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A Probabilistic Perspective on Gaussian Filtering and Smoothing [PDF]
, 2010 15.07.13 KB. Ok to add report to Spiral.We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of ...
Deisenroth, MP, Ohlsson, H
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Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
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A parallel Kalman filter via the square root Kalman filtering [PDF]
, 1993 A parallel algorithm for Kalman filtering with contaminated observations is developed. Theı parallel implementation is based on the square root version of the Kalman filter (see [3]).
Romera, Rosario, Cipra, Tomas
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On Kalman Filtering with Nonlinear Equality Constraints [PDF]
, 2007 The state space description of some physical systems possess nonlinear equality constraints between some state variables. In this paper, we consider the problem of applying a Kalman filter-type estimator in the presence of such constraints. We categorize
Julier, SJ +3 more
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Gong-kuang zidonghua, 2014 In view of problems of large errors and low accuracy of positioning technology in coal mine, the strapdown inertial navigation system was introduced into coal mine personnel and equipment for precise positioning and navigation.
LIU Xiaowen, WANG Cun, WANG Long
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Penalized likelihood estimation and iterative kalman smoothing for non-gaussian dynamic regression models [PDF]
, 1995 Dynamic regression or state space models provide a flexible framework for analyzing non-Gaussian time series and longitudinal data, covering for example models for discrete longitudinal observations.
Fahrmeir, Ludwig, Wagenpfeil, Stefan
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Bayesian Nonlinear Filtering via Information Geometric Optimization
Entropy, 2017 In this paper, Bayesian nonlinear filtering is considered from the viewpoint of information geometry and a novel filtering method is proposed based on information geometric optimization.
Yubo Li +5 more
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A Study on Sensor System Latency in VR Motion Sickness
Journal of Sensor and Actuator Networks, 2021 One of the most frequent technical factors affecting Virtual Reality (VR) performance and causing motion sickness is system latency. In this paper, we adopted predictive algorithms (i.e., Dead Reckoning, Kalman Filtering, and Deep Learning algorithms) to
Ripan Kumar Kundu +2 more
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Square root kalman filter with contaminated observations [PDF]
, 1992 The algorithm of square root Kalman filtering for the case of contaminated observations is described in the paper. This algorithm is suitable for the parallel computer implementation allowing to treat dynamic linear systems with large number of state ...
Rubio, A., Romera, Rosario, Cipra, Tomas
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A Review of Nonlinear Filtering Algorithms in Integrated Navigation Systems
SensorsNonlinear filtering algorithms have significant implications in the optimal estimation of navigation states and in improving the accuracy, reliability, and robustness of navigation systems.
Jiaqian Si, Yanxiong Niu, Botao Wang
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