publications by year

2021

  1. M. Ristic, B. Noack, and U. D. Hanebeck, Cryptographically Privileged State EstimationWith Gaussian Keystreams (accepted), IEEE Control Systems Letters, May 2021.
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  2. C. Funk, B. Noack, and U. D. Hanebeck, Conservative Quantization of Covariance Matrices with Applications to Decentralized Information Fusion, Sensors, vol. 21, no. 9, Apr. 2021.
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  3. M. Ristic, B. Noack, and U. D. Hanebeck, Secure Fast Covariance Intersection Using Partially Homomorphic and Order Revealing Encryption Schemes, IEEE Control Systems Letters, vol. 5, no. 1, pp. 217–222, Jan. 2021.
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2020

  1. C. Funk, B. Noack, and U. D. Hanebeck, Conservative Quantization of Fast Covariance Intersection, in Proceedings of the 2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2020), Virtual, Sep. 2020.
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  2. S. Radtke, B. Noack, and U. D. Hanebeck, Fully Decentralized Estimation Using Square-Root Decompositions, in Proceedings of the 23rd International Conference on Information Fusion (Fusion 2020), Virtual, Jul. 2020.
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  3. S. Radtke, B. Noack, and U. D. Hanebeck, Reconstruction of Cross-Correlations between Heterogeneous Trackers Using Deterministic Samples, in Proceedings of the 21st IFAC World Congress (IFAC 2020), Berlin, Germany, Jul. 2020.
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  4. B. Noack, C. Funk, S. Radtke, and U. D. Hanebeck, State Estimation with Event-Based Inputs Using Stochastic Triggers, in Proceedings of the 21st IFAC World Congress (IFAC 2020), Berlin, Germany, Jul. 2020.
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  5. K. Li, J. Cox, B. Noack, and U. D. Hanebeck, Improved Pose Graph Optimization for Planar Motions Using Riemannian Geometry on the Manifold of Dual Quaternions, in Proceedings of the 21st IFAC World Congress (IFAC 2020), Berlin, Germany, Jul. 2020.
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  6. F. Pfaff, C. Pieper, G. Maier, B. Noack, R. Gruna, H. Kruggel-Emden, U. D. Hanebeck, S. Wirtz, V. Scherer, T. Längle, and J. Beyerer, Predictive Tracking with Improved Motion Models for Optical Belt Sorting, at – Automatisierungstechnik, vol. 4, no. 68, Apr. 2020.
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  7. G. Maier, F. Pfaff, A. Bittner, R. Gruna, B. Noack, H. Kruggel-Emden, U. D. Hanebeck, T. Längle, and J. Beyerer, Characterizing Material Flow in Sensor-Based Sorting Systems Using an Instrumented Particle, at – Automatisierungstechnik, vol. 4, no. 68, Apr. 2020.
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  8. G. Maier, F. Pfaff, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, and J. Beyerer, Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking, Transactions on Industrial Electronics, Feb. 2020.
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2019

  1. S. Radtke, B. Noack, and U. D. Hanebeck, Consistent Fusion in Networks Using Square-root Decompositions of Correlations, in Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), Ottawa, Canada, Jul. 2019.
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  2. B. Noack, U. Orguner, and U. D. Hanebeck, Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection, in Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), Ottawa, Canada, Jul. 2019.
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  3. T. Kronauer, F. Pfaff, B. Noack, W. Tian, G. Maier, and U. D. Hanebeck, Feature-Aided Multitarget Tracking for Optical Belt Sorters, in Proceedings of the 22nd International Conference on Information Fusion (Fusion 2019), Ottawa, Canada, Jul. 2019.
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  4. E. J. Schmitt, B. Noack, W. Krippner, and U. D. Hanebeck, Gaussianity-Preserving Event-Based State Estimation with an FIR-Based Stochastic Trigger, IEEE Control Systems Letters, vol. 3, no. 3, pp. 769–774, Jul. 2019.
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  5. S. Radtke, B. Noack, and U. D. Hanebeck, Distributed Estimation with Partially Overlapping States based on Deterministic Sample-based Fusion, in Proceedings of the 2019 European Control Conference (ECC 2019), Naples, Italy, Jun. 2019.
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  6. K. Li, D. Frisch, B. Noack, and U. Hanebeck, Geometry-Driven Deterministic Sampling for Nonlinear Bingham Filtering, in Proceedings of the 2019 European Control Conference (ECC 2019), Naples, Italy, Jun. 2019.
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  7. S. Özgen, S. Kohn, B. Noack, and U. D. Hanebeck, State Estimation with Model-Mismatch-Based Secrecy against Eavesdroppers, in Proceedings of the 2019 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2019), Taipei, Taiwan, May 2019.
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  8. S. Radtke, K. Li, B. Noack, and U. D. Hanebeck, Comparative Study of Track-to-Track Fusion Methods for Cooperative Tracking with Bearings-only Measurements, in Proceedings of the 2019 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2019), Taipei, Taiwan, May 2019.
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2018

