检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

18 篇 会议

馆藏范围

18 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

11 篇 工学
- 5 篇 电气工程
- 5 篇 电子科学与技术（可...
- 5 篇 控制科学与工程
- 4 篇 计算机科学与技术...
- 3 篇 软件工程
- 2 篇 信息与通信工程
- 1 篇 航空宇航科学与技...
- 1 篇 安全科学与工程
8 篇 理学
- 5 篇 数学
- 3 篇 系统科学
- 1 篇 统计学（可授理学、...
2 篇 管理学
- 2 篇 图书情报与档案管...

主题

5 篇 target tracking
5 篇 kalman filters
3 篇 particle measure...
3 篇 covariance matri...
3 篇 equations
2 篇 measurement erro...
2 篇 proposals
2 篇 bandpass filters
2 篇 software measure...
2 篇 bayesian methods
2 篇 collision avoida...
2 篇 approximation me...
2 篇 time measurement
2 篇 estimation
2 篇 filtering algori...
1 篇 formations
1 篇 noise measuremen...
1 篇 function approxi...
1 篇 software algorit...
1 篇 filtering

机构

6 篇 data fusion algo...
5 篇 data fusion algo...
4 篇 data fusion algo...
1 篇 department senso...
1 篇 dept. sensor dat...
1 篇 dept. sensor dat...
1 篇 data fusion algo...
1 篇 intelligent sens...
1 篇 karlsruhe
1 篇 intelligent sens...
1 篇 fgan research in...
1 篇 fgan research in...
1 篇 d-53343 wachtber...
1 篇 data fusion algo...
1 篇 dept. sensor dat...
1 篇 data fusion algo...
1 篇 intelligent sens...

作者

8 篇 fränken dietrich
7 篇 dietrich franken
3 篇 feldmann michael
3 篇 hanebeck uwe d.
3 篇 uwe d. hanebeck
3 篇 vesa klumpp
2 篇 felix sawo
2 篇 michael feldmann
2 篇 klumpp vesa
1 篇 schmidt m.
1 篇 d. franken
1 篇 m. ulmke
1 篇 baum marcus
1 篇 hüpper andreas
1 篇 ulmke m.
1 篇 frederik beutler
1 篇 fränken d.
1 篇 koch wolfgang
1 篇 julian horst
1 篇 m. schmidt

语言

18 篇 英文

检索条件"机构=Data Fusion Algorithms & Software"

共 18 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Unified tracking and fusion for airborne collision avoidance using log-polar coordinates

Unified tracking and fusion for airborne collision avoidance...

引用

15th International Conference on Information fusion, fusion 2012

作者： Fränken, Dietrich Hüpper, Andreas Data Fusion Algorithms and Software Cassidian D-89077 Ulm Germany

ISBN: (纸本)9780982443859

Collision avoidance applications require state estimators that are able to deliver estimates of relevant quantities with sufficient quality under hard real-time constraints. In this paper, we will present a unified approach to tracking and data fusion in this context. The proposed approach is easy to implement and allows for a kinematics integration of data stemming from a variety of sensor types. Initialization, prediction, and update in a common state space extended Kalman filter are elaborated. Simulation results show strengths and weaknesses of the proposed approach. © 2012 ISIF (Intl Society of Information Fusi).

关键词： Collision avoidance

来源：评论

学校读者我要写书评

暂无评论

Unified tracking and fusion for airborne collision avoidance using log-polar coordinates

Unified tracking and fusion for airborne collision avoidance...

引用

International Conference on Information fusion

作者： Dietrich Fränken Andreas Hüpper Data Fusion Algorithms & Software Cassidian Ulm Germany

关键词： Equations Kalman filters Optical sensors Radar tracking Mathematical model Collision avoidance Jacobian matrices

来源：评论

学校读者我要写书评

暂无评论

The sliced Gaussian Mixture Filter with adaptive state decomposition depending on linearization error

The sliced Gaussian Mixture Filter with adaptive state decom...

