Deterministic Sampling for Nonlinear Dynamic State Estimation
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[1] Gerhard Kurz,et al. Recursive Bingham filter for directional estimation involving 180 degree symmetry , 2014 .
[2] A. Wood,et al. Saddlepoint approximations for the Bingham and Fisher–Bingham normalising constants , 2005 .
[3] Gerhard Kurz,et al. Deterministic approximation of circular densities with symmetric Dirac mixtures based on two circular moments , 2014, 17th International Conference on Information Fusion (FUSION).
[4] Akimichi Takemura,et al. Holonomic Gradient Descent and its Application to Fisher-Bingham Integral , 2010, ArXiv.
[5] Ronald F. Boisvert,et al. NIST Handbook of Mathematical Functions , 2010 .
[6] Rudolph van der Merwe,et al. Sigma-point kalman filters for probabilistic inference in dynamic state-space models , 2004 .
[7] Kazufumi Ito,et al. Gaussian filters for nonlinear filtering problems , 2000, IEEE Trans. Autom. Control..
[8] Jeff Gill,et al. Circular Data in Political Science and How to Handle It , 2010, Political Analysis.
[9] E. Batschelet. Circular statistics in biology , 1981 .
[10] Young Soo Suh. Orientation Estimation Using a Quaternion-Based Indirect Kalman Filter With Adaptive Estimation of External Acceleration , 2010, IEEE Transactions on Instrumentation and Measurement.
[11] Wendelin Feiten,et al. MPG - Fast Forward Reasoning on 6 DOF Pose Uncertainty , 2012, ROBOTIK.
[12] Federico Thomas,et al. Approaching Dual Quaternions From Matrix Algebra , 2014, IEEE Transactions on Robotics.
[13] A. Rényi. On Measures of Entropy and Information , 1961 .
[14] Uwe D. Hanebeck,et al. Localized Cumulative Distributions and a multivariate generalization of the Cramér-von Mises distance , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.
[15] Simon J. Julier,et al. The spherical simplex unscented transformation , 2003, Proceedings of the 2003 American Control Conference, 2003..
[16] S. F. Schmidt. APPLICATION OF STATISTICAL FILTER THEORY TO THE OPTIMAL ESTIMATION OF POSITION AND VELOCITY ON BOARD A CIRCUMLUNAR VEHICLE , 2022 .
[17] Uwe D. Hanebeck,et al. Advances in hypothesizing distributed Kalman filtering , 2013, Proceedings of the 16th International Conference on Information Fusion.
[18] Nimeshika Udayangani,et al. IEEE Signal Processing Cup 2016 Team-MGLS , 2016 .
[19] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[20] Mongi A. Abidi,et al. Pose and motion estimation from vision using dual quaternion-based extended kalman filtering , 1997 .
[21] Jun S. Liu,et al. Sequential Monte Carlo methods for dynamic systems , 1997 .
[22] Uwe D. Hanebeck,et al. S2KF: The Smart Sampling Kalman Filter , 2013, Proceedings of the 16th International Conference on Information Fusion.
[23] A. Willsky,et al. Estimation for rotational processes with one degree of freedom--Part I: Introduction and continuous- , 1975 .
[24] H. Sorenson,et al. Recursive bayesian estimation using gaussian sums , 1971 .
[25] Richard A. Volz,et al. Estimating 3-D location parameters using dual number quaternions , 1991, CVGIP Image Underst..
[26] Gerhard Kurz,et al. Bivariate angular estimation under consideration of dependencies using directional statistics , 2014, 53rd IEEE Conference on Decision and Control.
[27] Robert J. Elliott,et al. Measure Theory and Filtering: Preface , 2004 .
[28] Jared Glover,et al. The quaternion Bingham Distribution, 3D object detection, and dynamic manipulation , 2014 .
[29] Ondrej Straka,et al. Stochastic Integration Filter , 2013, IEEE Transactions on Automatic Control.
[30] Nicholas Roy,et al. Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution , 2012 .
[31] Alison L Gibbs,et al. On Choosing and Bounding Probability Metrics , 2002, math/0209021.
