Results 31 to 40 of about 82,988 (261)
Sensors, 2020 Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-space ...
Chenghao Shan +3 more
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Remote Sensing, 2020 Synthetic aperture radar (SAR) tomography has shown great potential in multi-dimensional monitoring of urban infrastructures and detection of their possible slow deformations. Along this line, undeniable improvements in SAR tomography (TomoSAR) detection
Hossein Aghababaei
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High-Dimensional Covariance Estimation via Constrained Lq-Type Regularization
Mathematics, 2023 High-dimensional covariance matrix estimation is one of the fundamental and important problems in multivariate analysis and has a wide range of applications in many fields.
Xin Wang +3 more
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Robustness Analysis Of Covariances Matrix Estimates
, 2010 Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Mahot, Mélanie +3 more
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Knowledge-Aided Structured Covariance Matrix Estimator Applied for Radar Sensor Signal Detection
Sensors, 2019 This study deals with the problem of covariance matrix estimation for radar sensor signal detection applications with insufficient secondary data in non-Gaussian clutter. According to the Euclidean mean, the authors combined an available prior covariance
Naixin Kang, Zheran Shang, Qinglei Du
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Sensors, 2022 Frequency diverse array (FDA)-multiple-input multiple-output (MIMO) radars can generate a range-angle two-dimensional transmit steering vector (SV), which is capable of suppressing mainbeam deceptive jamming in the transmit–receive frequency domain by ...
Fuhai Wan, Jingwei Xu, Zhenrong Zhang
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Blind Estimation of Spreading Code Sequence of QPSK-DSSS Signal Based on Fast-ICA
Information, 2023 Most of the existing estimation methods of spreading code sequence are not suitable for the QPSK-DSSS. We propose a spreading code sequence estimation method based on fast independent component analysis (Fast-ICA). It mainly includes signal preprocessing,
Lu Xu, Xiaxia Liu, Yijia Zhang
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Estimating model error covariance matrix parameters in extended Kalman filtering [PDF]
Nonlinear Processes in Geophysics, 2014 The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user.
A. Solonen +4 more
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Tuning the Parameters for Precision Matrix Estimation Using Regression Analysis
IEEE Access, 2019 Precision matrix, i.e., inverse covariance matrix, is widely used in signal processing, and often estimated from training samples. Regularization techniques, such as banding and rank reduction, can be applied to the covariance matrix or precision matrix ...
Jun Tong +4 more
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Molecular Oncology, EarlyView.This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic +10 more
wiley +1 more source