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Conference on sensor fusion - architectures, algorithms, and applications VI

作者： Biel, L Wide, P Univ Orebro Ctr Appl Autonomous Sensor Syst Orebro Sweden

ISBN: (纸本)0819444812

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

关键词： sensors sensor fusion Data fusion Fuzzy systems Carbon monoxide Oxygen Systems modeling Environmental sensing Control systems Signal processing

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The Continuum fusion theory of signal detection applied to a bi-modal fusion problem

The Continuum Fusion theory of signal detection applied to a...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Schaum, A. USN Res Lab Washington DC 20375 USA

ISBN: (纸本)9780819486387

A new formalism has been developed that produces detection algorithms for model-based problems, in which one or more parameter values is unknown. Continuum fusion can be used to generate different flavors of algorithm for any composite hypothesis testing problem. The methodology is defined by a fusion logic that can be translated into max/min conditions. Here it is applied to a simple sensor fusion model, but one for which the generalized likelihood ratio test is intractable. By contrast, a fusion-based response to the same problem can be devised that is solvable in closed form and represents a good approximation to the GLR test.

关键词： bi-modal continuum fusion detector algorithm

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Proceedings of SPIE - The International Society for Optical Engineering

Proceedings of SPIE - The International Society for Optical ...

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sensor fusion: architectures, algorithms and applications V

The proceedings contains 33 papers from SPIE 2001 conference on application of sensor fusion: architectures, algorithms, and applications V. The topics discussed includes;feature and decision level fusion;bayesian, neural networks, and genetic algorithms;image data fusion and its applications;image data fusion and its applications;military applications;fusion concepts and architectures;miscellaneous applications and fuzzy logic approaches.

关键词： sensor data fusion

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A fuzzy model-based multi-sensor data fusion system

A fuzzy model-based multi-sensor data fusion system

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Conference on sensor fusion - architectures, algorithms, and applications V

作者： Prajitno, P Mort, N Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD S Yorkshire England

ISBN: (纸本)0819440809

A fuzzy model-based multi-sensor data fusion system is presented in this paper. The system is capable of accommodating both non-linear sensors of the same type and different (non-commensurate) sensors and to give accurate information about the observed system state by combining readings from them at feature/decision level. The data fusion system consists of process model and knowledge-based sensor model units based on a fuzzy inference system that predicts the future system and sensor states based on the previous states and the inputs. The predicted state is used as a reference datum in the sensor validation process which is conducted through a fuzzy classifier to categorise each sensor reading as a valid or invalid datum. The data fusion unit combines the valid sensor data to generate the feature/decision output. The corrector unit functions as a filtering unit to provide the final decision on the value of the current state based on the current measurement (fused output) and the predicted state. The results of the simulation of this system and other data fusion systems have been compared to justify the capability of the system.

关键词： multisensor data fusion fuzzy inference system function approximation predictive-based data fusion method

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Decision fusion strategies for target detection with a three-sensor suite

Decision fusion strategies for target detection with a three...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Dasarathy, BV Dynetics Inc. (United States)

ISBN: (纸本)081942482X

Boolean logic based decision fusion strategies for target detection with two sensors have been studied in detail in the literature over the years. Increasing the number of sensors to three, offers an aided dimension of flexibility in the design of fusion strategies. One could visualize a single stage fusion wherein the decision outputs of all the three sensor subsystems are fused simultaneously under a variety of strategies such as AND logic, or majority (simple or firm decisions only) logic, or a no-firm contradiction logic. Alternatively, one could explore a two-stage fusion strategy, wherein either an AND or an OR logic is used at the first stage combining the decisions of two of the sensor subsystems, followed by a similar logic choice combining the fused decision from the first level with the decision from the third sensor subsystem. Of these strategies, while some may turn out to be equivalent in a mathematical sense, others remain clearly unique. The study analyzes these strategies to assess their relative benefits. The papers concludes with a brief discussion on possible extensions in terms of temporal fusion strategies that exploit information derived from multiple looks and the potential for application to real-world problems such as mine detection.

关键词： sensor fusion decision fusion fusion strategies three-sensors suite mine detection

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Integrated Multi-sensor fusion for Mapping and Localization in Outdoor Environments for Mobile Robots

Integrated Multi-sensor Fusion for Mapping and Localization ...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Emter, Thomas Petereit, Janko Fraunhofer Inst Optron Syst Technol & Image Explo Karlsruhe Germany

ISBN: (纸本)9781628410587

An integrated multi-sensor fusion framework for localization and mapping for autonomous navigation in unstructured outdoor environments based on extended Kalman filters (EKF) is presented. The sensors for localization include an inertial measurement unit, a GPS, a fiber optic gyroscope, and wheel odometry. Additionally a 3D LIDAR is used for simultaneous localization and mapping (SLAM). A 3D map is built while concurrently a localization in a so far established 2D map is estimated with the current scan of the LIDAR. Despite of longer run-time of the SLAM algorithm compared to the EKF update, a high update rate is still guaranteed by sophisticatedly joining and synchronizing two parallel localization estimators.