[32] Xiangyu Wang,et al. Parallelizing MCMC via Weierstrass Sampler , 2013, 1312.4605.
[33] Calyampudi R. Rao,et al. Characterization Problems in Mathematical Statistics , 1976 .
[34] Robert B. McGhee,et al. An improved quaternion-based Kalman filter for real-time tracking of rigid body orientation , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).
[35] S. R. Jammalamadaka,et al. Topics in Circular Statistics , 2001 .
[36] Gerhard Kurz. Directional Estimation for Robotic Beating Heart Surgery , 2015 .
[37] T. Başar,et al. A New Approach to Linear Filtering and Prediction Problems , 2001 .
[38] Serge Reboul,et al. A recursive fusion filter for angular data , 2009, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO).
[39] R. A. Leibler,et al. On Information and Sufficiency , 1951 .
[40] R. Booton. Nonlinear control systems with random inputs , 1954, IRE Transactions on Circuit Theory.
[41] Gerhard Kurz,et al. Recursive nonlinear filtering for angular data based on circular distributions , 2013, 2013 American Control Conference.
[42] S Julier,et al. Comment on "A new method for the nonlinear transformation of means and covariances in filters and estimators" - Reply , 2002 .
[43] R. Plackett. Some theorems in least squares. , 1950, Biometrika.
[44] Marco F. Huber,et al. Gaussian Filter based on Deterministic Sampling for High Quality Nonlinear Estimation , 2008 .
[45] J. A. Carta,et al. Statistical modelling of directional wind speeds using mixtures of von Mises distributions: Case study , 2008 .
[46] N. A. Carlson. Federated square root filter for decentralized parallel processors , 1990 .
[47] Gerhard Kurz,et al. Unscented Orientation Estimation Based on the Bingham Distribution , 2013, IEEE Transactions on Automatic Control.
[48] Uwe D. Hanebeck,et al. Dirac mixture approximation of multivariate Gaussian densities , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.
[49] K. Mardia. Characterizations of Directional Distributions , 1975 .
[50] Ken Shoemake,et al. Animating rotation with quaternion curves , 1985, SIGGRAPH.
[51] Simo Särkkä,et al. Bayesian Filtering and Smoothing , 2013, Institute of Mathematical Statistics textbooks.
[52] Joris De Schutter,et al. Nonlinear Kalman Filtering for Force-Controlled Robot Tasks , 2010, Springer Tracts in Advanced Robotics.
[53] S. R. Jammalamadaka,et al. Directional Statistics, I , 2011 .
[54] Andrew T. A. Wood,et al. On the derivatives of the normalising constant of the Bingham distribution , 2007 .
[55] Dan Simon,et al. Optimal State Estimation: Kalman, H∞, and Nonlinear Approaches , 2006 .
[56] Adrian N. Bishop. Information fusion via the wasserstein barycenter in the space of probability measures: Direct fusion of empirical measures and Gaussian fusion with unknown correlation , 2014, 17th International Conference on Information Fusion (FUSION).
[57] Norbert Wiener,et al. Extrapolation, Interpolation, and Smoothing of Stationary Time Series , 1964 .
[58] Angelo M. Sabatini,et al. Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing , 2006, IEEE Transactions on Biomedical Engineering.
[59] Walter Schmidt. Statistische Methoden beim Gefügestudium krystalliner Schiefer , 1917 .
[60] Clifford,et al. Preliminary Sketch of Biquaternions , 1871 .
[61] Gerhard Kurz,et al. Efficient Bingham filtering based on saddlepoint approximations , 2014, 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI).
[62] Jirí Zára,et al. Skinning with dual quaternions , 2007, SI3D.
[63] Sandra Hirche,et al. Gaussian process kernels for rotations and 6D rigid body motions , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[64] Uwe D. Hanebeck,et al. Stochastic nonlinear model predictive control based on progressive density simplification , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[65] T. Brehard,et al. Hierarchical particle filter for bearings-only tracking , 2007, IEEE Transactions on Aerospace and Electronic Systems.