  1. C. Pieper, F. Pfaff, G. Maier, H. Kruggel-Emden, S. Wirtz, B. Noack, R. Gruna, V. Scherer, U. D. Hanebeck, T. Längle, and J. Beyerer, Numerical Modelling of an Optical Belt Sorter Using a DEM–CFD Approach Coupled with Particle Tracking and Comparison with Experiments, Powder Technology, vol. 370, pp. 181–193, Dec. 2018.
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  2. K. Li, D. Frisch, S. Radtke, B. Noack, and U. D. Hanebeck, Wavefront Orientation Estimation Based on Progressive Bingham Filtering, in Proceedings of the IEEE ISIF Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF 2018), Oct. 2018.
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  3. S. Özgen, U. D. Hanebeck, B. Noack, M. Huber, F. Rosenthal, and J. Mayer, Retrodiction of Data Association Probabilities via Convex Optimization, in Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), Cambridge, United Kingdom, Jul. 2018.
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  4. S. Radtke, B. Noack, U. D. Hanebeck, and O. Straka, Reconstruction of Cross-Correlations with Constant Number of Deterministic Samples, in Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), Cambridge, United Kingdom, Jul. 2018.
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  5. M. Aristov, B. Noack, U. D. Hanebeck, and J. Müller-Quade, Encrypted Multisensor Information Filtering, in Proceedings of the 21st International Conference on Information Fusion (Fusion 2018), Cambridge, United Kingdom, Jul. 2018.
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  6. F. Rosenthal, B. Noack, and U. D. Hanebeck, State Estimation in Networked Control Systems with Delayed and Lossy Acknowledgments, in Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System, S. Lee, H. Ko, and S. Oh, Eds. Cham: Springer International Publishing, Jul. 2018, pp. 22–38.
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  7. J. Duník, O. Straka, B. Noack, J. Steinbring, and U. D. Hanebeck, On Directional Splitting of Gaussian Density in Nonlinear Random Variable Transformation, IET Signal Processing, Jul. 2018.
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  8. F. Rosenthal, B. Noack, and U. D. Hanebeck, Scheduling of Measurement Transmission in Networked Control Systems Subject to Communication Constraints, in Proceedings of the 2018 American Control Conference (ACC 2018), Milwaukee, Wisconsin, USA, Jun. 2018.
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  9. K. Dormann, B. Noack, and U. D. Hanebeck, Optimally Distributed Kalman Filtering with Data-Driven Communication, Sensors, vol. 18, no. 4, Apr. 2018.
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  10. G. Maier, F. Pfaff, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, S. Wirtz, V. Scherer, and J. Beyerer, Application of Area-Scan Sensors in Sensor-Based Sorting, in Proceedings of the Eighth Conference on Sensor-Based Sorting & Control 2018 (SBSC 2018), Aachen, Germany, Mar. 2018.

