Results 181 to 190 of about 40,768 (209)

Geomagnetic orbit determination: EKF or UKF?

Aircraft Engineering and Aerospace Technology, 2021
Purpose Autonomous orbit determination using geomagnetic measurements is an important backup technique for safe spacecraft navigation with a mere magnetometer. The geomagnetic model is used for the state estimation of orbit elements, but this model is highly nonlinear.
Wu, Jin, Liu, Ming, Zhang, Chengxi, Huang, Yulong, Zhou, Zebo   +4 more
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EKF Schemes in Array Processing

1993
The small error approximation is used to derive a linear relationship between the source parameters (i.e. power levels and directions of arrival) and a measurement of the covariance error matrix, defined as the difference between the data covariance and a covariance model from the scenario parameters. The resulting framework reveals the similarity with
M. A. Lagunas, A. Perez-Neira, D. Maiwald   +2 more
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TDoA based EKF localization for LTE

2016 Twenty Second National Conference on Communication (NCC), 2016
The advent of location based services has increased the need for accurate positioning of mobile stations (MS). Global Positioning Systems (GPS) is not reliable in indoor and urban environments. Cellular wireless communication systems like the OFDM based 3GPP-LTE provide an alternative via Time Difference of Arrival (TDoA) measurements. Typical Extended
Rohan Sriram, Devendra Jalihal
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EKF learning for feedforward neural networks

2003 European Control Conference (ECC), 2003
Learning for feedforward neural networks can be regarded as a nonlinear parameter estimation problem with the objective of finding the optimal weights that provide the best fitting of a given training set. The extended Kalman filter is well-suited to accomplishing this task, as it is a recursive state estimation method for nonlinear systems.
ALESSANDRI, ANGELO, G. CIRIMELE, M. CUNEO, S. PAGNAN, SANGUINETI, MARCELLO   +4 more
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MCC-EKF for Autonomous Car Security

2020 Fourth IEEE International Conference on Robotic Computing (IRC), 2020
This work attempts to answer two problems. (1) Can we use the odometry information from two different Simultaneous Localization And Mapping (SLAM) algorithms to get a better estimate of the odometry? and (2) What if one of the SLAM algorithms gets affected by shot noise or by attack vectors, and can we resolve this situation?
Ashutosh Singandhupe, Hung Manh La
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Head attitude tracking based on EKF

SPIE Proceedings, 2012
As there exists a high mean-square error for the monocular vision PNP algorithms in solving the problem of continuous head attitude tracking especially at certain relative orientations, this paper presented a new refinement method based on Extended Kalman Filter.
Kai Ma, Quanxin Ding, Quizhi Zhang, Jinfeng Zhang   +3 more
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MIMO Propagation Parameter Tracking using EKF

2006 IEEE Nonlinear Statistical Signal Processing Workshop, 2006
In this paper we describe the application of extracting the MIMO radio channel propagation parameters from channel sounding measurements using the Extended Kalman Filter. This approach allows to capture the dynamics of the radio propagation channels and enables recursive, computationally low-complexity (compared with traditional iterative maximum ...
Jussi Salmi, Andreas Richter, Visa Koivunen   +2 more
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IMPACT OF PERTURBATION ESTIMATOR ON EKF-SLAM RESULTS

IFAC Proceedings Volumes, 2007
Abstract This paper deals with the Simultaneous Localization and Map building (SLAM) problem using an Extended Kalman Filter with Perturbation Estimator (EKFPE). The perturbation estimator is used to take systematic errors into account. These disturbance estimates are added to vehicle states in a feedback loop to improve location and map estimates ...
Chanier, François, Checchin, Paul, Blanc, Christophe, Trassoudaine, Laurent   +3 more
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Exact Learning Curves for EKF Training

1998
We formulate a learning algorithm for online learning in neural networks using the principles of the Extended Kaiman Filter approach. This gives rise to a Bayesian learning scheme where the learning rate parameter is adapted automatically. The approach is applied to regression problems whereby the rule to be learned is non-stationary, examining both ...
B. Schottky, D. Saad
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Geomagnetic Surface Navigation Using Adaptive EKF

2007 2nd IEEE Conference on Industrial Electronics and Applications, 2007
In need of accurate and covert positioning, a geomagnetic surface navigation system is investigated in the paper. The Earth anomaly magnetic field intensity is selected as the reference to bound the INS (inertial navigation system) errors. Using stochastic linearization technique, we have proposed an EKF (extended Kalman filtering) algorithm which is ...
Hua Mu, Meiping Wu, Xiaoping Hu, Hongxu Ma   +3 more
openaire   +1 more source