Project 1: Acoustic Monitoring of Underwater and Surface Vessels
CSR Research PI: Alexander Sutin, Stevens Institute of Technology
Project Description: The acoustic part of the CSR research is aimed at the investigation of applying passive acoustic methods to surface and underwater threat detection, classification and tracking in coastal zones. Acoustics is the only tool that provides detection of underwater threats and Stevens work has concentrated on passive acoustic methods that are much simpler and cheaper than conventional sonar techniques mainly applied for underwater threat detection. These studies have resulted in improved understanding of the signatures – and the underlying physics responsible for the signatures – for a variety of surface and underwater threats. Using this understanding, Stevens researchers have developed unique passive acoustic sensing technology that has promise to provide near real-time, detection, characterization, and tracking capabilities in nearshore, harbor and inland waterway environments.
All vessels underway produce broadband and discrete noise that is a combination of hydrodynamic noise and noise generated by the ship’s crew and the operation of onboard machinery. The low-frequency underwater acoustic output generated by surface ships is a significant contributor to background ambient noise in the open sea and in littoral regions, near harbors and shipping lanes. With minimal acoustic attenuation at low frequencies, ship acoustic footprints extend over tens to hundreds of kilometers.
Project 2: Decision Support Systems
CSR Research PI: Jeff Nickerson, Stevens Institute of Technology
Project Description: Domestic shipping and waterside facilities are subject to numerous surface and underwater threats. Any size vessel, from a large container ship to a small boat, has the ability to act as a delivery vehicle for illicit materials and harmful activities. This necessitates the ability to integrate sensor information from many different sensors with the goal of providing accurate situation awareness.
The goal of this research is to understand how users process and identify the information available from the various sensors that are currently in place, with the intention of maximizing the utility of an interface. Specifically, this research seeks to make use of crowd experiments to identify which visualizations of data are effective in the identification and classification of vessels.
What types of visualizations or methods of information integration are best for rapidly conveying both key output data from Coast Guard’s SAROPS, and weather or environmental data streams? For example, should novel risk calculations that incorporate the calculations for the probability of detection and probability of success be available as additional, optional information layers?” In the end, these findings will help address more general questions regarding information integration, fusion, and visualization such as, “Do additional sources of information help? Does the manner in which the information is displayed matter? If so, what forms of display result in better decision making?” Along the way, we will continue to address the following question, “Can experiments performed on participants in a more general demographic be used to predict the responses of those who are, or who have been, involved in Coast Guard operational decision making?”
Project 3: Development of a Dual-use Surface Current Mapping and Vessel Detection Capability for SeaSonde Multi-static High Frequency Radar Networks
CSR Research PI: Scott Glenn, Rutgers University
Project Description: The NOAA-led U.S. Integrated Ocean Observing System (IOOS) has designed, is constructing, and has recently begun operating the more advanced portions of, a National HF Radar network focused on the real-time mapping of surface currents. The primary users of the resulting surface current maps are the U.S. Coast Guard for Search And Rescue (SAR) and the NOAA HAZMAT team for ocean spill-response. The IOOS Mid-Atlantic Region’s CODAR SeaSonde HF Radar Network, operated by Rutgers University, is the first region in the U.S. to achieve operational status by constructing and operating the end-to-end system that produces and links validated real-time surface current maps to the Coast Guard’s Search And Rescue Optimal Planning System (SAROPS).
Rutgers and CODAR Ocean Sensors, an academic-industry partnership established in 1997, have worked together for over a decade to expand the capabilities of compact CODAR HF Radars to include the dual-use application of detecting and tracking ships without compromising the network’s ability to map surface currents. Development prior to the establishment of CSR focused on the demonstration and evaluation of a non-real-time end-to-end system for dual-use vessel tracking in the New York Bight multi-frequency HF Radar testbed. Software demonstrations determined (a) that vessels could be detected, (b) that the detections could be associated with a known ship, and (c) that the associated detections could then be input to a range of tracking algorithms whose output produced tracks and predicted trajectories on a computer screen, providing useful over-the-horizon information to operators not available through any other source. Radar hardware development focused on developing network flexibility beyond monostatic backscatter operations, demonstrating (a) that bistatic and multi-static operations were possible with a shore based network, and (b) that buoy-based bistatic transmitters can be operated at all three of the commonly used HF Radar frequencies (5-6 MHz, 12-13 MHz, 24-25 MHz). The pre-CSR research demonstrated that the rate-limiting step in the development of a robust vessel tracking capability for any HF radar was going to be development of the initial vessel detection algorithm. This conclusion focused the initial CSR step in dual-use HF Radar development on the mathematical problem of identifying and extracting the radar return of a surface vessel hidden within a highly variable and noisy background, requiring additional detection algorithm development, testing and sensitivity analysis in a variety of environments with different noise characteristics.