2017

  1. F. Rosenthal, B. Noack, and U. D. Hanebeck, State Estimation in Networked Control Systems With Delayed And Lossy Acknowledgments, in Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Daegu, Korea, Nov. 2017.
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  2. F. Pfaff, G. Kurz, C. Pieper, G. Maier, B. Noack, H. Kruggel-Emden, R. Gruna, U. D. Hanebeck, S. Wirtz, V. Scherer, T. Längle, and J. Beyerer, Improving Multitarget Tracking Using Orientation Estimates for Sorting Bulk Materials, in Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Daegu, Korea, Nov. 2017.
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  3. K. Dormann, B. Noack, and U. D. Hanebeck, Distributed Kalman Filtering With Reduced Transmission Rate, in Proceedings of the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017), Daegu, Korea, Nov. 2017.
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  4. G. Maier, F. Pfaff, M. Wagner, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, S. Wirtz, V. Scherer, and J. Beyerer, Real-Time Multitarget Tracking for Sensor-Based Sorting, Journal of Real-Time Image Processing, Nov. 2017.
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  5. G. Maier, F. Pfaff, F. Becker, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, S. Wirtz, V. Scherer, and J. Beyerer, Motion-Based Material Characterization in Sensor-Based Sorting, tm - Technisches Messen, De Gruyter, Oct. 2017.
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  6. C. Pieper, G. Maier, F. Pfaff, H. Kruggel-Emden, R. Gruna, B. Noack, S. Wirtz, V. Scherer, T. Längle, U. D. Hanebeck, and J. Beyerer, Numerical Modelling of the Separation of Complex Shaped Particles in an Optical Belt Sorter Using a DEM–CFD Approach and Comparison with Experiments, in V International Conference on Particle-based Methods. Fundamentals and Applications (PARTICLES 2017), Hannover, Germany, Sep. 2017.
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  7. F. Pfaff, B. Noack, U. D. Hanebeck, F. Govaers, and W. Koch, Information Form Distributed Kalman Filtering (IDKF) with Explicit Inputs, in Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), Xi’an, China, Jul. 2017.
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  8. F. Pfaff, B. Noack, and U. D. Hanebeck, Optimal Distributed Combined Stochastic and Set-Membership State Estimation, in Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), Xi’an, China, Jul. 2017.
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  9. B. Noack, J. Sijs, and U. D. Hanebeck, Inverse Covariance Intersection: New Insights and Properties, in Proceedings of the 20th International Conference on Information Fusion (Fusion 2017), Xi’an, China, Jul. 2017.
  10. J. Sijs and B. Noack, Event-Based Estimation in a Feedback Loop Anticipating on Imperfect Communication, in Proceedings of the 20th IFAC World Congress (IFAC 2017), Toulouse, France, Jul. 2017.
  11. F. Pfaff, G. Maier, M. Aristov, B. Noack, R. Gruna, U. D. Hanebeck, T. Längle, J. Beyerer, C. Pieper, H. Kruggel-Emden, S. Wirtz, and V. Scherer, Real-Time Motion Prediction Using the Chromatic Offset of Line Scan Cameras, at - Automatisierungstechnik, De Gruyter, Jun. 2017.
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  12. B. Noack, J. Sijs, M. Reinhardt, and U. D. Hanebeck, Decentralized Data Fusion with Inverse Covariance Intersection, Automatica, vol. 79, pp. 35–41, May 2017.
  13. G. Maier, F. Pfaff, F. Becker, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, S. Wirtz, V. Scherer, and J. Beyerer, Improving Material Characterization in Sensor-Based Sorting by Utilizing Motion Information, in Proceedings of the 3rd Conference on Optical Characterization of Materials (OCM 2017), Karlsruhe, Germany, Mar. 2017.
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2016

  1. F. Pfaff, C. Pieper, G. Maier, B. Noack, H. Kruggel-Emden, R. Gruna, U. D. Hanebeck, S. Wirtz, V. Scherer, T. Längle, and J. Beyerer, Simulation-based Evaluation of Predictive Tracking for Sorting Bulk Materials, in Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), Baden-Baden, Germany, Sep. 2016.
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  2. B. Noack, J. Sijs, and U. D. Hanebeck, Algebraic Analysis of Data Fusion with Ellipsoidal Intersection, in Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), Baden-Baden, Germany, Sep. 2016.
  3. G. Maier, F. Pfaff, C. Pieper, R. Gruna, B. Noack, H. Kruggel-Emden, T. Längle, U. D. Hanebeck, S. Wirtz, V. Scherer, and J. Beyerer, Fast Multitarget Tracking via Strategy Switching for Sensor-Based Sorting, in Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), Baden-Baden, Germany, Sep. 2016.
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  4. F. Faion, A. Zea, B. Noack, J. Steinbring, and U. D. Hanebeck, Camera- and IMU-based Pose Tracking for Augmented Reality, in Proceedings of the 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2016), Baden-Baden, Germany, Sep. 2016.
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  5. C. Pieper, H. Kruggel-Emden, S. Wirtz, V. Scherer, F. Pfaff, B. Noack, U. D. Hanebeck, G. Maier, R. Gruna, T. Längle, and J. Beyerer, Numerical Investigation of Optical Sorting using the Discrete Element Method, in Proceedings of the 7th International Conference on Discrete Element Methods (DEM7), Dalian, China, Aug. 2016.
  6. J. Steinbring, B. Noack, M. Reinhardt, and U. D. Hanebeck, Optimal Sample-Based Fusion for Distributed State Estimation, in Proceedings of the 19th International Conference on Information Fusion (Fusion 2016), Heidelberg, Germany, Jul. 2016.
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  7. B. Noack, F. Pfaff, M. Baum, and U. D. Hanebeck, State Estimation Considering Negative Information with Switching Kalman and Ellipsoidal Filtering, in Proceedings of the 19th International Conference on Information Fusion (Fusion 2016), Heidelberg, Germany, Jul. 2016.
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  8. C. Pieper, G. Maier, F. Pfaff, H. Kruggel-Emden, S. Wirtz, R. Gruna, B. Noack, V. Scherer, T. Längle, J. Beyerer, and U. D. Hanebeck, Numerical Modeling of an Automated Optical Belt Sorter using the Discrete Element Method, Powder Technology, Jul. 2016.
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  9. B. Noack and U. D. Hanebeck, State Estimation Using Virtual Measurement Information, in Proceedings of the 18. GMA/ITG Fachtagung Sensoren und Messsysteme 2016, May 2016.
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  10. F. Pfaff, C. Pieper, G. Maier, B. Noack, H. Kruggel-Emden, R. Gruna, U. D. Hanebeck, S. Wirtz, V. Scherer, T. Längle, and J. Beyerer, Improving Optical Sorting of Bulk Materials Using Sophisticated Motion Models, tm - Technisches Messen, De Gruyter, vol. 83, no. 2, pp. 77–84, Feb. 2016.
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2015

