Particle filtering for positioning and tracking applications
暂无分享,去创建一个
[1] Petros G. Voulgaris,et al. On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..
[2] A. Marrs,et al. Comparison of the KF and particle filter based out-of-sequence measurement filtering algorithms , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.
[3] Dan S. Necsulescu,et al. Extended Kalman filter-based sensor fusion for operational space control of a robot arm , 2002, IEEE Trans. Instrum. Meas..
[4] H. P. Blom. An efficient filter for abruptly changing systems , 1984, The 23rd IEEE Conference on Decision and Control.
[5] David V. Stallard,et al. Angle-only tracking filter in modified spherical coordinates , 1991 .
[6] Jun S. Liu,et al. Sequential Imputations and Bayesian Missing Data Problems , 1994 .
[7] J. A. Volpe. Vulnerability Assessment of the Transportation Infrastructure Relying on the Global Positioning Syst , 2001 .
[8] B. Wahlberg. On the Identification and Approximation of Linear Systems , 1987 .
[9] N. Gordon. A hybrid bootstrap filter for target tracking in clutter , 1995, IEEE Transactions on Aerospace and Electronic Systems.
[10] Fredrik Tjärnström,et al. Variance Expressions and Model Reduction in System Identification , 2002 .
[11] Robin J. Evans,et al. An information theoretic approach to observer path design for bearings-only tracking , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.
[12] Arnaud Doucet,et al. Particle filters for state estimation of jump Markov linear systems , 2001, IEEE Trans. Signal Process..
[13] Fredrik Gustafsson,et al. Particle filter for underwater terrain navigation , 2003, IEEE Workshop on Statistical Signal Processing, 2003.
[14] Petar M. Djuric,et al. An efficient fixed-point implementation of residual resampling scheme for high-speed particle filters , 2004, IEEE Signal Processing Letters.
[15] H. Sorenson,et al. Bayesian Parameter Estimation , 2006, Statistical Inference for Engineers and Data Scientists.
[16] M. Norrlof,et al. Iterative learning control of a flexible robot arm using accelerometers , 2004, Proceedings of the 2004 IEEE International Conference on Control Applications, 2004..
[17] Jun S. Liu,et al. Mixture Kalman filters , 2000 .
[18] Christian P. Robert,et al. Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.
[19] J. Löfberg. Minimax approaches to robust model predictive control , 2003 .
[20] Anders Høst-Madsen,et al. Effects of sampling and quantization on single-tone frequency estimation , 2000, IEEE Trans. Signal Process..
[21] Michael J. Grimble,et al. Iterative Learning Control for Deterministic Systems , 1992 .
[22] A. Doucet,et al. Particle filtering for partially observed Gaussian state space models , 2002 .
[23] H. V. Trees,et al. Utilization of Modified Polar Coordinates for BearingsOnly Tracking , 2007 .
[24] B. Widrow. A Study of Rough Amplitude Quantization by Means of Nyquist Sampling Theory , 1956 .
[25] Ragnar Wallin,et al. Optimization Algorithms for System Analysis and Identification , 2004 .
[26] Petar M. Djuric,et al. Gaussian particle filtering , 2003, IEEE Trans. Signal Process..
[27] K. Forsman. Constructive Commutative Algebra in Nonlinear Control Theory , 1991 .
[28] Donald Geman,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .
[29] L. B. Hostetler,et al. Nonlinear Kalman filtering techniques for terrain-aided navigation , 1983 .
[30] M. Jirstrand. Constructive Methods for Inequality Constraints in Control , 1998 .
[31] Y. Boers,et al. Interacting multiple model particle filter , 2003 .
[32] Carlos H. Muravchik,et al. Posterior Cramer-Rao bounds for discrete-time nonlinear filtering , 1998, IEEE Trans. Signal Process..
[33] H. Sorenson,et al. Nonlinear Bayesian estimation using Gaussian sum approximations , 1972 .
[34] Anders Stenman,et al. Model on Demand: Algorithms, Analysis and Applications , 1999 .
