Visualization of and Access to CloudSat Vertical Data through Google Earth

Online tools, pioneered by the Google Earth (GE), are facilitating the way in which scientists and general public interact with geospatial data in real three dimensions. However, even in Google Earth, there is no method for depicting vertical geospatial data derived from remote sensing satellites as an orbit curtain seen from above. Here, an effective solution is proposed to automatically render the vertical atmospheric data on Google Earth. The data are first processed through the Giovanni system, then, processed to be 15-second vertical data images. A generalized COLLADA model is devised based on the 15-second vertical data profile. Using the designed COLLADA models and satellite orbit coordinates, a satellite orbit model is designed and implemented in KML format to render the vertical atmospheric data in spatial and temporal ranges vividly. The whole orbit model consists of repeated model slices. The model slices, each representing 15 seconds of vertical data, are placed on the CloudSat orbit based on the size, scale, and angle with the longitude line that are precisely and separately calculated on the fly for each slice according to the CloudSat orbit coordinates. The resulting vertical scientific data can be viewed transparently or opaquely on Google Earth. Not only is the research bridged the science and data with scientists and the general public in the most popular way, but simultaneous visualization and efficient exploration of the relationships among quantitative geospatial data, e.g. comparing the vertical data profiles with MODIS and AIRS precipitation data, becomes possible

Contributions to automated realtime underwater navigation

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 February 2012This dissertation presents three separate–but related–contributions to the art of underwater navigation. These methods may be used in postprocessing with a human in the loop, but the overarching goal is to enhance vehicle autonomy, so the emphasis is on automated approaches that can be used in realtime. The three research threads are: i) in situ navigation sensor alignment, ii) dead reckoning through the water column, and iii) model-driven delayed measurement fusion. Contributions to each of these areas have been demonstrated in simulation, with laboratory data, or in the field–some have been demonstrated in all three arenas. The solution to the in situ navigation sensor alignment problem is an asymptotically stable adaptive identifier formulated using rotors in Geometric Algebra. This identifier is applied to precisely estimate the unknown alignment between a gyrocompass and Doppler velocity log, with the goal of improving realtime dead reckoning navigation. Laboratory and field results show the identifier performs comparably to previously reported methods using rotation matrices, providing an alignment estimate that reduces the position residuals between dead reckoning and an external acoustic positioning system. The Geometric Algebra formulation also encourages a straightforward interpretation of the identifier as a proportional feedback regulator on the observable output error. Future applications of the identifier may include alignment between inertial, visual, and acoustic sensors. The ability to link the Global Positioning System at the surface to precision dead reckoning near the seafloor might enable new kinds of missions for autonomous underwater vehicles. This research introduces a method for dead reckoning through the water column using water current profile data collected by an onboard acoustic Doppler current profiler. Overlapping relative current profiles provide information to simultaneously estimate the vehicle velocity and local ocean current–the vehicle velocity is then integrated to estimate position. The method is applied to field data using online bin average, weighted least squares, and recursive least squares implementations. This demonstrates an autonomous navigation link between the surface and the seafloor without any dependence on a ship or external acoustic tracking systems. Finally, in many state estimation applications, delayed measurements present an interesting challenge. Underwater navigation is a particularly compelling case because of the relatively long delays inherent in all available position measurements. This research develops a flexible, model-driven approach to delayed measurement fusion in realtime Kalman filters. Using a priori estimates of delayed measurements as augmented states minimizes the computational cost of the delay treatment. Managing the augmented states with time-varying conditional process and measurement models ensures the approach works within the proven Kalman filter framework–without altering the filter structure or requiring any ad-hoc adjustments. The end result is a mathematically principled treatment of the delay that leads to more consistent estimates with lower error and uncertainty. Field results from dead reckoning aided by acoustic positioning systems demonstrate the applicability of this approach to real-world problems in underwater navigation.I have been financially supported by: the National Defense Science and Engineering Graduate (NDSEG) Fellowship administered by the American Society for Engineering Education, the Edwin A. Link Foundation Ocean Engineering and Instrumentation Fellowship, and WHOI Academic Programs office

RRS James Cook Cruise 35, 7-19 Jun 2009. Sidescan sonar mapping of the Whittard Canyon, Celtic Margin

James Cook cruise 035 was aimed at the detailed mapping of the Whittard Canyon system along the Celtic Margin (NE Atlantic). In 12 days, &gt;700 km of track-lines were surveyed with the Towed Ocean Bottom Instrument (TOBI, carrying a 30 kHz sidescan sonar system with phase bathymetry capability, an 8 kHz chirp profiler and a magnetometer) and 6130 km2 of shipborne multibeam data was acquired over the 4 main branches of the canyon. This comprehensive and highly detailed dataset will provide new insights in canyon morphology, formation, sediment transport processes and into the resulting spatial distribution of benthic habitats. In addition, the data formed an indispensable base map for the planning of ROV dives during the follow-on cruise JC036.<br/