  1. J. Sijs, B. Noack, M. Lazar, and U. D. Hanebeck, Time-Periodic State Estimation with Event-Based Measurement Updates, in Event-Based Control and Signal Processing, M. Miskowicz, Ed. CRC Press, Nov. 2015, pp. 261–279.
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  2. B. Noack, M. Baum, and U. D. Hanebeck, State Estimation for Ellipsoidally Constrained Dynamic Systems with Set-membership Pseudo Measurements, in Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, Sep. 2015.
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  3. M. Baum, B. Noack, and U. D. Hanebeck, Kalman Filter-based SLAM with Unknown Data Association using Symmetric Measurement Equations, in Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2015), San Diego, California, USA, Sep. 2015.
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  4. F. Pfaff, M. Baum, B. Noack, U. D. Hanebeck, R. Gruna, T. Längle, and J. Beyerer, TrackSort: Predictive Tracking for Sorting Uncooperative Bulk Materials, in Proceedings of the 2015 IEEE International Conference on Multisensor Fusion and Information Integration (MFI 2015), San Diego, California, USA, Sep. 2015.
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  5. M. Reinhardt, B. Noack, P. O. Arambel, and U. D. Hanebeck, Minimum Covariance Bounds for the Fusion under Unknown Correlations, IEEE Signal Processing Letters, vol. 22, no. 9, pp. 1210–1214, Sep. 2015.
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  6. B. Noack, J. Sijs, M. Reinhardt, and U. D. Hanebeck, Treatment of Dependent Information in Multisensor Kalman Filtering and Data Fusion, in Multisensor Data Fusion: From Algorithms and Architectural Design to Applications, H. Fourati, Ed. CRC Press, Aug. 2015, pp. 169–192.
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  7. B. Noack, S. J. Julier, and U. D. Hanebeck, Treatment of Biased and Dependent Sensor Data in Graph-based SLAM, in Proceedings of the 18th International Conference on Information Fusion (Fusion 2015), Washington D. C., USA, Jul. 2015.
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2014

  1. B. Noack, J. Sijs, and U. D. Hanebeck, Fusion Strategies for Unequal State Vectors in Distributed Kalman Filtering, in Proceedings of the 19th IFAC World Congress (IFAC 2014), Cape Town, South Africa, Aug. 2014.
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  2. J. Sijs, L. Kester, and B. Noack, A Study on Event Triggering Criteria for Estimation, in Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), Salamanca, Spain, Jul. 2014.
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  3. M. Reinhardt, B. Noack, S. Kulkarni, and U. D. Hanebeck, Distributed Kalman Filtering in the Presence of Packet Delays and Losses, in Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), Salamanca, Spain, Jul. 2014.
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  4. B. Noack, M. Reinhardt, and U. D. Hanebeck, On Nonlinear Track-to-track Fusion with Gaussian Mixtures, in Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), Salamanca, Spain, Jul. 2014.
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  5. J. Ajgl, M. Šimandl, M. Reinhardt, B. Noack, and U. D. Hanebeck, Covariance Intersection in State Estimation of Dynamical Systems, in Proceedings of the 17th International Conference on Information Fusion (Fusion 2014), Salamanca, Spain, Jul. 2014.
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  6. M. Reinhardt, B. Noack, and U. D. Hanebeck, Reconstruction of Joint Covariance Matrices in Networked Linear Systems, in Proceedings of the 48th Annual Conference on Information Sciences and Systems (CISS 2014), Princeton, New Jersey, USA, Mar. 2014.
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2013