[35] M. Pitt,et al. Filtering via Simulation: Auxiliary Particle Filters , 1999 .
[36] A. Jazwinski. Stochastic Processes and Filtering Theory , 1970 .
[37] T. Bayes. An essay towards solving a problem in the doctrine of chances , 2003 .
[38] S.J. Dunham,et al. Alternatives to GPS , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).
[39] Måns Östring,et al. Modeling and Control of a Bending Backwards Industrial Robot , 2003 .
[40] Thiagalingam Kirubarajan,et al. Out-of-sequence measurement processing for tracking ground target using particle filters , 2002, Proceedings, IEEE Aerospace Conference.
[41] B. Bengtsson. On some Control Problems for Queues , 1982 .
[42] Håkan Hjalmarsson. Aspects on Incomplete Modeling in System Identification , 1993 .
[43] M. Norrlof,et al. Bayesian position estimation of an industrial robot using multiple sensors , 2004, Proceedings of the 2004 IEEE International Conference on Control Applications, 2004..
[44] P. Nordlund. Sequential Monte Carlo Filters and Integrated Navigation , 2002 .
[45] Ke Wang-Chen. Transformation and Symbolic Calculations in Filtering and Control , 1994 .
[46] Alan V. Oppenheim,et al. Digital Signal Processing , 1978, IEEE Transactions on Systems, Man, and Cybernetics.
[47] Hans Driessen,et al. An efficient particle filter for jump Markov nonlinear systems , 2004 .
[48] Patrick Pérez,et al. Sequential Monte Carlo methods for multiple target tracking and data fusion , 2002, IEEE Trans. Signal Process..
[49] Branko Ristic,et al. Comparison of the particle filter with range-parameterized and modified polar EKFs for angle-only tracking , 2000, SPIE Defense + Commercial Sensing.
[50] D. Mayne,et al. Monte Carlo techniques to estimate the conditional expectation in multi-stage non-linear filtering† , 1969 .
[51] Suguru Arimoto,et al. Bettering operation of Robots by learning , 1984, J. Field Robotics.
[52] Ola Härkegård,et al. Backstepping and control allocation with applications to flight control , 2003 .
[53] Yaakov Bar-Shalom,et al. Estimation and Tracking: Principles, Techniques, and Software , 1993 .
[54] Fredrik Gustafsson,et al. Particle filtering and Cramer-Rao lower bound for underwater navigation , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..
[55] J. E. Handschin. Monte Carlo techniques for prediction and filtering of non-linear stochastic processes , 1970 .
[56] E. L. Lehmann,et al. Theory of point estimation , 1950 .
[57] Brian D. Ripley,et al. Stochastic Simulation , 2005 .
[58] Mats Viberg,et al. Subspace fitting concepts in sensor array processing , 1990 .
[59] Jake K. Aggarwal,et al. Matching Aerial Images to 3-D Terrain Maps , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[60] Patric Jensfelt,et al. Approaches to Mobile Robot Localization in Indoor Environments , 2001 .
[61] J. Gunnarsson. Symbolic Methods and Tools for Discrete Event Dynamic Systems , 1997 .
[62] 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..
[63] J. Aggarwal,et al. Navigation using image sequence analysis and 3-D terrain matching , 1989, [1989] Proceedings. Workshop on Interpretation of 3D Scenes.
[64] W. K. Stewart,et al. Terrain-relative navigation for autonomous underwater vehicles , 1997 .
[65] F. Gustafsson,et al. Model-based statistical tracking and decision making for collision avoidance application , 2004, Proceedings of the 2004 American Control Conference.
[66] Inger Klein,et al. Automatic Synthesis of Sequential Control Schemes , 1993 .
[67] Svante Gunnarsson. Frequency Domain Aspects of Modeling and Control in Adaptive Systems , 1988 .
[68] Timothy J. Robinson,et al. Sequential Monte Carlo Methods in Practice , 2003 .
[69] N. Peach,et al. Bearings-only tracking using a set of range-parameterised extended Kalman filters , 1995 .