Ultimate ocean depth packaging for a digital ring laser gyroscope

A Honeywell GG 1320AN Digital Ring Laser Gyroscope (RLG), typically an aviation sensor, has been adapted for use as part of a navigation package rated to ocean depths of 6,000 meters. Researchers and engineers at the Deep Submergence Laboratory (DSL) of the Woods Hole Oceanographic Institution (WHOI) designed a high-density instrument package around the basic RLG. The integrated instrument is modular and field serviceable. It includes a chassis, housing, a Crossbow 6-axis dynamic measurement unit (DMU), battery backup, power regulation, support circuitry and robust interfaces. A pressure-proof titanium case and non-corroding accessories ensure that the RLG will remain unaffected by prolonged immersion in seawater. Associated mounting bracketry allow the housing to be axially registered alongside the navigation suites of various deep diving WHOI assets, or with any host platform capable of caring a 25 pound payload. Primary RLG platforms will be the manned deep submergence vehicle ALVIN, the unmanned remotely operated vehicle JASON, and the unmanned autonomous vehicle ABE. As an extremely accurate yaw rate measuring device, the RLG will provide navigation data far more reliable and precise that has been available to scientists in the past. The WHOI RLG has been used successfully on one JASON cruise.Funding was provided by the National Science Foundation under Grant No. OCE-9710512

SEAPAK user's guide, version 2.0. Volume 2: Descriptions of programs

The SEAPAK is a user-interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made since version 1.0, and the ancillary environmental data analysis module was greatly expanded. The package continues to be user friendly and user interactive. Also, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing for large quantities of data to be ingested and analyzed

Stabilization of planar collective motion: All-to-all communication

This paper proposes a design methodology to stabilize isolated relative equilibria in a model of all-to-all coupled identical particles moving in the plane at unit speed. Isolated relative equilibria correspond to either parallel motion of all particles with fixed relative spacing or to circular motion of all particles with fixed relative phases. The stabilizing feedbacks derive from Lyapunov functions that prove exponential stability and suggest almost global convergence properties. The results of the paper provide a low-order parametric family of stabilizable collectives that offer a set of primitives for the design of higher-level tasks at the group level

Model-Based Adaptive Behavior Framework for Optimal Acoustic Communication and Sensing by Marine Robots

In this paper, a hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication. The adaptation framework is implemented within the behavior-based mission-oriented operating suite-interval programming (MOOS-IvP) marine autonomy architecture and uses a new embedded high-fidelity acoustic modeling infrastructure, the generic robotic acoustic model (GRAM), to provide real-time estimates of the acoustic environment under changing environmental and situational scenarios. A set of behaviors that combine adaptation to the current acoustic environment with strategies that extend the decision horizon beyond that of typical behavior-based systems have been developed, implemented, and demonstrated in a series of field experiments and virtual experiments in a MOOS-IvP simulation.United States. Office of Naval Research (Grant N00014-08-1-0011)United States. Office of Naval Research (Grant N00014-08-1-0013)NATO Undersea Research Centre (NURC

Aeolus Ocean -- A simulation environment for the autonomous COLREG-compliant navigation of Unmanned Surface Vehicles using Deep Reinforcement Learning and Maritime Object Detection

Heading towards navigational autonomy in unmanned surface vehicles (USVs) in the maritime sector can fundamentally lead towards safer waters as well as reduced operating costs, while also providing a range of exciting new capabilities for oceanic research, exploration and monitoring. However, achieving such a goal is challenging. USV control systems must, safely and reliably, be able to adhere to the international regulations for preventing collisions at sea (COLREGs) in encounters with other vessels as they navigate to a given waypoint while being affected by realistic weather conditions, either during the day or at night. To deal with the multitude of possible scenarios, it is critical to have a virtual environment that is able to replicate the realistic operating conditions USVs will encounter, before they can be implemented in the real world. Such "digital twins" form the foundations upon which Deep Reinforcement Learning (DRL) and Computer Vision (CV) algorithms can be used to develop and guide USV control systems. In this paper we describe the novel development of a COLREG-compliant DRL-based collision avoidant navigational system with CV-based awareness in a realistic ocean simulation environment. The performance of the trained autonomous Agents resulting from this approach is evaluated in several successful navigations to set waypoints in both open sea and coastal encounters with other vessels. A binary executable version of the simulator with trained agents is available at https://github.com/aavek/Aeolus-OceanComment: 22 pages, last blank page, 17 figures, 1 table, color, high resolution figure

Observationally constrained modeling of sound in curved ocean internal waves: Examination of deep ducting and surface ducting at short range

Author Posting. © Acoustical Society of America, 2011. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 130 (2011): 1173-1187, doi:10.1121/1.3605565.A study of 400 Hz sound focusing and ducting effects in a packet of curved nonlinear internal waves in shallow water is presented. Sound propagation roughly along the crests of the waves is simulated with a three-dimensional parabolic equation computational code, and the results are compared to measured propagation along fixed 3 and 6 km source/receiver paths. The measurements were made on the shelf of the South China Sea northeast of Tung-Sha Island. Construction of the time-varying three-dimensional sound-speed fields used in the modeling simulations was guided by environmental data collected concurrently with the acoustic data. Computed three-dimensional propagation results compare well with field observations. The simulations allow identification of time-dependent sound forward scattering and ducting processes within the curved internal gravity waves. Strong acoustic intensity enhancement was observed during passage of high-amplitude nonlinear waves over the source/receiver paths, and is replicated in the model. The waves were typical of the region (35 m vertical displacement). Two types of ducting are found in the model, which occur asynchronously. One type is three-dimensional modal trapping in deep ducts within the wave crests (shallow thermocline zones). The second type is surface ducting within the wave troughs (deep thermocline zones).Grants from the Office of Naval Research funded this work. Use of the vessels Ocean Researcher I and Ocean Researcher II in this experiment was funded by the Taiwan National Science Council