Results 31 to 40 of about 80,517 (261)
IET Radar, Sonar & Navigation, 2021 To improve the space‐time adaptive processing (STAP) performance of airborne radar in complex environment, a generalised eigenvalue reweighting covariance matrix estimation algorithm called GERCM is proposed here. First, the interference plus noise (IPN)
Hao Xiao, Tong Wang, Cai Wen, Bing Ren
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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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High‐dimensional covariance matrix estimation [PDF]
WIREs Computational Statistics, 2019 AbstractCovariance matrix estimation plays an important role in statistical analysis in many fields, including (but not limited to) portfolio allocation and risk management in finance, graphical modeling, and clustering for genes discovery in bioinformatics, Kalman filtering and factor analysis in economics. In this paper, we give a selective review of
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Sample Space-time Covariance Matrix Estimation [PDF]
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations.
Delaosa, Connor +4 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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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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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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Robustness Analysis Of Covariances Matrix Estimates
, 2010 Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Mahot, Mélanie +3 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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Applied Sciences, 2021 For adaptive ultrasound imaging, a reliable estimation of the covariance matrix has a decisive influence on the performance of beamformers. In this paper, we propose a new cross subaperture averaging generalized sidelobe canceler approach (GSC-CROSS) for
Jin Yang +5 more
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