Results 41 to 50 of about 359,270 (146)
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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Sensors, 2020 The paper presents a method of computational complexity reduction in Extended Kalman Filters dedicated for systems with non-linear measurement models.
Piotr Kaniewski
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Reduce Position and Velocity RMS Error of Non-linear Filters in LEO Satellite Radar Tracking [PDF]
فصلنامه علوم و فناوری فضایی, 2017 For the detection of and tracking thelow earth orbit Satellites (LEO), there are different methods such as optic, laser and radar tracking, among which radar tracking is the best.
Javad Salem +2 more
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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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, 2023 The well-known Kalman filters model dynamical systems by relying on state-space representations with the next state updated, and its uncertainty controlled, by fresh information associated with newly observed system outputs.
Zambon, Daniele, Alippi, Cesare
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Future BatteriesAccurate estimation of supercapacitor state-of-charge (SOC) is vital for optimal energy management in electric vehicles (EVs), particularly within hybrid energy storage systems (HESS). Challenges arise from nonlinear dynamics, self-discharge, temperature
Islam A. Sayed, Yousef Mahmoud
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An Introduction to Kalman Filters
Measurement + Control, 1986 Kalman filters are a powerful tool for reducing the effects of noise in measurements. This paper gives a no-nonsense introduction to the subject for people with A-level maths.
G C Dean
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Adaptive Measurement Noise for Robust Kalman Filtering in Smart Beehive Telemetry
IEEE AccessHoneybee colony monitoring generates multimodal, non-stationary telemetry streams that require reliable recursive state estimation with well-calibrated uncertainty for digital apiculture.
H. A. A. U. Ranasinghe +4 more
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Journal of Applied Mathematics, 2014 A direct approach of designing weighted fusion robust steady-state Kalman filters with uncertain noise variances is presented. Based on the steady-state Kalman filtering theory, using the minimax robust estimation principle and the unbiased linear ...
Wen-Juan Qi, Peng Zhang, Zi-Li Deng
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Simple and extended Kalman filters : an application to term structures of commodity prices. [PDF]
This article presents and compares two different Kalman filters. These methods provide a very interesting way to cope with the presence of non-observable variables, which is a frequent problem in finance. They are also very fast even in the presence of a
Lautier, Delphine, Galli, Alain
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