[70] Simon J. Godsill,et al. Monte Carlo smoothing with application to audio signal enhancement , 2002, IEEE Trans. Signal Process..
[71] J. Aldrich. R.A. Fisher and the making of maximum likelihood 1912-1922 , 1997 .
[72] R. Deriche,et al. A terrain referenced underwater positioning using sonar bathymetric profiles and multiscale analysis , 1996, OCEANS 96 MTS/IEEE Conference Proceedings. The Coastal Ocean - Prospects for the 21st Century.
[73] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[74] G. Kitagawa. Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .
[75] Rickard Karlsson,et al. Simulation Based Methods for Target Tracking , 2002 .
[76] H. Jonson. A Newton Method for Solving Non-Linear Optimal Control Problems with General Constraints , 1983 .
[77] Steven Kay,et al. Fundamentals Of Statistical Signal Processing , 2001 .
[78] Petar M. Djuric,et al. Gaussian sum particle filtering for dynamic state space models , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).
[79] Mille Millnert. Identification and Control of Systems Subject to Abrupt Changes , 1983 .
[80] Samuel S. Blackman,et al. Multiple-Target Tracking with Radar Applications , 1986 .
[81] P. Fearnhead,et al. An improved particle filter for non-linear problems , 1999 .
[82] Wolfram Burgard,et al. Tracking multiple moving targets with a mobile robot using particle filters and statistical data association , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).
[83] P. Pérez,et al. Tracking multiple objects with particle filtering , 2002 .
[84] Bruno Siciliano,et al. Modelling and Control of Robot Manipulators , 1997, Advanced Textbooks in Control and Signal Processing.
[85] Jeroen D. Hol,et al. Resampling in particle filters , 2004 .
[86] Arnaud Doucet,et al. A survey of convergence results on particle filtering methods for practitioners , 2002, IEEE Trans. Signal Process..
[87] F. Gustafsson,et al. Complexity analysis of the marginalized particle filter , 2005, IEEE Transactions on Signal Processing.
[88] Robin J. Evans,et al. Comparison of suboptimal strategies for optimal own-ship maneuvers in bearings-only tracking , 1998, Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207).
[89] X. Rong Li,et al. Survey of maneuvering target tracking: dynamic models , 2000, SPIE Defense + Commercial Sensing.
[90] Nando de Freitas,et al. The Unscented Particle Filter , 2000, NIPS.
[91] A. Isaksson. On System Identification in one and two Dimensions with Signal Processing Applications , 1988 .
[92] Peter Andersson,et al. Adaptive Forgetting in Recursive Identification through Multiple Models , 1985 .
[93] F. Gustafsson. Estimation of Discrete Parameters in Linear Systems , 1993 .
[94] Fredrik Gunnarsson. Power control in cellular radio system: Analysis, design and estimation , 2000 .
[95] Jakob Roll. Local and Piecewise Affine Approaches to System Identification , 2003 .
[96] Y. Boers. On the number of samples to be drawn in particle filtering , 1999 .
[97] Hisashi Tanizaki,et al. Nonlinear and nonnormal filters using Monte Carlo methods , 1997 .
[98] Dieter Fox,et al. Real-time particle filters , 2004, Proceedings of the IEEE.
[99] P. Robinson,et al. Modified spherical coordinates for radar , 1994 .
[100] Lennart Ljung,et al. Adaptive control based on explicit criterion minimization , 1985, Autom..
[101] Jeffrey K. Uhlmann,et al. Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.
[102] Multiple model estimation using the bootstrap filter , 1998 .
[103] Mikael Norrlöf,et al. An adaptive iterative learning control algorithm with experiments on an industrial robot , 2002, IEEE Trans. Robotics Autom..
[104] Peter I. Corke,et al. A robotics toolbox for MATLAB , 1996, IEEE Robotics Autom. Mag..
[105] H. Cramér. Mathematical methods of statistics , 1947 .
