L. Mihaylova, D. Angelova, C. N. Canagarajah, D. Bull
{"title":"Algorithms for Mobile Nodes Self-Localisation in Wireless Ad Hoc Networks","authors":"L. Mihaylova, D. Angelova, C. N. Canagarajah, D. Bull","doi":"10.1109/ICIF.2006.301571","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301571","url":null,"abstract":"This paper addresses the problem of position localisation of mobile nodes in ad hoc wireless networks based on received signal strength indicator measurements. Node mobility is modelled as a linear system driven by a discrete command Markov process. Self-localisation of mobile nodes is performed via an interacting multiple model filter consisting of a bank of unscented Kalman filters (IMM-UKF). Estimation of the mobility state, which comprises the position, speed and acceleration of the mobile nodes is accomplished. The performance of the IMM- UKF filter is investigated and compared to a multiple model particle filter (MM PF) by Monte Carlo simulation","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130406131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fusion of trajectory clusters for situation assessment","authors":"L. Snidaro, C. Piciarelli, G. Foresti","doi":"10.1109/ICIF.2006.301658","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301658","url":null,"abstract":"In this paper, we address the problem of identifying anomalous events in the context of a multi sensor surveillance system. Targets' trajectories are analyzed and compared to common patterns of activity represented as clusters of trajectories. Here we extend our previous work to cater for observations provided by multiple cameras observing the same scene. Data fusion is performed within the Dempster-Shafer theory of evidence framework. The proposed approach is validated through experimental results performed in the context of an automatic road traffic monitoring application","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116948141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Adaptive Situation Assessment Based Decision Making System","authors":"F. Mirmoeini, V. Krishnamurthy","doi":"10.1109/ICIF.2006.301583","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301583","url":null,"abstract":"This paper describes the development of a hierarchical situation assessment system using Bayesian networks and also a situation assessment based decision making system for battlespace environment. The situation assessment system consists of two levels of reconfigurable Bayesian networks that are adapted with changes that occur in the battlespace on two different timescales. The decision making system uses this adaptive situation assessment system to make decisions that in turn affect the battlespace dynamics. An algorithm is provided to model these interactions and dynamics of the battlespace. Furthermore, a Markovian model for the battlespace dynamics is provided","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134033139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stochastic Line Search Using UUVs","authors":"M. Sodhi, P. Swaszek, E. Bovio","doi":"10.1109/ICIF.2006.301784","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301784","url":null,"abstract":"Unmanned underwater vehicles (UUVs) are increasingly being used in a diverse range of applications. In one particular application, we analyze UUV operations for location, detection and classification of mines. The mission objective is to search the area of interest, using underwater imaging sensors such as side scan sonars, until either the first mine is located, or it is verified that none can be found. Communication constraints require that the vehicle be connected with physically for downloads. In such as scenario, the search area can be considered as a line, and prior probabilities of finding a mine on the line can be related to external considerations such as the bottom characteristics, etc. The optimization problem is the determination of a sequence of points on the line where the UUV should be configured to return for a data download, so as to minimize the expected mission time. Operational models are defined and analytical expressions and numerical results describe the optimal strategies for searching with several distributions and return point specifications","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134394517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Parameterized Joint Densities with Gaussian and Gaussian Mixture Marginals","authors":"F. Sawo, D. Brunn, U. Hanebeck","doi":"10.1109/ICIF.2006.301684","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301684","url":null,"abstract":"In this paper we attempt to lay the foundation for a novel filtering technique for the fusion of two random vectors with imprecisely known stochastic dependency. This problem mainly occurs in decentralized estimation, e.g., of a distributed phenomenon, where the stochastic dependencies between the individual states are not stored. Thus, we derive parameterized joint densities with both Gaussian marginals and Gaussian mixture marginals. These parameterized joint densities contain all information about the stochastic dependencies between their marginal densities in terms of a parameter vector xi, which can be regarded as a generalized correlation parameter. Unlike the classical correlation coefficient, this parameter is a sufficient measure for the stochastic dependency even characterized by more complex density functions such as Gaussian mixtures. Once this structure and the bounds of these parameters are known, bounding densities containing all possible density functions could be found","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132077866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intelligent