CSR HF Radar research, coordinated between Rutgers University, CODAR Ocean Sensors, and the University of Puerto Rico Mayaguez, is currently focused on improving the vessel detection algorithm. Vessel tracking testbeds have been constructed in the urbanized mid-latitude environment of New York Bight, and in the tropical environment of Puerto Rico. Each test bed consists of, at a minimum, multiple HF radar systems operating in multi-static mode and shore based AIS transceivers to provide unencumbered access to validation data. In collaboration with CIMES, Rutgers, CODAR and University of Alaska have established an Arctic testbed in Barrow, Alaska.
Project 4: MTS Resiliency: Ports
CSR Research PI: Jim Rice, MIT
Project Description: PORT MAPPER provides end-users with the capability to visualize port locations and to conduct real-time and scenario based disruption analysis. Port Mapper is comprised of two formats, a web-based visualization app (pictured above) and a spreadsheet database tool. Developed by CSR researchers Jim Rice and Kai Trepte of MIT Center for Transportation & Logistics (CTL), Port Mapper allows end-users to look up every U.S. port or cargo type by Standard Industrial Classification (SIC) code and identify options for redistribution of cargo in the event of port failures. Port Mapper is a decision support tool designed to assist maritime stakeholders as they develop response and resilience plans in the event of U.S. port closures and disruptions. The tool assists in answering the following questions: Where could cargo move to if a specific U.S. port was closed? What other ports handle the same cargo types as the disrupted port? What is the distance between the ports?
Utilized by U.S. Coast Guard senior leadership during Hurricane Sandy and the week-long closure of the Port of NY/NJ, Port Mapper enabled the USCG to visualize the redirection of cargo to alternative port locations.
Project 5: Satellite Radar Applications in the Coastal and Maritime Domain
CSR Research PI: Hans Graber, University of Miami
Project Description: The University of Miami’s Center for Southeastern Tropical Advanced Remote Sensing (CSTARS) leads the space-base applications and is developing new understanding and new processes for receiving and analyzing large maritime area data from multi-satellite and multi-frequency sensors such as Synthetic Aperture Radar (SAR) and electro-optical (EO) sensors. Algorithms continue to be developed to employ the data to detect vessels, including small ships, in harbors, inland waterways, the coastal ocean and the high seas. Algorithms are also being developed to integrate this vessel detection information with ground-based systems such as Automatic Identification System (AIS).
Large-area, satellite-based surveillance is an essential capability in the development of Maritime Domain Awareness, particularly in ship detection, classification and identification. The goal of this aspect of the CSR effort involves detecting vessels, including small ships, in the coastal ocean and high seas or when approaching and leaving ports, sensitive coastal regions and denied access regions. When combined with existing vessel monitoring systems (e.g., AIS, expanding shore-based and harbor surveillance systems and an emerging space-based AIS system, this capability will provide the tools that the DHS can employ in ensuring global Maritime Domain Awareness, Marine Transportation System Security, and Maritime Enforcement.
Using CSTARS’ capability to collect satellite image data on a global scale from multi-satellite and multi-frequency sensors such as Synthetic Aperture Radar (SAR) and electro-optical (EO) satellites, will allow in an operational sense to monitor the entire global oceans. SAR satellites can operate day and night and in all weather conditions and thus allow surveillance of ports and choke points in different ocean basins, as well as monitoring vessel traffic inbound and outbound of ports and harbors. The recently launched satellite SARs have spotlight modes that provide spatial resolutions comparable to high-resolution optical sensors. Since the end of last year we also added a new optical satellite sensor, EROS-B, with high-resolution panchromatic images at 70 cm resolution.