[66] Jonathan Corcoran,et al. Using circular statistics to analyse time patterns in crime incidence , 2006, Comput. Environ. Urban Syst..
[67] Gerhard Kurz,et al. Efficient evaluation of the probability density function of a wrapped normal distribution , 2014, 2014 Sensor Data Fusion: Trends, Solutions, Applications (SDF).
[68] George Casella,et al. Explaining the Saddlepoint Approximation , 1999 .
[69] Louis-Paul Rivest,et al. Some Statistical Methods for Bivariate Circular Data , 1982 .
[70] Kiseon Kim,et al. Why Gaussianity? , 2008, IEEE Signal Processing Magazine.
[71] Ondrej Straka,et al. Randomized unscented Kalman filter in target tracking , 2012, 2012 15th International Conference on Information Fusion.
[72] G. Kallianpur. Stochastic Filtering Theory , 1980 .
[73] Hugh F. Durrant-Whyte,et al. A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..
[74] R. E. Kalman,et al. New Results in Linear Filtering and Prediction Theory , 1961 .
[75] Gerhard Kurz,et al. Recursive estimation of orientation based on the Bingham distribution , 2013, Proceedings of the 16th International Conference on Information Fusion.
[76] Andrew T. A. Wood,et al. Saddlepoint approximations for the normalizing constant of Fisher--Bingham distributions on products of spheres and Stiefel manifolds , 2013 .
[77] Alan Edelman,et al. The efficient evaluation of the hypergeometric function of a matrix argument , 2006, Math. Comput..
[78] Uwe D. Hanebeck,et al. Efficient deterministic dirac mixture approximation of Gaussian distributions , 2013, 2013 American Control Conference.
[79] K. Mardia. Directional statistics in geosciences , 1981 .
[80] Jack B. Kuipers,et al. Quaternions and Rotation Sequences: A Primer with Applications to Orbits, Aerospace and Virtual Reality , 2002 .
[81] Christopher Bingham. An Antipodally Symmetric Distribution on the Sphere , 1974 .
[82] Joseph J. LaViola,et al. On Kalman Filtering With Nonlinear Equality Constraints , 2007, IEEE Transactions on Signal Processing.
[83] C. Herz. BESSEL FUNCTIONS OF MATRIX ARGUMENT , 1955 .
[84] Wendelin Feiten,et al. 6D Pose Uncertainty in Robotic Perception , 2009 .
[85] Simon J. Godsill,et al. On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..
[86] Gerhard Kurz,et al. Bearings-only sensor scheduling using circular statistics , 2013, Proceedings of the 16th International Conference on Information Fusion.
[87] Arthur Gelb,et al. Applied Optimal Estimation , 1974 .
[88] Uwe D. Hanebeck. Optimal Reduction of Multivariate Dirac Mixture Densities , 2015, Autom..
[89] H.F. Durrant-Whyte,et al. A new approach for filtering nonlinear systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.
[90] Robert B. McGhee,et al. An extended Kalman filter for quaternion-based orientation estimation using MARG sensors , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).
[91] Uwe D. Hanebeck,et al. A robust computational test for overlap of two arbitrary-dimensional ellipsoids in fault-detection of Kalman filters , 2012, 2012 15th International Conference on Information Fusion.
[92] Robert F. Stengel,et al. Optimal Control and Estimation , 1994 .
[93] Uwe D. Hanebeck,et al. A direct method for checking overlap of two hyperellipsoids , 2014, 2014 Sensor Data Fusion: Trends, Solutions, Applications (SDF).
[94] D. Crisan,et al. Fundamentals of Stochastic Filtering , 2008 .
[95] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[96] Anja Vogler,et al. An Introduction to Multivariate Statistical Analysis , 2004 .
[97] Aarnout Brombacher,et al. Probability... , 2009, Qual. Reliab. Eng. Int..
[98] Tamio Koyama,et al. Holonomic gradient descent for the Fisher–Bingham distribution on the $$d$$d-dimensional sphere , 2012, Comput. Stat..
