Results 11 to 20 of about 39,931 (297)
Partial Diffusion Kalman Filter With Adaptive Combiners [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2021 Adaptive estimation of optimal combination weights for partial-diffusion Kalman filtering together with its mean convergence and stability analysis is proposed here. The simulations confirm its superior performance compared with the existing combiners. Sensor networks with limited accessible power highly benefit from this design.
Azam Khalili +4 more
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Journal of Research of the National Bureau of Standards, 1985 The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Brown, Steven D., Rutan, Sarah C.
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Fiber Optic Gyro Random Error Suppression Based on Dual Adaptive Kalman Filter. [PDF]
Micromachines (Basel)Li H +5 more
europepmc +3 more sources
Joint semi-blind detection and channel estimation in space-frequency trellis coded MIMO-OFDM [PDF]
, 2003 This paper considers an OFDM system with a multiple-input multiple-output (MIMO) configuration, which uses space-frequency trellis coding (SFTC). A novel method of decoding SFTC without a need to transmit separate training sequences is developed.
McGeehan, JP, Nix, AR, Piechocki, RJ
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Adaptive Kalman filter equaliser
Electronics Letters, 1980 A new adaptive equaliser for digital communication channels is proposed. It is derived from a state-variable representation of the communication channel by means of the extended Kalman filter technique. The equaliser proposed is structured as two Kalman filters, one estimating the transmitted data symbols, the other the unknown channel parameters.
DALLE MESE E, CORSINI, GIOVANNI
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Speed adaptation as Kalman filtering
Journal of Vision, 2008 If the purpose of adaptation is to fit sensory systems to different environments, it may implement an optimization of the system. What the optimum is depends on the statistics of these environments. Therefore, the system should update its parameters as the environment changes.
Barraza, Jose Fernando +1 more
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Adaptive smartphone-based sensor fusion for estimating competitive rowing kinematic metrics. [PDF]
, 2019 Competitive rowing highly values boat position and velocity data for real-time feedback during training, racing and post-training analysis. The ubiquity of smartphones with embedded position (GPS) and motion (accelerometer) sensors motivates their ...
Cloud, Bryn +7 more
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The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation
Sensors, 2016 This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead.
Siwei Gao +4 more
doaj +1 more source
Application of fractional sensor fusion algorithms for inertial mems sensing
Mathematical Modelling and Analysis, 2009 The work presents an extension of the conventional Kalman filtering concept for systems of fractional order (FOS). Modifications are introduced using the Grünwald‐Letnikov (GL) definition of the fractional derivative (FD) and corresponding truncation of ...
Michailas Romanovas +3 more
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A novel variational Bayesian adaptive Kalman filter with mismatched process noise covariance matrix
IET Radar, Sonar & Navigation, 2023 This paper proposes a novel variational Bayesian (VB) adaptive Kalman filter with mismatched process noise covariance matrix (PNCM). Firstly, this paper explains the reason why the predicted error covariance matrix (PECM) is chosen for variational ...
Xinrui Liu +3 more
doaj +1 more source