Val E. Schmidt

Automated optimal processing of phase differencing side-scan sonar data using the Most-Probable Angle Algorithm

Phase-differencing side-scan sonar systems produce co-located bathymetry in addition to each side-scan amplitude measurement. Bathymetric soundings are calculated from the range to each measurement (derived from the two-way travel time) and the receive angle of the incoming signal. Because phase-differencing systems produce a seafloor sounding with each individual measurement, they are often characterized as noisy when compared to multi-beam sonar systems, whose seafloor estimates, whether by amplitude-weighted mean or sub-aperture phase difference detection, are the product of averaging several measurements. In addition, every effort is made to increase the resolution of side-scan data by increasing the bandwidth and sampling rate of the transmitted signal, often producing more than 10,000 data points per ping. This volume of outlier-prone, relatively noisy data is difficult for operators to interpret and software to process. A series of methods has been developed for the automated processing of phase-differencing side-scan sonar data producing seafloor estimates and related uncertainties optimized for the survey application. The “Most-Probable Angle Algorithm” (MPAA) has been developed for the filtering of outliers in range-angle measurements. With outliers removed, the uncertainty of the filtered measurements are estimated. Angle estimates are then calculated as an uncertainty-weighted mean where the number of measurements contributing to each estimate is determined from that required to achieve a desired depth uncertainty. The resulting swath of depth measurements contains irregularly spaced soundings, typically obtaining full spatial resolution of the side-scan data from 20-50 degrees from nadir, and combining several measurements to reduce the uncertainty elsewhere. In this way, given a survey requirement, an optimal amount of information can be extracted from the sonar data in varying conditions.

Measurement of micro-bathymetry with a GOPRO underwater stereo camera pair

A GO-PRO underwater stereo camera kit has been used to measure the 3D topography (bathymetry) of a patch of seafloor producing a point cloud with a spatial data density of 15 measurements per 3 mm grid square and an standard deviation of less than 1 cm A GO-PRO camera is a fixed focus, 11 megapixel, still-frame (or 1080p high-definition video) camera, whose small form-factor and water-proof housing has made it popular with sports enthusiasts. A stereo camera kit is available providing a waterproof housing (to 61 m / 200 ft) for a pair of cameras. Measures of seafloor micro-bathymetry capable of resolving seafloor features less than 1 cm in amplitude were possible from the stereo reconstruction. Bathymetric measurements of this scale provide important ground-truth data and boundary condition information for modeling of larger scale processes whose details depend on small-scale variations. Examples include modeling of turbulent water layers, seafloor sediment transfer and acoustic backscatter from bathymetric echo sounders.

Underwater radiated noise levels of a research icebreaker in the central Arctic Ocean

U.S. Coast Guard Cutter Healys underwater radiated noise signature was characterized in the central Arctic Ocean during different types of ice-breaking operations. Propulsion modes included transit in variable ice cover, breaking heavy ice with backing-and-ramming maneuvers, and dynamic positioning with the bow thruster in operation. Compared to open-water transit, Healys noise signature increased approximately 10 dB between 20 Hz and 2 kHz when breaking ice. The highest noise levels resulted while the ship was engaged in backing-and-ramming maneuvers, owing to cavitation when operating the propellers astern or in opposing directions. In frequency bands centered near 10, 50, and 100 Hz, source levels reached 190-200 dB re: 1 μPa at 1 m (full octave band) during ice-breaking operations.

Underwater Tracking of Humpback Whales (Megaptera Novaeangliae) With High-Frequency Pingers and Acoustic Recording Tags

A long-baseline (LBL) acoustic system has been developed for the tracking of humpback whales (Megaptera novaeangliae) that have been tagged with digital acoustic recording devices (DTAGs), providing quantitative observations of submerged whale behavior during bubble net feeding. The system includes three high-frequency acoustic sources deployed from small boats that follow the whale after the animal has been tagged. Integrated global positioning systems (GPSs) provide positioning and synchronized operation of the sources. Time-encoded acoustic signals from the sources are recorded along with whale vocalizations and ambient noise on the whale tag. Time-of-flight measurements, as measured by the tag acoustic data, are converted to range from the whale to each source with a measured sound-speed profile. A nonlinear least squares solution is then solved for the whales position with a nominal positional fix rate of once per second. The system is demonstrated with data collected from a tagged animal in summer 2007. Dead-reckoned track generation methods commonly used in previous studies are shown to capture the qualitative nature of the whale track, albeit with poor absolute positional accuracy, and to distort the track when the whales movement is predominantly vertical. In contrast, the LBL data can provide quantitative measures of whale behavior. Transit speeds between bubble net feeding events for this case study are found to range from 0.7 to 1.9 m · s-1 (n = 8). The mean diameter of bubble net curtains are measured to range from 9.6 to 10.9 m. Whale speeds during bubble net rotations vary from 1.0 to 1.9 m · s-1 (n = 6).

