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2010 13th International Conference on Information Fusion最新文献

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Particle filtering with dependent noise 具有相关噪声的粒子滤波
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712052
F. Gustafsson, S. Saha
{"title":"Particle filtering with dependent noise","authors":"F. Gustafsson, S. Saha","doi":"10.1109/ICIF.2010.5712052","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712052","url":null,"abstract":"The theory and applications of the particle filter (PF) have developed tremendously during the past two decades. However, there appear to be no version of the PF readily applicable to the case of dependent process and measurement noise. This is in contrast to the Kalman filter, where the case of correlated noise is a standard modification. Further, the fact that sampling continuous time models give dependent noise processes is an often neglected fact in literature. We derive the optimal proposal distribution in the PF for general and Gaussian noise processes, respectively. The main result is a modified prediction step. It is demonstrated that the original Bootstrap particle filter gets a particular simple and explicit form for dependent Gaussian noise. Finally, the practical importance of dependent noise is motivated in terms of sampling of continuous time models.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123398753","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}
引用次数: 13
GNSS pseudorange error density tracking using Dirichlet Process Mixture 基于Dirichlet过程混合的GNSS伪距误差密度跟踪
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711829
N. Viandier, J. Marais, A. Rabaoui, E. Duflos
{"title":"GNSS pseudorange error density tracking using Dirichlet Process Mixture","authors":"N. Viandier, J. Marais, A. Rabaoui, E. Duflos","doi":"10.1109/ICIF.2010.5711829","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711829","url":null,"abstract":"In satellite navigation system, classical localization algorithms assume that the observation noise is white-Gaussian. This assumption is not correct when the signal is reflected on the surrounding obstacles. That leads to a decrease of accuracy and of continuity of service. To enhance the localization performances, a better observation noise density can be use in an adapted filtering process. This article aims to show how the Dirich-let Process Mixture can be employed to track the observation density on-line. This sequential estimation solution is adapted when the noise is non-stationary. The approach will be tested under a simulation scenario with multiple propagation conditions. Then, this density modeling will be used in Rao-Blackwellised Particle Filter.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123669306","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}
引用次数: 8
Low-cost INS/GPS with nonlinear filtering methods 采用非线性滤波方法的低成本INS/GPS
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712023
Junchuan Zhou, E. Edwan, S. Knedlik, O. Loffeld
{"title":"Low-cost INS/GPS with nonlinear filtering methods","authors":"Junchuan Zhou, E. Edwan, S. Knedlik, O. Loffeld","doi":"10.1109/ICIF.2010.5712023","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712023","url":null,"abstract":"For land-based navigation, Euler angles are often used in INS/GPS integrated navigation systems. However, the trigonometric operations required in the updates and forming of the rotation matrices for transforming the INS measurements from the body frame to the navigation frame turns the system model to be highly nonlinear. Besides, using low-cost MEMS-based IMUs, the gyroscope bias errors must be correctly estimated and compensated, which makes the nonlinearity problem a critical one. In this contribution, three Kalman filtering methods (i.e., Extended Kalman filter with simplified system model, Extended Kalman filter with linearized system model and Unscented Kalman filter with nonlinear system model) are utilized in INS/GPS tightly-coupled integration. Simulations and field experiments are conducted. Numerical results are compared in terms of both estimation accuracy and processing time.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124012666","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}
引用次数: 28
Fusion gain in multi-target tracking 多目标跟踪中的融合增益
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711925
S. Coraluppi, M. Guerriero, C. Carthel
{"title":"Fusion gain in multi-target tracking","authors":"S. Coraluppi, M. Guerriero, C. Carthel","doi":"10.1109/ICIF.2010.5711925","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711925","url":null,"abstract":"This paper introduces an information quality metric and a definition for fusion gain in multi-target tracking systems. We validate the reasonableness of these quantities and illustrate the relationship between fusion gain, scenario difficulty, and tracker effectiveness. The information quality metric is closely related to the information reduction factor, and has direct application to sensor management.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129440842","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}
引用次数: 2
Geometric augmentation of topological track atlas for localization 拓扑轨迹图谱的几何增强定位
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711913
Carsten Hasberg, Stefan Hensel
{"title":"Geometric augmentation of topological track atlas for localization","authors":"Carsten Hasberg, Stefan Hensel","doi":"10.1109/ICIF.2010.5711913","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711913","url":null,"abstract":"In automotive domain localization is typically performed through fusion of observations e.g. GPS positions and roadmaps. A transfer of these strategies to rail vehicle positioning is often impossible, because geometric track maps are not available. Key focus of this contribution is the enlargement of given topological track maps with geometric features, to enable a map-assisted rail vehicle localization based on geometric measurements. Initially we compute the optimal path within the track topology based on local track features that are measured with an eddy current sensor system. Then we process noisy INS positions and estimate the geometric shape of the map segments the measurement train has passed. Finally we augment the corresponding segments with geometric information. The proposed method is validated on real data in a real railway scenario.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128589657","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}
引用次数: 1
A Multi-Disciplinary University Research Initiative in Hard and Soft information fusion: Overview, research strategies and initial results 软硬信息融合的多学科大学研究计划:综述、研究策略和初步成果
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712083
J. Llinas, R. Nagi, D. Hall, John Lavery