  1. J. Sijs, U. D. Hanebeck, and B. Noack, An Empirical Method to Fuse Partially Overlapping State Vectors for Distributed State Estimation, in Proceedings of the 2013 European Control Conference (ECC 2013), Zürich, Switzerland, Jul. 2013.
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  2. J. Sijs, B. Noack, and U. D. Hanebeck, Event-Based State Estimation with Negative Information, in Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), Istanbul, Turkey, Jul. 2013.
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  3. M. Reinhardt, B. Noack, and U. D. Hanebeck, Advances in Hypothesizing Distributed Kalman Filtering, in Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), Istanbul, Turkey, Jul. 2013.
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  4. F. Pfaff, B. Noack, and U. D. Hanebeck, Data Validation in the Presence of Stochastic and Set-membership Uncertainties, in Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), Istanbul, Turkey, Jul. 2013.
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  5. B. Noack, S. J. Julier, M. Reinhardt, and U. D. Hanebeck, Nonlinear Federated Filtering, in Proceedings of the 16th International Conference on Information Fusion (Fusion 2013), Istanbul, Turkey, Jul. 2013.
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  6. B. Noack, State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties, Dissertation, Karlsruhe Institute of Technology (KIT), Karlsruhe Series on Intelligent Sensor-Actuator-Systems 14, Jan. 2013.
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2012

  1. M. Reinhardt, B. Noack, and U. D. Hanebeck, Decentralized Control Based on Globally Optimal Estimation, in Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), Maui, Hawaii, USA, Dec. 2012.
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  2. B. Noack, F. Pfaff, and U. D. Hanebeck, Optimal Kalman Gains for Combined Stochastic and Set-Membership State Estimation, in Proceedings of the 51st IEEE Conference on Decision and Control (CDC 2012), Maui, Hawaii, USA, Dec. 2012.
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  3. M. Reinhardt, B. Noack, and U. D. Hanebeck, The Hypothesizing Distributed Kalman Filter, in Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2012), Hamburg, Germany, Sep. 2012.
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  4. M. Reinhardt, B. Noack, and U. D. Hanebeck, On Optimal Distributed Kalman Filtering in Non-ideal Situations, in Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), Singapore, Jul. 2012.
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  5. M. Reinhardt, B. Noack, and U. D. Hanebeck, Closed-form Optimization of Covariance Intersection for Low-dimensional Matrices, in Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), Singapore, Jul. 2012.
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  6. B. Noack, F. Pfaff, and U. D. Hanebeck, Combined Stochastic and Set-membership Information Filtering in Multisensor Systems, in Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), Singapore, Jul. 2012.
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  7. A. Benavoli and B. Noack, Pushing Kalman’s Idea to the Extremes, in Proceedings of the 15th International Conference on Information Fusion (Fusion 2012), Singapore, Jul. 2012.
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2011

