Automated matching of long range underwater acoustic arrivals to predictions using a minimum variance Approach

2021 ◽  
Vol 150 (4) ◽  
pp. A279-A279
Author(s):  
Cristian E. Graupe ◽  
Lora Van Uffelen ◽  
Peter F. Worcester ◽  
Matthew Dzieciuch ◽  
Bruce M. Howe
Keyword(s):  
Long Range ◽  
Minimum Variance ◽  
Underwater Acoustic ◽  
Variance Approach

scholarly journals Design of Self-Tuning Regulator for Large-Scale Interconnected Hammerstein Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Mourad Elloumi ◽  
Samira Kamoun
Keyword(s):  
Large Scale ◽  
Recursive Algorithm ◽  
Minimum Variance ◽  
Parametric Estimation ◽  
Hammerstein Model ◽  
Stochastic Nonlinear Systems ◽  
Hydraulic Systems ◽  
Self Tuning ◽  
Variance Approach ◽  
Error Method

This paper deals with the self-tuning regulator for large-scale stochastic nonlinear systems, which are composed of several interconnected nonlinear monovariable subsystems. Each interconnected subsystem is described by discrete Hammerstein model with unknown and time-varying parameters. This self-tuning control is developed on the basis of the minimum variance approach and is combined by a recursive algorithm in the estimation step. The parametric estimation step is performed on the basis of the prediction error method and the least-squares techniques. Simulation results of the proposed self-tuning regulator for two interconnected nonlinear hydraulic systems show the reliability and effectiveness of the developed method.

scholarly journals Stereo Camera Head-Eye Calibration Based on Minimum Variance Approach Using Surface Normal Vectors

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3706 ◽  
Author(s):  
Joong-Jae Lee ◽  
Mun-Ho Jeong
Keyword(s):  
Vision System ◽  
Real Data ◽  
Humanoid Robots ◽  
Calibration Method ◽  
Minimum Variance ◽  
Kinematic Data ◽  
Stereo Camera ◽  
Surface Normal ◽  
Normal Vectors ◽  
Variance Approach

This paper presents a stereo camera-based head-eye calibration method that aims to find the globally optimal transformation between a robot’s head and its eye. This method is highly intuitive and simple, so it can be used in a vision system for humanoid robots without any complex procedures. To achieve this, we introduce an extended minimum variance approach for head-eye calibration using surface normal vectors instead of 3D point sets. The presented method considers both positional and orientational error variances between visual measurements and kinematic data in head-eye calibration. Experiments using both synthetic and real data show the accuracy and efficiency of the proposed method.

scholarly journals The Effect of Attenuation from Fish Shoals on Long-Range, Wide-Area Acoustic Sensing in the Ocean

2019 ◽  
Vol 11 (21) ◽  
pp. 2464 ◽  
Author(s):  
Daniel Duane ◽  
Byunggu Cho ◽  
Ankita D. Jain ◽  
Olav Rune Godø ◽  
Nicholas C. Makris
Keyword(s):  
Remote Sensing ◽  
Long Range ◽  
Cross Sections ◽  
Electromagnetic Waves ◽  
Low Frequency ◽  
Wide Area ◽  
Line Transect ◽  
Acoustic Sensing ◽  
Underwater Acoustic ◽  
Primary Means

Acoustics is the primary means of long-range and wide-area sensing in the ocean due to the severe attenuation of electromagnetic waves in seawater. While it is known that densely packed fish groups can attenuate acoustic signals during long-range propagation in an ocean waveguide, previous experimental demonstrations have been restricted to single line transect measurements of either transmission or backscatter and have not directly investigated wide-area sensing and communication issues. Here we experimentally show with wide-area sensing over 360° in the horizontal and ranges spanning many tens of kilometers that a single large fish shoal can significantly occlude acoustic sensing over entire sectors spanning more than 30° with corresponding decreases in detection ranges by roughly an order of magnitude. Such blockages can comprise significant impediments to underwater acoustic remote sensing and surveillance of underwater vehicles, marine life and geophysical phenomena as well as underwater communication. This makes it important to understand the relevant mechanisms and accurately predict attenuation from fish in long-range underwater acoustic sensing and communication. To do so, we apply an analytical theory derived from first principles for acoustic propagation and scattering through inhomogeneities in an ocean waveguide to model propagation through fish shoals. In previous experiments, either the attenuation from fish in the shoal or the scattering cross sections of fish in the shoal were measured but not both, making it impossible to directly confirm a theoretical prediction on attenuation through the shoal. Here, both measurements have been made and they experimentally confirm the waveguide theory presented. We find experimentally and theoretically that attenuation can be significant when the sensing frequency is near the resonance frequency of the shoaling fish. Negligible attenuation was observed in previous low-frequency ocean acoustic waveguide remote sensing (OAWRS) experiments because the sensing frequency was sufficiently far from the swimbladder resonance peak of the shoaling fish or the packing densities of the fish shoals were not sufficiently high. We show that common heuristic approaches that employ free space scattering assumptions for attenuation from fish groups can lead to significant errors for applications involving long-range waveguide propagation and scattering.

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