{"title":"A Multi-Disciplinary University Research Initiative in Hard and Soft information fusion: Overview, research strategies and initial results","authors":"J. Llinas, R. Nagi, D. Hall, John Lavery","doi":"10.1109/ICIF.2010.5712083","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712083","url":null,"abstract":"The University at Buffalo (UB) Center for Multisource Information Fusion (CMIF) along with a team including the Pennsylvania State University (PSU), Iona College (Iona), and Tennessee State University (TSU) is conducting research to develop a generalized framework, mathematical techniques, and test and evaluation methods to address the ingestion and harmonized fusion of Hard and Soft information in a distributed Level 1 and Level 2 data fusion environment. The primary Research Thrusts addressed are framed around the major functional components of the JDL Fusion Process; these include: 1. Source Characterization of Soft Data input streams including; human observation-direct, indirect, open source inputs, linguistic framing, and text processing. 2. Common Referencing and Alignment of Hard and Soft Data, especially strategies and methods for meta-data generation for Hard-Soft data normalization. 3. Generalized Data Association Strategies and Algorithms for Hard and Soft Data. Robust Estimation Methods that exploit associated Hard and Soft Data. 5. Dynamic Network-based Effects on Hard-Soft Data Fusion Architectures and Methods. 6. Test and Evaluation Methodology Development to include Human-in-the-Loop. 7. Extensibility, Adaptability, and Robustness Assessment. 8. Fusion Process Framework. 9. Technology Concept of Employment. This program is a large, 5-year effort and considered distinctive in being a major academic thrust into the complexities of the hard and soft fusion problem. This paper summarizes the research strategy, the early technology decisions made, and the very early results of both design approaches and prototyping.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128616407","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}
引用次数: 40
Quasi-tracklet fusion accounting for cross-correlation 考虑互相关的准轨道融合
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711957
Yongxin Gao, X. Li
{"title":"Quasi-tracklet fusion accounting for cross-correlation","authors":"Yongxin Gao, X. Li","doi":"10.1109/ICIF.2010.5711957","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711957","url":null,"abstract":"This paper deals with distributed fusion with local quasi-tracklets and provides the optimal linear minimum mean-squared error (LMMSE) fusion, namely optimal quasi-tracklet fusion. We analyze its performance, present a necessary and sufficient condition under which the fusion is identical with the centralized fusion, and exploit its relationships with some existing distributed fusion methods. Numerical results are provided to illustrate its performance compared with the centralized and existing distributed fusion algorithms.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129355008","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}
引用次数: 2
A generative model for 3D range sensors in the Bayesian Occupancy filter framework: Application for fusion in smart home monitoring 贝叶斯占位滤波框架下三维距离传感器的生成模型:融合在智能家居监测中的应用
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5712110
J. Ros, K. Mekhnacha
{"title":"A generative model for 3D range sensors in the Bayesian Occupancy filter framework: Application for fusion in smart home monitoring","authors":"J. Ros, K. Mekhnacha","doi":"10.1109/ICIF.2010.5712110","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5712110","url":null,"abstract":"The utilisation of a network of heterogeneous sensors to track humans and analyse their behaviours in indoor environment is essential due to the high risk of occlusions. For this purpose, the Bayesian Occupancy (BOF) filter was shown efficient to fuse data coming from infrared and visible cameras by providing the occupancy/velocity probability distributions of each spatial cell of the grid representation of the environment. As the main contribution of this paper, we will present a novel generative sensor model intended to be used for 3D sensors providing range information (e.g., time-of-flight cameras). In order to show the effectiveness of our solution, we will present a fusion example using (i) two visible cameras, (ii) one infrared camera, (ii) and one PMD sensor. We will especially show that this fusion scheme significantly increase the robustness of the tracking process.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132070649","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}
引用次数: 3
Doppler-aided target tracking in heavy clutter 杂波条件下多普勒辅助目标跟踪
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711933
D. Musicki
{"title":"Doppler-aided target tracking in heavy clutter","authors":"D. Musicki","doi":"10.1109/ICIF.2010.5711933","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711933","url":null,"abstract":"Target tracking in clutter uses measurements of uncertain origin. In addition to target detections, in every scan the sensor returns clutter measurements. Standard target tracking in clutter most often uses the position measurements only. The tracking then becomes clutter limited, and beyond a limited clutter measurement density target tracking algorithms do not perform. Using the Doppler information of each measurement can significantly increase these limits. Previous publications used Doppler measurements either to improve the data association probabilities only, or to improve trajectory state estimates only. Whilst it helps, it often is not enough. This paper extends popular Integrated Probabilistic Data Association to use Doppler information in the track update step both to enhance the Data Association probabilities, and to improve trajectory state estimation. A simulation study shows that this approach may provide reliable automatic target tracking in the case of severe clutter.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127914690","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}
引用次数: 8
A new fusion algorithm for shadow penetration using visible and midwave infrared polarimetric images 基于可见光和中波红外偏振图像的阴影穿透融合新算法
2010 13th International Conference on Information Fusion Pub Date : 2010-07-26 DOI: 10.1109/ICIF.2010.5711945
Daniel A. Lavigne, M. Breton
{"title":"A new fusion algorithm for shadow penetration using visible and midwave infrared polarimetric images","authors":"Daniel A. Lavigne, M. Breton","doi":"10.1109/ICIF.2010.5711945","DOIUrl":"https://doi.org/10.1109/ICIF.2010.5711945","url":null,"abstract":"This paper presents a new polarimetric image fusion algorithm to discriminate objects lying in shadow areas against cluttered backgrounds. Polarimetric signatures of man-made objects are collected using a fully automated passive polarimetric sensor-suite operating in the visible, shortwave, midwave, and longwave infrared bands. The polarization state of the radiation emitted and/or reflected from objects' surfaces and surrounding background is characterized using the total intensity, the degree of linear polarization, and the phase of the polarization. Using two distinct scenarios, experimental results demonstrate the utility of the proposed image fusion algorithm to exploit the polarized signatures of man-made objects in the visible and midwave infrared bands for shadow penetration purposes.","PeriodicalId":341446,"journal":{"name":"2010 13th International Conference on Information Fusion","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123157197","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}
引用次数: 9
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