  1. M. Baum, B. Noack, and U. D. Hanebeck, Mixture Random Hypersurface Models for Tracking Multiple Extended Objects, in Proceedings of the 50th IEEE Conference on Decision and Control (CDC 2011), Orlando, Florida, USA, Dec. 2011.
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  2. B. Noack, M. Baum, and U. D. Hanebeck, Automatic Exploitation of Independencies for Covariance Bounding in Fully Decentralized Estimation, in Proceedings of the 18th IFAC World Congress (IFAC 2011), Milan, Italy, Aug. 2011.
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  3. M. Reinhardt, B. Noack, M. Baum, and U. D. Hanebeck, Analysis of Set-theoretic and Stochastic Models for Fusion under Unknown Correlations, in Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, Jul. 2011.
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  4. B. Noack, M. Baum, and U. D. Hanebeck, Covariance Intersection in Nonlinear Estimation Based on Pseudo Gaussian Densities, in Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, Jul. 2011.
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  5. M. Baum, B. Noack, F. Beutler, D. Itte, and U. D. Hanebeck, Optimal Gaussian Filtering for Polynomial Systems Applied to Association-free Multi-Target Tracking, in Proceedings of the 14th International Conference on Information Fusion (Fusion 2011), Chicago, Illinois, USA, Jul. 2011.
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  6. B. Noack, D. Lyons, M. Nagel, and U. D. Hanebeck, Nonlinear Information Filtering for Distributed Multisensor Data Fusion, in Proceedings of the 2011 American Control Conference (ACC 2011), San Francisco, California, USA, Jun. 2011.
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  7. J. Schmid, F. Beutler, B. Noack, U. D. Hanebeck, and K. D. Müller-Glaser, An Experimental Evaluation of Position Estimation Methods for Person Localization in Wireless Sensor Networks, in Proceedings of the 8th European Conference on Wireless Sensor Networks (EWSN 2011), Bonn, Germany, Feb. 2011, vol. 6567, pp. 147–162.
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2010

  1. E. Bogatyrenko, B. Noack, and U. D. Hanebeck, Reliable Estimation of Heart Surface Motion under Stochastic and Unknown but Bounded Systematic Uncertainties, in Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan, Oct. 2010.
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  2. B. Noack, V. Klumpp, D. Lyons, and U. D. Hanebeck, Modellierung von Unsicherheiten und Zustandsschätzung mit Mengen von Wahrscheinlichkeitsdichten, tm - Technisches Messen, Oldenbourg Verlag, vol. 77, no. 10, pp. 544–550, Oct. 2010.
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  3. A. Hekler, D. Lyons, B. Noack, and U. D. Hanebeck, Nonlinear Model Predictive Control Considering Stochastic and Systematic Uncertainties with Sets of Densities, in Proceedings of the IEEE Multi-Conference on Systems and Control (MSC 2010), Yokohama, Japan, Sep. 2010.
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  4. B. Noack, V. Klumpp, N. Petkov, and U. D. Hanebeck, Bounding Linearization Errors with Sets of Densities in Approximate Kalman Filtering, in Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), Edinburgh, United Kingdom, Jul. 2010.
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  5. V. Klumpp, B. Noack, M. Baum, and U. D. Hanebeck, Combined Set-Theoretic and Stochastic Estimation: A Comparison of the SSI and the CS Filter, in Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), Edinburgh, United Kingdom, Jul. 2010.
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  6. M. Baum, B. Noack, and U. D. Hanebeck, Extended Object and Group Tracking with Elliptic Random Hypersurface Models, in Proceedings of the 13th International Conference on Information Fusion (Fusion 2010), Edinburgh, United Kingdom, Jul. 2010.
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  7. D. Lyons, B. Noack, and U. D. Hanebeck, A Log-Ratio Information Measure for Stochastic Sensor Management, in Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC 2010), Newport Beach, California, USA, Jun. 2010.
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  8. B. Noack, V. Klumpp, D. Lyons, and U. D. Hanebeck, Systematische Beschreibung von Unsicherheiten in der Informationsfusion mit Mengen von Wahrscheinlichkeitsdichten, in Verteilte Messsysteme, F. Puente León, K.-D. Sommer, and M. Heizmann, Eds. KIT Scientific Publishing, Mar. 2010, pp. 167–178.
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  9. D. Lyons, A. Hekler, B. Noack, and U. D. Hanebeck, Maße für Wahrscheinlichkeitsdichten in der informationstheoretischen Sensoreinsatzplanung, in Verteilte Messsysteme, F. Puente León, K.-D. Sommer, and M. Heizmann, Eds. KIT Scientific Publishing, Mar. 2010, pp. 121–132.
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2009

  1. B. Noack, V. Klumpp, and U. D. Hanebeck, State Estimation with Sets of Densities considering Stochastic and Systematic Errors, in Proceedings of the 12th International Conference on Information Fusion (Fusion 2009), Seattle, Washington, USA, Jul. 2009.
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2008

  1. B. Noack, V. Klumpp, D. Brunn, and U. D. Hanebeck, Nonlinear Bayesian Estimation with Convex Sets of Probability Densities, in Proceedings of the 11th International Conference on Information Fusion (Fusion 2008), Cologne, Germany, Jul. 2008, pp. 1–8.
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