Multibeam sonar backscatter data processing

Multibeam sonar systems now routinely record seafloor backscatter data, which are processed into backscatter mosaics and angular responses, both of which can assist in identifying seafloor types and morphology. Those data products are obtained from the multibeam sonar raw data files through a sequence of data processing stages that follows a basic plan, but the implementation of which varies greatly between sonar systems and software. In this article, we provide a comprehensive review of this backscatter data processing chain, with a focus on the variability in the possible implementation of each processing stage. Our objective for undertaking this task is twofold: (1) to provide an overview of backscatter data processing for the consideration of the general user and (2) to provide suggestions to multibeam sonar manufacturers, software providers and the operators of these systems and software for eventually reducing the lack of control, uncertainty and variability associated with current data processing implementations and the resulting backscatter data products. One such suggestion is the adoption of a nomenclature for increasingly refined levels of processing, akin to the nomenclature adopted for satellite remote-sensing data deliverables.

Modular autonomous biosampler (MAB) — A prototype system for distinct biological size-class sampling and preservation

Presently, there is a community wide deficiency in our ability to collect and preserve multiple size-class biologic samples across a broad spectrum of oceanographic platforms (e.g. AUVs, ROVs, and Ocean Observing System Nodes). This is particularly surprising in comparison to the level of instrumentation that now exists for acquiring physical and geophysical data (e.g. side-scan sonar, current profiles etc.), from these same platforms. We present our effort to develop a low-cost, high sample capacity modular, autonomous biological sampling device (MAB). The unit is designed for filtering and preserving 3 distinct biological size-classes (including bacteria), and is deployable in any aquatic setting from a variety of platform modalities (AUV, ROV, or mooring).

Analysis of the radiated sound field of deep water multibeam echo sounders for return intensity calibration using an underwater hydrophone array

Multibeam echo sounders (MBES) are tools used to gather geophysical information on the seafloor and watercolumn which are important for feature detection, identifying gas seeps, and characterizing the seafloor, among others. At high frequencies (>100 kHz), MBES can be calibrated for their ensonification patterns in test tanks. However, deep water MBES feature long transmit arrays and varying geometries that make tank calibration impractical. The transmit arrays can be over 8m and have a far field range in the hundreds of meters. In addition, these systems use beam steering techniques to segment the swath into multiple sectors to mitigate ship motions, which complicates the radiated pattern and return intensity. This study will better characterize the radiated sound field of deep water MBES for return intensity calibration. A MBES survey was conducted using a Kongsberg EM122 MBES on the SCORE range, a submerged broadband hydrophone array. Hydrophones were spaced ~5 km apart and were continuously recording ...

Providing Nautical Chart awareness to autonomous surface vessel operations

When a mariner navigates into an unfamiliar area, he/she uses a nautical chart to familiarize him/herself with the environment, determine the locations of hazards, and decide upon a safe course of travel. An autonomous surface vehicle (ASV) would gain a great advantage if, like its human counterpart, it can learn to read and use the information from a nautical chart. Electronic Nautical Charts (ENCs) contain extensive information on an area, providing indications of rocks and other obstructions, navigational aids, water depths, and shore lines. The goal of this research is to increase an ASVs autonomy by using ENCs to provide guidance to the helm when its intended path, which may be dynamically changing, is unsafe due to known hazards to navigation, and context to its sensor measurements that are invariably subject to uncertainty.The approach taken in this paper divides nautical chart awareness into two sections: obstacle avoidance and contextualizing sensor measurements. Unplanned changes to the ASVs path, such as avoidance of other vessels or previously unknown obstacles sensed by the ASV in real-time, may cause the ASV to maneuver into an unsafe environment. Prior mission planning, even with knowledge of nautical charts, cannot account for these dynamic responses. Therefore, to navigate an ASV safely through its environment, obstacle avoidance procedures have been developed to reactively change the ASVs path to avoid known obstacles identified from ENCs. The ENC obstacle avoidance procedures are implemented in a behavior-based architecture where information on the potential threat of the nearby obstacles, as well as the ASVs current state, are used to penalize heading choices that would intersect with the obstacle and, when combined with the waypoint behavior, ensures safe travel around the obstacle while maintaining close proximity to the original path. Identifying objects in a camera, sonar, LIDAR or other sensors data can be a challenging endeavor in an ocean environment due to the variable sea state, wind, fog, sea spray, sun glint from the sea surface, and bubbles in the water column. Therefore, providing a prior probability distribution for the likely location of those objects in a sensors field of view has the potential to significantly enhance object detection processing. Contextualizing sensor measurements dynamically identifies objects from the ENC in a sensors field of view and provides that information to the sensor in real-time. To accomplish these tasks, feature layers within a standard ENC must be translated to a spatial database. In this database, features are encoded with a “threat level” based on the feature type and the estimated depth of the object, which is not always encoded within the ENC. Variations in the local tides as well as the vessel size and speed are also factors when deciding the threat level and the vehicles appropriate course of action. Providing an ASV the ability to read, understand, and use nautical charts allows the ASV to safely react to known obstacles in its environment and to increase robustness of sensor detection algorithms. No mariner would go into an unfamiliar harbor with restricted visibility without consulting a nautical chart. Autonomous surface vehicles should not be an exception.