[99] Gerhard Kurz,et al. The partially wrapped normal distribution for SE(2) estimation , 2014, 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI).
[100] Uwe D. Hanebeck,et al. Deterministic Dirac mixture approximation of Gaussian mixtures , 2014, 17th International Conference on Information Fusion (FUSION).
[101] Gerhard Kurz,et al. A new probability distribution for simultaneous representation of uncertain position and orientation , 2014, 17th International Conference on Information Fusion (FUSION).
[102] D. B. Duncan,et al. Linear Dynamic Recursive Estimation from the Viewpoint of Regression Analysis , 1972 .
[103] S. Rachev,et al. Probability metrics and recursive algorithms , 1995, Advances in Applied Probability.
[104] Jr. J.J. LaViola,et al. A comparison of unscented and extended Kalman filtering for estimating quaternion motion , 2003, Proceedings of the 2003 American Control Conference, 2003..
[105] Uwe D. Hanebeck,et al. PGF 42: Progressive Gaussian filtering with a twist , 2013, Proceedings of the 16th International Conference on Information Fusion.
[106] W. J. Cody,et al. Chebyshev approximations for the exponential integral () , 1969 .
[107] N. Mattern,et al. An evaluation of nonlinear filtering algorithms for integrating GNSS and inertial measurements , 2008, 2008 IEEE/ION Position, Location and Navigation Symposium.
[108] Stelios C. A. Thomopoulos,et al. Distributed Fusion Architectures and Algorithms for Target Tracking , 1997, Proc. IEEE.
[109] Jirí Zára,et al. Geometric skinning with approximate dual quaternion blending , 2008, TOGS.
[110] H. Sorenson,et al. Nonlinear Bayesian estimation using Gaussian sum approximations , 1972 .
[111] Uwe D. Hanebeck,et al. Superficial Gaussian Mixture Reduction , 2011, GI-Jahrestagung.
[112] José A. Castellanos,et al. Unscented SLAM for large-scale outdoor environments , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[113] Eduardo Mario Nebot,et al. Consistency of the EKF-SLAM Algorithm , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[114] Nicholas Roy,et al. Extrinsic Calibration from Per-Sensor Egomotion , 2013 .
[115] Hiroyuki Ochiai,et al. Anti-commutative Dual Complex Numbers and 2D Rigid Transformation , 2016, ArXiv.
[116] Ron Meir,et al. Density Estimation Through Convex Combinations of Densities: Approximation and Estimation Bounds , 1997, Neural Networks.
[117] Uwe D. Hanebeck,et al. The Hypothesizing Distributed Kalman Filter , 2012, 2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).
[118] Gerhard Kurz,et al. Nonlinear measurement update for estimation of angular systems based on circular distributions , 2014, 2014 American Control Conference.
[119] H. Daniels. Saddlepoint Approximations in Statistics , 1954 .
[120] R. Johnson,et al. Measures and models for angular correlation and angular-linear correlation. [correlation of random variables] , 1976 .
[121] A. Jazwinski. Stochastic Processes and Filtering Theory , 1970 .
[122] Stergios I. Roumeliotis,et al. A Kalman Filter-Based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation , 2008, IEEE Transactions on Robotics.
[123] Leslie Pack Kaelbling,et al. Tracking 3-D Rotations with the Quaternion Bingham Filter , 2013 .
[124] Alessandro Chiuso,et al. Visual tracking of points as estimation on the unit sphere , 1997, Block Island Workshop on Vision and Control.
[125] Sandra Hirche,et al. Rigid motion estimation using mixtures of projected Gaussians , 2013, Proceedings of the 16th International Conference on Information Fusion.
[126] R. Muirhead. Aspects of Multivariate Statistical Theory , 1982, Wiley Series in Probability and Statistics.
[127] C. Brezinski. Interpolation and Extrapolation , 2001 .
[128] Jeffrey K. Uhlmann,et al. Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.
[129] Uwe D. Hanebeck,et al. Regularized non-parametric multivariate density and conditional density estimation , 2010, 2010 IEEE Conference on Multisensor Fusion and Integration.