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Most of the tests proposed in the literature to verify if a given random multivariate dataset fits a spherical or elliptical distribution are designed for real valued data and rely on the estimation of high order moment matrices. Recently, a test that considers complex random vectors, derived based on the Schott spherical symmetry test was proposed aiming in a more proper analysis of PolSAR data....
Advancing a holistic theory of networks and network processes requires the extension of existing results in the processing of time-varying signals to signals supported on graphs. This paper focuses on the definition of stationarity and power spectral density for random graph signals, generalizes the concepts of autoregressive and moving average random processes to the graph domain, and investigates...
An effective method is proposed to estimate the desired-signal (S) subspace by the intersection between the signal-plus-interference (SI) subspace and a reference space covering the angular region where the desired signal is located. The estimated S subspace is robust to steering vector mismatch and overestimation of the SI subspace, capable of detecting the relative strength of the desired signal...
The problem of Angle-of-Arrival estimation of multiple sources in the presence of mutual coupling is addressed. The presence of unknown mutual coupling between antenna array elements is known to degrade the performance of direction-finding algorithms. We first present a result explaining why some traditional methods, that estimate Angles-of-Arrival (AoAs) of multiple sources in the presence of mutual...
Identifying the location of a target is a fundamental application in multistatic sonar. Numerous attempts have been made to improve the accuracy, computational efficiency and robustness of target positioning. Previous studies mostly use time delay and angle measurements for localization, or time delays and Doppler shifts if relative motions exist among the transmitters, target and receivers. This...
A two-stage method for off-grid coherent direction-of-arrival (DOA) estimation using atomic norm minimization based on the covariance matrix is proposed in this paper. In the first stage, by vectorizing the covariance matrix, a new off-grid model matched as a linear combination of two dimensional harmonic is presented, where the proposed denoising covariance matrix-based atomic norm minimization (DCMANM)...
In a low angle target parameter estimation scenario, the backscattered signals from targets are distorted by clutter and multipath, which degrades the performance of direction-of-arrival (DOA) estimator significantly. This paper presents a novel method using time reversal (TR) technique and coherent signal-subspace method (CSM) for DOA estimation in a low angle scenario. The TR method exploits target...
This paper provides bounds on the sample complexity of estimating Kronecker-structured dictionaries for Kth-order tensor data. The training samples are generated by linear combinations of these structured dictionary atoms and observed through white Gaussian noise. The lower bound follows from a lower bound on the minimax risk for general coefficient distributions and can be further specialized to...
In 2013, Nguyen and Yamada proposed Adaptive normalized quasi-Newton algorithm and its adaptive step size for accurate and stable extraction of the first generalized eigenvector. The adaptive step size is determined by an upper bound of the condition number of a time-varying matrix. However, the employed upper bound is fairly tight only when the size of matrix is small, which degrades the performance...
Cognitive radio (CR) systems need to detect the presence of a primary user (PU) signal by continuously sensing the spectrum area of interest. Radiowave propagation effects like fading and shadowing often complicate sensing of spectrum holes because the PU signal can be weak in a particular area. Cooperative spectrum sensing is seen as a prospective solution to enhance the detection of PU signals....
In this paper, a new method for two-dimensional (2-D) direction-of-arrival (DOA) estimation is proposed. We first reconstruct the covariance matrix of the coarray with block-Toeplitz structure and then retrieve the DOAs. Our method is computationally efficient as supported by the derived closed-form expression for the estimated covariance matrix. Unlike other methods, which require fully loaded arrays,...
We investigate the problem of direction of arrival (DOA) estimation using sparse linear arrays, such as co-prime and nested arrays, in the case of missing data resulting from sensor failures. We introduce a signal model where sensor failures occur after taking certain number of snapshots. We formulate a structured covariance estimation problem by exploiting the special geometry of sparse linear arrays,...
Parameter estimation has applications in many fields of signal processing, such as spectral analysis or direction-of-arrival estimation. Subspace-based methods like root-MUSIC and ESPRIT provide high parameter resolution at low computational complexity by exploiting specific sampling structure, namely uniform linear sampling and shift-invariant sampling, respectively. On the other hand, compressed...
The digital scans of double sided documents suffer from distortions because the contents on the back side of the document often shows up on the front side in the scans and vice-versa either due to transparency of the paper or due to ink-bleeding. This is show-through effect. In this paper a state-space based approach is proposed for removing this commonly found contamination in the scans of duplex...
It is known that accurate partition of subspaces is important to fourth-order statistics based multiple signal classification (FO-MUSIC) algorithm. However, when the number of signals exceeds the number of array elements, the error of conventional subspace partition method will increase, and the performance of FO-MUSIC algorithm will decrease. A novel subspace partition method for FO-MUSIC algorithm...
It has been recently shown that judicious use of correlation priors can lead to significant improvement in the performance of sparse estimation algorithms. This happens primarily due to two reasons: (i) second order statistics or covariance matrix of signals can possess unique structures that are not captured in the raw measurements (ii) these structures involve non linear functions of the underlying...
In many angle of arrival (AoA) estimation algorithms for broadband signals a-prior knowledge about the impinging signals' bandwidth is required for the algorithms to function. In this paper, we present a new technique for estimating the AoA and the bandwidth of the received broadband signals without requiring any knowledge of the bandwidth of the received signals. The proposed technique consists of...
In this paper, a new algorithm to suppress the interferences for Direction-of-Arrival(DOA) estimation is presented. The method is based on the property of the noise subspace invariant to power of emitters. With theoretical analysis and computer simulations, it is shown that the proposed method has a good performance on signal DOA estimation under disturbances.
Feature extraction is very important for interpreting polarimteric SAR images. Compact Polarimetrie imaging mode has been provided as an experimental mode in ALOS/PALSAR-2 to enable wide swath coverages of more polarimeric observations compared to the conventional dual-pol modes. In this study, to explore more information from compact data, we propose a least squares (LS) method to estimate the parameters...
This paper presents a novel array configuration which improves the accuracy for high-resolution direction of arrival (DOA) estimation using the concept of Khatri-Rao (KR) product. We extended the concept of two-level nested array and found a novel array configuration which has larger array aperture and more degree of freedom compared with that of the two-level nested array. The performance of the...
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