's own velocity and removing it from the relative velocity measurement to obtain the true current velocity. Then, a causal scheme for estimating the Earth-referenced current velocity is presented. The causal algorithm is based on an Extended Kalman Filter (EKF) that utilizes the hydrodynamics connecting current velocity to vehicle's motion. In both methods, the raw ADCP measurement is corrected to achieve more accurate current velocity estimate. Field data from the Haro Strait Tidal Front Experiment are processed by both methods. Current velocity estimation results reveal horizontal and vertical velocity structure of the tidal mixing process, and are also consistent with the vehicle's deviated trajectory. The capability of the AUV-borne current profiling system is thus demonstrated.by Yanwu Zhang.S.M.in Oceanographic Engineerin

Evolution of a physical and biological front from upwelling to relaxation

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Continental Shelf Research 108 (2015): 55-64, doi:10.1016/j.csr.2015.08.005.Fronts influence the structure and function of coastal marine ecosystems. Due to the complexity and dynamic nature of coastal environments and the small scales of frontal gradient zones, frontal research is difficult. To advance this challenging research we developed a method enabling an autonomous underwater vehicle (AUV) to detect and track fronts, thereby providing high-resolution observations in the moving reference frame of the front itself. This novel method was applied to studying the evolution of a frontal zone in the coastal upwelling environment of Monterey Bay, California, through a period of variability in upwelling intensity. Through 23 frontal crossings in four days, the AUV detected the front using real-time analysis of vertical thermal stratification to identify water types and the front between them, and the vehicle tracked the front as it moved more than 10 km offshore. The physical front coincided with a biological front between strongly stratified phytoplankton-enriched water inshore of the front, and weakly stratified phytoplankton-poor water offshore of the front. While stratification remained a consistent identifier, conditions on both sides of the front changed rapidly as regional circulation responded to relaxation of upwelling winds. The offshore water type transitioned from relatively cold and saline upwelled water to relatively warm and fresh coastal transition zone water. The inshore water type exhibited an order of magnitude increase in chlorophyll concentrations and an associated increase in oxygen and decrease in nitrate. It also warmed and freshened near the front, consistent with the cross-frontal exchange that was detected in the high-resolution AUV data. AUV-observed cross-frontal exchanges beneath the surface manifestation of the front emphasize the importance of AUV synoptic water column surveys in the frontal zone.This work was supported by the David and Lucile Packard Foundation

Superconductivity in epitaxially grown LaVO3/KTaO3(111) heterostructures

Complex oxide heterointerfaces can host a rich of emergent phenomena, and epitaxial growth is usually at the heart of forming these interfaces. Recently, a strong crystalline-orientation-dependent two-dimensional superconductivity was discovered at interfaces between KTaO3 single-crystal substrates and films of other oxides. Unexpectedly, rare of these oxide films was epitaxially grown. Here, we report the existence of superconductivity in epitaxially grown LaVO3/KTaO3(111) heterostructures, with a superconducting transition temperature of ~0.5 K. Meanwhile, no superconductivity was detected in the (001)- and (110)-orientated LaVO3/KTaO3 heterostructures down to 50 mK. Moreover, we find that for the LaVO3/KTaO3(111) interfaces to be conducting, an oxygen-deficient growth environment and a minimum LaVO3 thickness of ~0.8 nm (~ 2 unit cells) are needed.Comment: 5 figures, plus 6 supplementary figure