Ping Sequencing for Multistatic Sonar Systems","authors":"D. Krout, M. El-Sharkawi, W. Fox, M. Hazen","doi":"10.1109/ICIF.2006.301663","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301663","url":null,"abstract":"We study the problem of determining optimal pinging strategies in multistatic sonar systems with multiple sources. We are specifically investigating algorithms that determine optimal pinging strategies both for generalized search scenarios, and for holding confirmed target tracks with constraints related to maintaining search performance in the rest of the area. An important part of this work is the development of metrics to be used in the optimization procedures. For maintaining search coverage, we used a \"probability of target presence\" metric formulation. This formulation utilizes sonar performance prediction and a Bayesian update equation to incorporate negative information (i.e., searching an area but finding no targets). We also discuss strategies that can be used to increase the performance of a multistatic field, such as the use of bandwidth diversity","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124532739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bio-Inspired Navigation of Chemical Plumes","authors":"M. Porter, J. Vasquez","doi":"10.1109/ICIF.2006.301656","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301656","url":null,"abstract":"The ability of many insects, especially moths, to locate either food or a member of the opposite sex is an amazing achievement. There are numerous scenarios where having this ability embedded into ground-based or aerial vehicles would be invaluable. This paper presents results from a 3-D computer simulation of an unmanned aerial vehicle (UAV) autonomously tracking a chemical plume to its source. The simulation study includes a simulated dynamic chemical plume, 6-degree of freedom, nonlinear aircraft model, and a bio-inspired navigation algorithm. The emphasis of this paper is the development and analysis of the navigation algorithm. The foundation of this algorithm is a fuzzy controller designed to categorize where in the plume the aircraft is located: coming into the plume, in the plume, exiting the plume, or out of the plume","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127765252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimized Visual and Thermal Image Fusion for Efficient Face Recognition","authors":"M. Hanif, Usman Ali","doi":"10.1109/ICIF.2006.301735","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301735","url":null,"abstract":"Data fusion of thermal and visual images is a solution to overcome the drawbacks present in individual thermal and visual images. Data fusion using different approach is discussed and results are presented in this paper. Traditional fusion approaches don't produce useful results for face recognition. An optimized approach for face data fusion is developed which works for face data fusion equally well as for non-face images. This paper presents the implementation of human face recognition system using proposed optimized data fusion of visual and thermal images. Gabor filtering technique, which extracts facial features, is used as a face recognition technique to test the effectiveness of the fusion techniques. It has been found that by using the proposed fusion technique Gabor filter can recognize face even with variable expressions and light intensities","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116315936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple-Hypothesis Trilateration and Tracking with Distributed Radars","authors":"Jelle van Kleef, J. Bergmans, L. Kester, F. Groen","doi":"10.1109/ICIF.2006.301617","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301617","url":null,"abstract":"A novel algorithm to associate and trilaterate detections from multiple distributed radars is presented. The algorithm provides for flexible track state representations. The coordinate system of a track is switched from the measurement coordinates (range-Doppler) to cartesian coordinates when a detection from another sensor is associated to the track. In the case of multiple targets and false alarms we run into the complication of multiple association possibilities. These can be resolved by using a multi-hypothesis algorithm. In general, correctly formed tracks will have more likely associations. Therefore, hypotheses describing these tracks will be favored. Simulations with one or two targets and different false alarm rates show the need to preserve multiple hypotheses of the world state. Tracking performance for various false alarms rates is evaluated","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115554938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Testing Estimator's Credibility - Part II: Other Tests*","authors":"X. R. Li, Zhanlue Zhao","doi":"10.1109/ICIF.2006.301740","DOIUrl":"https://doi.org/10.1109/ICIF.2006.301740","url":null,"abstract":"For pt.I see ibid., p.Z001330-7 (2006). Many estimators and filters provide assessments of their own estimation error. Are these self-assessments trustable? What is the degree to which they are trustable? This is Part II of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It proposes several tests for credibility and a test-based solution to the problem of comparing estimators' credibility. Numerical examples are provided to illustrate the utility and effectiveness of the proposed tests","PeriodicalId":248061,"journal":{"name":"2006 9th International Conference on Information Fusion","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115229610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}