引用

作者： Klumpp, Vesa Beutler, Frederik Hanebeck, Uwe D. Fränken, Dietrich Germany Data Fusion Algorithms and Software EADS Deutschland GmbH D-89077 Ulm Germany

ISBN: (纸本)9780982443811

In this paper, a novel nonlinear/nonlinear model decomposition for the Sliced Gaussian Mixture Filter is presented. Based on the level of nonlinearity of the model, the overall estimation problem is decomposed into a "severely" nonlinear and a "slightly" nonlinear part, which are processed by different estimation techniques. To further improve the efficiency of the estimator, an adaptive state decomposition algorithm is introduced that allows decomposition according to the linearization error for nonlinear system and measurement models. Simulations show that this approach has orders of magnitude less complexity compared to other state of the art estimators, while maintaining comparable estimation errors.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Extended object and group tracking: A comparison of random matrices and random hypersurface models

Extended object and group tracking: A comparison of random m...

引用

40th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Service Science - Neue Perspektiven fur die Informatik, INFORMATIK 2010

作者： Baum, Marcus Feldmann, Michael Fränken, Dietrich Hanebeck, Uwe D. Koch, Wolfgang Karlsruhe Germany Dept. Sensor Data and Information Fusion Fraunhofer FKIE Wachtberg Germany Data Fusion Algorithms and Software EADS Deutschland GmbH Ulm Germany

ISBN: (纸本)9783885792703

Based on previous work of the authors, this paper provides a comparison of two different tracking methodologies for extended objects and group targets, where the true shape of the extent is approximated by an ellipsoid. Although both methods exploit usual sensor data, i.e., position measurements of varying scattering centers, the distinctions are a consequence of the different modeling of the extent as a symmetric positive definite random matrix on the one hand and an elliptic random hypersurface model on the other. Besides analyzing the fundamental assumptions and a comparison of the properties of these tracking methods, simulation results are presented based on a static tracking environment to highlight especially the differences in the update step for the extension estimate.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Sliced Gaussian Mixture Filter with adaptive state decomposition depending on linearization error

The Sliced Gaussian Mixture Filter with adaptive state decom...

引用

International Conference on Information fusion

作者： Vesa Klumpp Frederik Beutler Uwe D. Hanebeck Dietrich Franken Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute of Anthropomatics Karlsruhe Institute of Technology Germany Data Fusion Algorithms and Software EADS Deutschland GmbH Ulm Germany

In this paper, a novel nonlinear/nonlinear model decomposition for the Sliced Gaussian Mixture Filter is presented. Based on the level of nonlin-earity of the model, the overall estimation problem is decomposed into a "severely" nonlinear and a "slightly" nonlinear part, which are processed by different estimation techniques. To further improve the efficiency of the estimator, an adaptive state decomposition algorithm is introduced that allows decomposition according to the linearization error for nonlinear system and measurement models. Simulations show that this approach has orders of magnitude less complexity compared to other state of the art estimators, while maintaining comparable estimation errors.

关键词： Approximation methods Adaptation model Estimation Computational modeling Covariance matrix Kalman filters Visualization

来源：评论

学校读者我要写书评

暂无评论

Tracking of extended objects and group targets using random matrices-a performance analysis

Tracking of extended objects and group targets using random ...

引用

39th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Im Focus das Leben, INFORMATIK 2009

作者： Feldmann, Michael Fränken, Dietrich Dept. Sensor Data and Information Fusion FGAN-FKIE Wachtberg Germany Data Fusion Algorithms and Software EADS Deutschland GmbH Ulm Germany

ISBN: (纸本)9783885792482

The task of tracking extended objects or (partly) unresolvable group targets raises new challenges for both data association and track maintenance. Due to limited sensor resolution capabilities, group targets (i. e., a number of closely spaced targets moving in a coordinated fashion) may show a similar detection pattern as extended objects, namely a varying number of detections whose spread is determined by both the statistical sensor errors as well as the physical extension of the group or extended object. Different tracking approaches treating these situations have been proposed where physical extension is represented by a symmetric positive definite random matrix. In this paper, a recently published Bayesian approach is discussed with regard to the estimator's self-assessment of the estimation error for both kinematics and extension.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Advances on Tracking of Extended Objects and Group Targets using Random Matrices

Advances on Tracking of Extended Objects and Group Targets u...

