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DESIGN OF DECISION DEVICE FOR THE ADAPTATION OF DECISION DIRECTED EQUALIZERS

DESIGN OF DECISION DEVICE FOR THE ADAPTATION OF DECISION DIR...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Atulya Yellepeddi James C. Preisig Electrical Eng./Applied Ocean Physics and Eng. MIT-WHOI Joint Program Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution

ISBN: (纸本)9781479903573

Adaptation of the coefficients of an equalizer usually takes place in the decision directed mode. The decision used for adaptation has a profound influence on the performance of the equalizer. In this work, we consider the influence of the probabilistic model used by a soft information decision device on the performance of the equalizer. It is shown that the equalizer output is distributed as a Gaussian Mixture, and these statistics are used to form a soft-decision device. We show that this is very near optimal in the sense of the Recursive Expected Least Squares algorithm introduced in prior work. Sub-optimal decision devices that are often more practical are also introduced and the loss of performance as a result of using these is considered.

关键词： Equalizers adaptive signal processing adaptive equalizers time-varying channels

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Soft-Adaptive Turbo Equalization: Using Soft Information in Adaptation

Soft-Adaptive Turbo Equalization: Using Soft Information in ...

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46th Asilomar Conference on Signals, Systems and Computers

作者： Yellepeddi, Atulya Preisig, James C. Electrical Engineering/Applied Ocean Science and Engineering MIT-WHOI Joint Program USA

ISBN: (纸本)9781467350518

Turbo equalizers have been exploited for underwater wireless communication due to their excellent practical performance. As the equalizer is adaptive, it is possible to take advantage of the soft information available from the decoder in the adaptation process. In this paper, we consider a method to do this and compare it with the use of soft information in feedback, which is a method that has been considered in the past. Data from the KAM11 experiment demonstrates that using soft information in adaptation can improve performance over using it only in feedback. We also consider combining these different approaches and how this affects performance.

关键词： adaptive equalisers marine communication turbo codes

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Soft-adaptive turbo equalization: Using soft information in adaptation

Soft-adaptive turbo equalization: Using soft information in ...

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Asilomar Conference on Signals, Systems & Computers

作者： Atulya Yellepeddi James C. Preisig Electrical Engineering/Applied Ocean Science and Engineering WHOI Joint Program MIT USA Applied Ocean Science and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA

ISBN: (纸本)9781467350501

关键词： Using how this soft information Equalizers Worm gears Turbo CARRIER SYSTEM Feedback Equalization decoders

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Exactly sparse delayed-state filters

Exactly sparse delayed-state filters

引用

2005 IEEE International Conference on Robotics and Automation

作者： Eustice, Ryan M. Singh, Hanumant Leonard, John J. MIT/WHOI Joint Program in Applied Ocean Science and Engineering Woods Hole Oceanographic Institution Woods Hole MA United States Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole MA United States Department of Ocean Engineering Massachusetts Institute of Technology Cambridge MA United States

ISBN: (纸本)078038914X

This paper presents the novel insight that the SLAM information matrix is exactly sparse in a delayed-state framework. Such a framework is used in view-based representations of the environment which rely upon scan-matching raw sensor data. Scan-matching raw data results in virtual observations of robot motion with respect to a place its previously been. The exact sparseness of the delayed-state information matrix is in contrast to other recent feature-based SLAM information algorithms like Sparse Extended Information Filters or Thin Junction Tree Filters. These methods have to make approximations in order to force the feature-based SLAM information matrix to be sparse. The benefit of the exact sparseness of the delayed-state framework is that it allows one to take advantage of the information space parameterization without having to make any approximations. Therefore, it can produce equivalent results to the "full-covariance" solution. ©2005 IEEE.

关键词： Digital filters

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Improved vehicle based multibeam bathymetry using sub-maps and SLAM

Improved vehicle based multibeam bathymetry using sub-maps a...

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2005 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： C. Roman H. Singh MIT/WHOI Joint Program in Applied Ocean Science and Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA

This paper presents an algorithm to improve sub-sea acoustic multibeam bottom mapping based on the simultaneous mapping and localization (SLAM) methodology. Multibeam bathymetry from underwater water vehicles can yield valuable large scale terrain maps of the sea door, but the overall accuracy of these maps is typically limited by the accuracy of the vehicle position estimates. The solution presented here uses small bathymetric patches created over short time scales in a sub-mapping context. These patches are registered with respect to one another and assembled in a single coordinate frame to produce a more accurate terrain estimate and provide improved renavigation of the vehicle trajectory. The mapping is implemented using a delayed state extended Kalman filter (EKF) and results are shown for a real world multibeam data set collected at the mid-Atlantic ridge using the JASON ROV.

关键词： Simultaneous localization and mapping Terrain mapping Marine vehicles Underwater vehicles Underwater acoustics Large-scale systems Yield estimation Assembly Delay Remotely operated vehicles

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Exactly Sparse Delayed-State Filters

Exactly Sparse Delayed-State Filters

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IEEE International Conference on Robotics and Automation (ICRA)

作者： R.M. Eustice H. Singh J.J. Leonard MIT/WHOI Joint Program in Applied Ocean Science and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA Department of Ocean Engineering Massachusetts Institute of Technology Cambridge MA USA

This paper presents the novel insight that the SLAM information matrix is exactly sparse in a delayed-state framework. Such a framework is used in view-based representations of the environment which rely upon scan-matching raw sensor data. Scan-matching raw data results in virtual observations of robot motion with respect to a place its previously been. The exact sparseness of the delayed-state information matrix is in contrast to other recent feature based SLAM information algorithms like Sparse Extended Information Filters or Thin Junction Tree Filters. These methods have to make approximations in order to force the feature-based SLAM information matrix to be sparse. The benefit of the exact sparseness of the delayed-state framework is that it allows one to take advantage of the information space parameterization without having to make any approximations. Therefore, it can produce equivalent results to the “full-covariance” solution.