[106] Thomas B. Schön,et al. Marginalized particle filters for mixed linear/nonlinear state-space models , 2005, IEEE Transactions on Signal Processing.
[107] Jonas Jansson. Tracking and decision making for automotive collision avoidance , 2002 .
[108] Jan-Erik Strömberg,et al. A Mode Switching Modelling Philosophy , 1994 .
[109] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[110] Magnus Larsson,et al. Behavioral and Structural Model Based Approaches to Discrete Diagnosis , 1999 .
[111] Valur Einarsson. Model Checking Methods for Mode Switching Systems , 2000 .
[112] X. R. Li,et al. Survey of maneuvering target tracking. Part I. Dynamic models , 2003 .
[113] T. McKelvey. Identification of State-Space Models from Time and Frequency Data , 1995 .
[114] Jun S. Liu,et al. Metropolized independent sampling with comparisons to rejection sampling and importance sampling , 1996, Stat. Comput..
[115] J R Treat,et al. TRI-LEVEL STUDY OF THE CAUSES OF TRAFFIC ACCIDENTS: FINAL REPORT , 1979 .
[116] R. Fisher. 001: On an Absolute Criterion for Fitting Frequency Curves. , 1912 .
[117] N. Bergman. Bayesian Inference in Terrain Navigation , 1997 .
[118] J. C. Hung,et al. Performance evaluation of six terrain stochastic linearization techniques for TAN , 1991, Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 1991.
[119] A. Gualtierotti. H. L. Van Trees, Detection, Estimation, and Modulation Theory, , 1976 .
[120] Yaakov Bar-Shalom,et al. Design of an interacting multiple model algorithm for air traffic control tracking , 1993, IEEE Trans. Control. Syst. Technol..
[121] Alessandro De Luca,et al. A frequency-domain approach to learning control: implementation for a robot manipulator , 1989, Proceedings. IEEE International Symposium on Intelligent Control 1989.
[122] Christian P. Robert,et al. The Bayesian choice , 1994 .
[123] G. Casella,et al. Rao-Blackwellisation of sampling schemes , 1996 .
[124] Jonas Blom. Power Control in Cellular Radio Systems , 1998 .
[125] J. Geweke,et al. BAYESIAN INFERENCE IN ECONOMETRIC MODELS USING , 1989 .
[126] A. Holtsberg,et al. Estimation and confidence in bearings only tracking , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.
[127] Kjell Nordström. Uncertainty, Robustness and Sensitivity Reduction in the Design of Single Input Control Systems , 1987 .
[128] Philip Rabinowitz,et al. Methods of Numerical Integration , 1985 .
[129] Anders Holtsberg. A Statistical Analysis of Bearings-Only Tracking , 1992 .
[130] P. Lindskog. Methods, Algorithms and Tools for System Identification Based on Prior Knowledge , 1996 .
[131] Allan Gut,et al. An intermediate course in probability , 1995 .
[132] H. Fortell. Algebraic Approaches to Normal Forms and Zero Dynamics , 1995 .
[133] T. Karlsson. Terrain Aided Underwater Navigation using Bayesian Statistics , 2002 .
[134] Roy L. Streit,et al. A comparison of the JPDAF and PMHT tracking algorithms , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.
[135] Jun S. Liu,et al. Blind Deconvolution via Sequential Imputations , 1995 .
[136] Zhe Chen,et al. BITAN-II: an improved terrain aided navigation algorithm , 1996, Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation.
[137] Fredrik Gustafsson,et al. Range estimation using angle-only target tracking with particle filters , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).
[138] T. R. Kronhamn,et al. Bearings-only target motion analysis based on a multihypothesis Kalman filter and adaptive ownship motion control , 1998 .
[139] Sangjin Hong,et al. Performance and complexity analysis of adaptive particle filtering for tracking applications , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..
[140] K. Edström. Switched Bond Graphs : Simulation and Analysis , 1999 .
[141] John Vanderkooy,et al. Quantization and Dither: A Theoretical Survey , 1992 .
