Multistatic acoustic characterization of seabed targets

Author Posting. © Acoustical Society of America, 2017. 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 142 (2017): 1587–1596, doi:10.1121/1.5002887.One application for autonomous underwater vehicles (AUVs) is detecting and classifying hazardous objects on the seabed. An acoustic approach to this problem has been studied in which an acoustic source insonifies seabed target while receiving AUVs with passive sensing payloads discriminate targets based on features of the three dimensional scattered fields. The OASES-SCATT simulator was used to study how scattering data collected by mobile receivers around targets insonified by mobile sources might be used for sphere and cylinder target characterization in terms of shape, composition, and size. The impact of target geometry on these multistatic scattering fields is explored, and a discrimination approach developed in which the source and receiver circle the target with the same radial speed. The frequency components of the multistatic scattering data at different bistatic angles are used to form models for target characteristics. Data are then classified using these models. Classification accuracies were greater than 98% for shape and composition. Regression for target volume showed potential, with 90% chance of errors less than 15%. The significance of this approach is to make classification using low-cost vehicles plausible from scattering amplitudes and the relative angles between the target, source, and receiver vehicles.This work was supported by Battelle

Memory-efficient approximate three-dimensional beamforming

Author Posting. © Acoustical Society of America, 2020. 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 148(6), (2020): 3467-3480, doi:10.1121/10.0002852.Localization of acoustic sources using a sensor array is typically performed by estimating direction-of-arrival (DOA) via beamforming of the signals recorded by all elements. Software-based conventional beamforming (CBF) forces a trade-off between memory usage and direction resolution, since time delays associated with a set of directions over which the beamformer is steered must be pre-computed and stored, limiting the number of look directions to available platform memory. This paper describes a DOA localization method that is memory-efficient for three-dimensional (3D) beamforming applications. Its key lies in reducing 3D look directions [described by azimuth/inclination angles (ϕ, θ) when considering the array as a whole] to a single variable (a conical angle, ζ) by treating the array as a collection of sensor pairs. This insight reduces the set of look directions from two dimensions to one, enabling computational and memory efficiency improvements and thus allowing direction resolution to be increased. This method is described and compared to CBF, with comparisons provided for accuracy, computational speedup, and memory usage. As this method involves the incoherent summation of sensor pair outputs, gain is limited, restricting its use to localization of strong sources—e.g., for real-time acoustic localization on embedded systems, where computation and/or memory are limited.This work was partially supported by the Office of Naval Research, the Defense Advanced Research Projects Agency, and Lincoln Laboratory.2021-06-0

Synchronous-clock range-angle relative acoustic navigation: a unified approach to multi-AUV localization, command, control, and coordination

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rypkema, N., Schmidt, H., & Fischell, E. Synchronous-clock range-angle relative acoustic navigation: a unified approach to multi-AUV localization, command, control, and coordination. Journal of Field Robotics, 2(1), (2022): 774–806, https://doi.org/10.55417/fr.2022026.This paper presents a scalable acoustic navigation approach for the unified command, control, and coordination of multiple autonomous underwater vehicles (AUVs). Existing multi-AUV operations typically achieve coordination manually by programming individual vehicles on the surface via radio communications, which becomes impractical with large vehicle numbers; or they require bi-directional intervehicle acoustic communications to achieve limited coordination when submerged, with limited scalability due to the physical properties of the acoustic channel. Our approach utilizes a single, periodically broadcasting beacon acting as a navigation reference for the group of AUVs, each of which carries a chip-scale atomic clock and fixed ultrashort baseline array of acoustic receivers. One-way travel-time from synchronized clocks and time-delays between signals received by each array element allow any number of vehicles within receive distance to determine range, angle, and thus determine their relative position to the beacon. The operator can command different vehicle behaviors by selecting between broadcast signals from a predetermined set, while coordination between AUVs is achieved without intervehicle communication by defining individual vehicle behaviors within the context of the group. Vehicle behaviors are designed within a beacon-centric moving frame of reference, allowing the operator to control the absolute position of the AUV group by repositioning the navigation beacon to survey the area of interest. Multiple deployments with a fleet of three miniature, low-cost SandShark AUVs performing closed-loop acoustic navigation in real-time provide experimental results validated against a secondary long-baseline positioning system, demonstrating the capabilities and robustness of our approach with real-world data.This work was partially supported by the Office of Naval Research, the Defense Advanced Research Projects Agency, Lincoln Laboratory, and the Reuben F. and Elizabeth B. Richards Endowed Funds at WHOI

Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields

One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7–9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834–875 (2010)]United States. Office of Naval Research (Grant N00014-14-1- 0214

Implementation of a Hydrodynamic Model-Based Navigation System for a Low-Cost AUV Fleet

© 2018 IEEE. This work implements a hydrodynamic model-based localization and navigation system for low-cost autonomous underwater vehicles (AUVs) that are limited to a micro-electro mechanical system (MEMS) inertial measurement unit (IMU). The hydrodynamic model of this work is uniquely developed to directly determine the linear velocities of the vehicle using the measured vehicle angular rates and propeller speed as inputs. The proposed system was tested in the field using a fleet of low-cost Bluefin SandShark AUVs. Implementation of the model-based localization system and fusing of the solution into the vehicle navigation loop was conducted using backseat computers of the AUV fleet that run mission orientated operating suite -interval programming (MOOS-IvP). With the model-based navigation system, the maximum localization error (i.e., in comparison to a long baseline (LBL) based ground-truth position) was limited to 15 m and 30 m for two 650-second and 1070-second long missions. Extrapolation of the position drift shows that the model-based localization system is able to limit the position uncertainty to less than 100 m by the end of hour-long mission; whereas, the drift in the default IMU-based localization solution was over 1 km per hour. This is a considerable improvement by only using a MEMS IMU that generally costs less than 100. Furthermore, this work is a step towards generalizing and automating the process of hydrodynamic modeling, model parameter estimation and data fusion (i.e., fusing the localization solution with those from other available aiding sensors and feeding to the navigation loop) so that a model-based localization system can be implemented in any AUV that has backseat computing capability. Index Terms—Autonomous underwater vehicles, model-based localization, hydrodynamic models, system identification, underwater navigatio

Ezetimibe added to statin therapy after acute coronary syndromes

BACKGROUND: Statin therapy reduces low-density lipoprotein (LDL) cholesterol levels and the risk of cardiovascular events, but whether the addition of ezetimibe, a nonstatin drug that reduces intestinal cholesterol absorption, can reduce the rate of cardiovascular events further is not known. METHODS: We conducted a double-blind, randomized trial involving 18,144 patients who had been hospitalized for an acute coronary syndrome within the preceding 10 days and had LDL cholesterol levels of 50 to 100 mg per deciliter (1.3 to 2.6 mmol per liter) if they were receiving lipid-lowering therapy or 50 to 125 mg per deciliter (1.3 to 3.2 mmol per liter) if they were not receiving lipid-lowering therapy. The combination of simvastatin (40 mg) and ezetimibe (10 mg) (simvastatin-ezetimibe) was compared with simvastatin (40 mg) and placebo (simvastatin monotherapy). The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, unstable angina requiring rehospitalization, coronary revascularization ( 6530 days after randomization), or nonfatal stroke. The median follow-up was 6 years. RESULTS: The median time-weighted average LDL cholesterol level during the study was 53.7 mg per deciliter (1.4 mmol per liter) in the simvastatin-ezetimibe group, as compared with 69.5 mg per deciliter (1.8 mmol per liter) in the simvastatin-monotherapy group (P<0.001). The Kaplan-Meier event rate for the primary end point at 7 years was 32.7% in the simvastatin-ezetimibe group, as compared with 34.7% in the simvastatin-monotherapy group (absolute risk difference, 2.0 percentage points; hazard ratio, 0.936; 95% confidence interval, 0.89 to 0.99; P = 0.016). Rates of pre-specified muscle, gallbladder, and hepatic adverse effects and cancer were similar in the two groups. CONCLUSIONS: When added to statin therapy, ezetimibe resulted in incremental lowering of LDL cholesterol levels and improved cardiovascular outcomes. Moreover, lowering LDL cholesterol to levels below previous targets provided additional benefit