关键词： Delay Simultaneous localization and mapping Navigation Cameras oceans Information filters Sparse matrices Information filtering Remotely operated vehicles Robot vision systems

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Visually augmented navigation in an unstructured environment using a delayed state history

Visually augmented navigation in an unstructured environment...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： R. Eustice O. Pizarro H. Singh MIT/WHOI Joint Program in Applied Ocean Science and Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Woods Hole MA USA

This work describes a framework for sensor fusion of navigation data with camera-based 5 DOF relative pose measurements for 6 DOF vehicle motion in an unstructured 3D underwater environment. The fundamental goal of this work is to concurrently estimate online current vehicle position and its past trajectory. This goal is framed within the context of improving mobile robot navigation to support sub-sea science and exploration. Vehicle trajectory is represented by a history of poses in an augmented state Kalman filter. Camera spatial constraints from overlapping imagery provide partial observation of these poses and are used to enforce consistency and provide a mechanism for loop-closure. The multi-sensor camera + navigation framework is shown to have compelling advantages over a camera-only based approach by: 1) improving the robustness of pairwise image registration, 2) setting the free gauge scale, and 3) allowing for a unconnected camera graph topology. Results are shown for a real world data set collected by an autonomous underwater vehicle in an unstructured undersea environment.

关键词： Navigation Delay History Cameras Underwater vehicles Robot vision systems Sensor fusion Motion measurement Mobile robots Robustness

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Micro-bathymetric mapping using acoustic range images

Micro-bathymetric mapping using acoustic range images

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oceanS

This work focuses on the creation of high resolution micro-bathymetric maps using a high frequency pencil beam sonar. These maps typically cover areas of 10's to 100's of square meters. Data is collected using a sonar mounted to an underwater vehicle that can be positioned at discrete locations on the sea floor or flown in a survey pattern above the bottom. Specifically, we are focused on improving the accuracy of these terrain maps by merging sonar pings taken from multiple vantage points over the same location. This requires the adaption of data registration techniques to handle errors related to the sonar sensor. The registration can also be modified to incorporate the navigation data available from an instrumented underwater vehicle. A two axis scanning sonar was used to gather data in the form of densely sampled range images. The data registration works on the 3D projection of these range images in a scan-matching manner. Through this process regions occluded in a single scan are filled with data available from other scans and individual pings which show a poor return are removed. Refined estimates of the scan vantage points are also generated during the registration. The initial estimates of these locations are provided by navigation data. The practical application of this work complements photographic mapping when visibility is limited. It also provides additional measurements which can be used to improve vehicle navigation.

关键词： Sonar navigation Sonar measurements Remotely operated vehicles Underwater vehicles Sea floor Underwater acoustics Layout oceans Acoustical engineering Acoustic beams

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Coherent source direction estimation for three-row bathymetric sidescan sonars

Coherent source direction estimation for three-row bathymetr...

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Proceedings of the oceanS '99 MTS/IEEE - Riding the Crest into the 21st Century

作者： Xu, Wen Stewart, W.Kenneth MIT/WHOI Joint Program in Applied Ocean Physics and Engineering Cambridge United States

In the context of three-row bathymetric sidescan sonars, a coherent source direction estimator (CSDE) is proposed to resolve two sources from different direction. This method is compared with the ESPRIT-based approach using different sonar models. The simulations show that CSDE works very well for highly coherent sources and at the signal-to-noise ratio above 10dB while the ESPRIT-based method is quite robust for the incoherent source signal model. In addition, CSDE gives the source time series estimation on the basis of the direction estimation as well.

关键词： Sonar

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Coherent source direction estimation for three-row bathymetric sidescan sonars

Coherent source direction estimation for three-row bathymetr...

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oceanS

作者： Wen Xu W.K. Stewart MIT/WHOI Joint Program in Applied Ocean Physics and Engineering Cambridge MA USA Virtual Marine Associates Inc. Fort Pierce FL USA

In practical applications with bathymetric sidescan sonar, the multipath reflection and other directional interferences are the key limiting factors for a better performance. To deal with this problem, a multiple-row system can be used to resolve the multipath reflections from the direct signal instead of smoothing the measurements over some time and/or angle intervals as previously widely investigated. However, most current algorithms for signal direction-of-arrival estimation fail when the sources from different directions are coherent, which often occurs in a shallow water multipath environment. In the context of three-row bathymetric sidescan sonars, this paper proposes a coherent source direction estimator (CSDE) to resolve two sources from different directions. This method is compared with the ESPRIT-based approach using different sonar data models. The simulations show that CSDE works very well for highly coherent sources at the angular separation of 10/spl deg/ between two sources and at the signal-to-noise ratio above 10 dB while the ESPRIT-based method is quite robust for the incoherent source signal model. In addition, CSDE gives the source time series estimation on the basis of the direction estimation as well. Analyses to the interference field associated with the sidescan sonar show that a model with two or three simultaneously received signals describes even some shallow water fields very well. These preliminary results suggest that the combination of above two approaches could replace the currently used differential phase technique to get a better performance in shallow water without significant increase of the system cost.

关键词： Sonar measurements Reflection Interference Signal resolution Sonar applications Smoothing methods Time measurement Direction of arrival estimation Water resources Data models

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