Acoustic Positioning and Tracking in Portsmouth Harbor, New Hampshire

Portsmouth Harbor, New Hampshire, is frequently used as a testing area for multibeam and sidescan sonars, and is the location of numerous ground-truthing studies. Having the ability to accurately position underwater sensors is an important aspect of this type of work. However, underwater positioning in Portsmouth Harbor is challenging. It is relatively shallow, approximately one kilometer wide with depths of less than 25 meters. There is mixing between fresh river water and seawater, which is intensified by high currents and strong tides. This causes a very complicated spatial and temporal sound speed structure. Solutions that use the time-of-arrival of an acoustic pulse to estimate range will require very precise knowledge of the travel paths of the signal in order to separate out issues of multipath arrivals. An alternative solution is to use the phase measurements between closely spaced hydrophones to measure the bearing of an acoustic pinger. By using two bearing measurement devices that are widely separated, the intersection of the two bearings can be used to position the pinger. The advantage of this approach is that the sound speed only needs to be known at the location of the phase measurements. Both time-of-arrival and phase difference systems may encounter difficulties arising from horizontal refraction due to spatially varying sound speed. To ascertain which solution would be optimal in Portsmouth Harbor, the time-of-arrival and phase measurement approaches are being examined individually. Initial field tests have been conducted using a 40 kHz signal to look at bearing accuracy. Using hydrophones that are spaced 2/3 wavelengths apart, the bearing accuracy was found to be 1.25deg for angles up to 20deg from broadside with signal to noise ratios (SNR) greater than 15 dB. The results from the closely spaced hydrophones were used to resolve phase ambiguities, allowing finer bearing measurements to be made between hydrophones spaced 5 wavelengths apart. The fine bearing measurements resulted in a bearing accuracy of 0.3deg for angles up to 20deg from broadside with SNR greater than 15 dB. Field tests planned for summer 2007 will include a more detailed investigation of how the environmental influences affect each of the measurement types including range, signal to noise ratio, currents, and sound speed structure.

Whale tracking underwater: High frequency acoustic pingers and the instrumented tag (DTAG)

Since 2004, scientists have been tagging and tracking humpback whales in Stellwagen Bank National Marine Sanctuary to better understand their behavior. Stellwagen Bank is a shoal area east of Boston and north of Cape Cod, MA where many species of baleen whale feed during the summer months. Instrumented tags (DTAGs) are suction‐cupped to the whales back from a RHIB. DTAGS, developed at WHOI, record whale pitch, roll, and heading, 3‐D acceleration, depth, and sound for up to 20 h. A pseudotrack for the tagged whale can be generated using visual fixes at the surface and dead‐reckoning while the whale is underwater. During extended dives, the solution is expected to exhibit substantial drift, placing limits on the ability to understand feeding behavior, mother‐calf interactions, etc. In order to develop higher accuracy whale tracks, three GPS‐positioned high‐frequency (25–32 kHz) acoustic pingers were deployed around tagged animals in July 2007. The pingers produce time‐encoded pulses from known positions, which are recorded along with whale vocalizations and ambient noise on the whale tag. Pulse arrival times from each pinger are converted into ranges from the known pinger locations to generate an underwater whale track. Results from this work will be presented.