[142] Simon J. Godsill,et al. On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..
[143] Ali H. Sayed,et al. Linear Estimation (Information and System Sciences Series) , 2000 .
[144] Christophe Andrieu,et al. Iterative algorithms for optimal state estimation of jump Markov linear systems , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).
[145] X. R. Li,et al. A Survey of Maneuvering Target Tracking—Part III: Measurement Models , 2001 .
[146] Jonas Elbornsson,et al. Analysis, Estimation and Compensation of Mismatch Effects in A/D Converters , 2003 .
[147] Anders Helmersson,et al. Methods for robust gain scheduling , 1995 .
[148] Petar M. Djuric,et al. Gaussian sum particle filtering , 2003, IEEE Trans. Signal Process..
[149] Fredrik Gustafsson,et al. Particle filters for positioning, navigation, and tracking , 2002, IEEE Trans. Signal Process..
[150] J. Huang,et al. Curse of dimensionality and particle filters , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).
[151] Neil J. Gordon,et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..
[152] C. Andrieu,et al. A Particle Filter for Model Based Audio Source Separation , 2000 .
[153] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[154] Van Overbeek. On-Line Structure Selection for the Identification of Multivariable Systems , 1982 .
[155] Predrag Pucar. Modeling and Segmentation using Multiple Models , 1995 .
[156] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[157] Branko Ristic,et al. Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters , 2004, EURASIP J. Adv. Signal Process..
[158] T. Başar,et al. A New Approach to Linear Filtering and Prediction Problems , 2001 .
[159] Thomas Sch. On Computational Methods for Nonlinear Estimation , 2003 .
[160] Mikael Norrlöf,et al. Iterative Learning Control : Analysis, Design, and Experiments , 2000 .
[161] Tommy Svensson. Mathematical Tools and Software for Analysis and Design of Nonlinear Control Systems , 1992 .
[162] Arnaud Doucet,et al. Markov chain Monte Carlo data association for target tracking , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[163] P. Willett,et al. Fusion of quantized measurements via particle filtering , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).
[164] Y. Bar-Shalom. Tracking and data association , 1988 .
[165] Fredrik Gustafsson,et al. Adaptive filtering and change detection , 2000 .
[166] Donald Reid. The application of multiple target tracking theory to ocean surveillance , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.
[167] Branko Ristic,et al. Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .
[168] Neil J. Gordon,et al. Littoral tracking using particle filter , 2002, Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997).
[169] Marc-Alain Simard,et al. Central level fusion of radar and IRST contacts and the choice of coordinate system , 1993, Defense, Security, and Sensing.
[170] Peter A. J. Nagy. Tools for Knowledge-Based Signal Processing with Applications to System Identification , 1992 .
[171] S. Andersson. On Dimension Reduction in Sensor Array Signal Processing , 1992 .
[172] Mikael Norrlöf,et al. PGT - A path Generation Toolbox for MatLab (v0.1) , 2003 .
[173] Niclas Bergman,et al. Recursive Bayesian Estimation : Navigation and Tracking Applications , 1999 .
[174] S. Taylor,et al. Kendall's Advanced Theory of Statistics, Volume 1 (5th Edition) , 1988 .
[175] Krzysztof Kozłowski,et al. Modelling and Identification in Robotics , 1998 .
[176] R. Fisher,et al. On the Mathematical Foundations of Theoretical Statistics , 1922 .
[177] D. Avitzour. Stochastic simulation Bayesian approach to multitarget tracking , 1995 .
[178] H. Sorenson,et al. Recursive bayesian estimation using gaussian sums , 1971 .
[179] J. Sjöberg. Non-Linear System Identification with Neural Networks , 1995 .
[180] S. Ljung. Fast Algorithms for Integral Equations and Least Squares Identification Problems , 1983 .
[181] B. Widrow,et al. Statistical theory of quantization , 1996 .
[182] Neil J. Gordon,et al. Tracking in the presence of intermittent spurious objects and clutter , 1998, Defense, Security, and Sensing.