关键词： multi-sensor fusion extended Kalman filter particle filter SLAM autonomous mobile robot asynchronous fusion 3D LIDAR mapping

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Practical Considerations in Bayesian fusion of Point sensors

Practical Considerations in Bayesian Fusion of Point Sensors

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Johnson, Kevin Minor, Christian USN Res Lab Washington DC 20375 USA Nova Res Inc Alexandria VA 22308 USA

ISBN: (纸本)9780819490858

sensor data fusion is and has been a topic of considerable research, but rigorous and quantitative understanding of the benefits of fusing specific types of sensor data remains elusive. Often, sensor fusion is performed on an ad hoc basis with the assumption that overall detection capabilities will improve, only to discover later, after expensive and time consuming laboratory and/or field testing that little advantage was gained. The work presented here will discuss these issues with theoretical and practical considerations in the context of fusing chemical sensors with binary outputs. Results are given for the potential performance gains one could expect with such systems, as well as the practical difficulties involved in implementing an optimal Bayesian fusion strategy with realistic scenarios. Finally, a discussion of the biases that inaccurate statistical estimates introduce into the results and their consequences is presented.

关键词： sensor fusion Bayes decision theory

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Decision fusion using channels with communication constraints

Decision fusion using channels with communication constraint...

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Conference on sensor fusion - architectures, algorithms, and applications

作者： Yu, CT Varshney, PK Nan-Tai Institute of Technology (Taiwan) Syracuse Univ. (United States)

ISBN: (纸本)081942482X

A decentralized detection system usually contains a number of remotely located local sensors that observe a common phenomenon and a data fusion center that makes a final decision. The local sensors are linked to the data fusion center by transmission channels. In this paper, some aspects of decision fusion problems with communication constraints are considered. Two interesting issues, namely, bandwidth allocation among the channels linking local sensors to the fusion center, and the trade-off between the number of sensors and the number of likelihood-ratio quantization levels at local sensors. are studied. Examples are presented for illustration.

关键词： bandwidth allocation sampling quantization data fusion distributed detection

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Implementation and testing of a sensor-netting algorithm for early warning and high confidence C/B threat detection

Implementation and testing of a sensor-netting algorithm for...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Gruber, Thomas Grim, Larry Fauth, Ryan Tercha, Brian Powell, Chris Steinhardt, Kristin MESH Inc Oxford PA 19363 USA

ISBN: (纸本)9780819486387

Large networks of disparate chemical/biological (C/B) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A data fusion algorithm design was completed in a Phase I SBIR effort and development continues in the Phase ii SBIR effort. The initial implementation and testing of the algorithm has produced some performance results. The algorithm accepts point and/or standoff sensor data, and event detection data (e. g., the location of an explosion) from various ISR sensors (e.g., acoustic, infrared cameras, etc.). These input data are preprocessed to assign estimated uncertainty to each incoming piece of data. The data are then sent to a weighted tomography process to obtain a consensus threat map, including estimated threat concentration level uncertainty. The threat map is then tested for consistency and the overall confidence for the map result is estimated. The map and confidence results are displayed on a COP. The benefits of a modular implementation of the algorithm and comparisons of fused /un-fused data results will be presented. The metrics for judging the sensor-netting algorithm performance are warning time, threat map accuracy (as compared to ground truth), false alarm rate, and false alarm rate v. reported threat confidence level.

关键词： sensor netting algorithm fusion tomography map uncertainty consistency

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Multisensor data fusion for obstacle tracking using neuro-fuzzy estimation algorithms

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Proceedings of SPIE - The International Society for Optical Engineering 1994年 2233卷 112-123页

作者： Doyle, Rory S. Harris, C.J. Univ. of Southampton Highfield Southampton UK

ISBN: (纸本)0819415375;9780819415370

The problem addressed in this paper is that of estimating the tracks of dynamic obstacles in the environment of a helicopter operating in hazardous conditions. Fuzzy logic and neural networks have shown their strength in recent years in the solutions to non-linear problems. The aim of this paper is to present neuro-fuzzy data fusion algorithms which can be used to fuse information provided by multiple spatially separate sensors engaged in the tracking of obstacles whose dynamics are a priori unknown.

关键词： sensor data fusion

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