引用

International Conference on Information fusion

作者： Michael Feldmann Dietrich Franken FGAN Research Institute for Communication Information Processing and Ergonomics (FKIE) Data Fusion Algorithms & Software EADS Deutschland GmbH

ISBN: (纸本)9780982443804

The task of tracking extended objects or (partly) unresolvable group targets raises new challenges for both data association and track maintenance. Due to limited sensor resolution capabilities, group targets (i. e., a number of closely spaced targets moving in a coordinated fashion) may show a similar detection pattern as extended objects, namely a varying number of detections whose spread is determined by both the statistical sensor errors as well as the physical extension of the group or extended object. Different tracking approaches treating these situations have been proposed where physical extension is represented by a random symmetric positive definite matrix. This paper discusses some results that should give deeper insight into behavior and performance analysis of these approaches. Further improvements are presented.

关键词： Target tracking Extended targets Group targets Formations Sensor resolution Random matrices Matrix-variate analysis

来源：评论

学校读者我要写书评

暂无评论

Extension of the Sliced Gaussian Mixture Filter with application to cooperative passive target tracking

Extension of the Sliced Gaussian Mixture Filter with applica...

引用

International Conference on Information fusion

作者： Julian Horst Felix Sawo Vesa Klumpp Uwe D. Hanebeck Dietrich Franken Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute of Anthropomatics Universität Karlsruhe Germany Data Fusion Algorithms and Software EADS Deutschland GmbH Ulm Germany

ISBN: (纸本)9780982443804

This paper copes with the problem of nonlinear Bayesian state estimation. A nonlinear filter, the sliced Gaussian mixture filter (SGMF), employs linear substructures in the nonlinear measurement and prediction model in order to simplify the estimation process. Here, a special density representation, the sliced Gaussian mixture density, is used to derive an exact solution of the Chapman-Kolmogorov equation. The sliced Gaussian mixture density is obtained by a systematic and deterministic approximation of a continuous density minimizing a certain distance measure. In contrast to previous work, improvements of the SGMF presented here include an extended system model and the processing of multi-dimensional nonlinear subspaces. As an application for the SGMF, cooperative passive target tracking, where sensors take angular measurements from a target, is considered in this paper. Finally, the performance of the proposed estimator is compared to the marginalized particle filter (MPF) in simulations.

关键词： Passive filters Target tracking

来源：评论

学校读者我要写书评

暂无评论

The sliced gaussian mixture filter for efficient nonlinear estimation

The sliced gaussian mixture filter for efficient nonlinear e...

引用

11th International Conference on Information fusion, fusion 2008

作者： Klumpp, Vesa Sawo, Felix Hanebeck, Uwe D. Fränken, Dietrich Germany Data Fusion Algorithms and Software EADS Deutschland GmbH D-89077 Ulm Germany

ISBN: (纸本)9783000248832

This paper addresses the efficient state estimation for mixed linear/nonlinear dynamic systems with noisy measurements. Based on a novel density representation - sliced Gaussian mixture density - the decomposition into a (conditionally) linear and nonlinear estimation problem is derived. The systematic approximation procedure minimizing a certain distance measure allows the derivation of (close to) optimal and deterministic estimation results. This leads to high-quality representations of the measurement-conditioned density of the states and, hence, to an overall more efficient estimation process. The performance of the proposed estimator is compared to state-of-the-art estimators, like the well-known marginalized particle filter.

关键词： Bandpass filters

来源：评论

学校读者我要写书评

暂无评论

Missed detection problems in the cardinalized probability hypothesis density filter

Missed detection problems in the cardinalized probability hy...

引用

11th International Conference on Information fusion, fusion 2008

作者： Ulmke, M. Fränken, D. Schmidt, M. Dept. Sensor Data and Information Fusion FGAN - FKIE D-53343 Wachtberg Germany Data Fusion Algorithms and Software EADS Deutschland GmbH D-89077 Ulm Germany

ISBN: (纸本)9783000248832

The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for estimating multiple target states with varying target number in clutter. In the present work, it is shown that a missed detection in one part of the field of view has a significant effect on the probability hypothesis density (PHD) arbitrarily far apart from the missed detection. In the case of zero false alarm rate, this effect is particularly pronounced and can be calculated by solving the CPHD filter equations analytically. While the CPHD filter update of the total cardinality distribution is exact, the local target number estimate close to the missed detection is artificially strongly reduced. A first ad-hoc approach towards a "locally" cardinalized PHD filter for reducing this deficiency is presented and discussed.

关键词： Bandpass filters

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共2页 << < 1 2 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：