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In this work, the problem of direction finding is addressed. We show the Direction Of Arrival (DOA) estimation can be realized through the non-unitary joint diagonalization of spatial quadratic time-frequency. We use an approach of selection of time-frequency points to construct the set of matrices which will be jointly diagonalized to estimate the noise subspace. The main advantage of this method...
An approach to detection of anomalous measurements (fault detection), which occur at solving guaranteed estimation issue is outlined. It is based on statistical processing the innovation sequence in the Kalman filter. A special case of the linear dynamical system, which state is observed only within a short-time interval, is considered; statistical characteristics of the innovation sequence are shown...
In order to enhance the performance of the existing beamformer-based direction-of-arrival (DOA) estimation methods, a novel DOA estimation method based on the sparse and low-rank decomposition of the sample covariance matrix is proposed. First, the sample covariance matrix is divided into the covariance matrix of the desired signal and interference as well as that of noise. The first component is...
As more than 2.5 quintillion bytes of data are generated every day, the era of big data is undoubtedly upon us. Running analysis on extensive datasets is a challenge. Fortunately, a significant percentage of the data accrued can be omitted while maintaining a certain quality of statistical inference in many cases. Censoring provides us a natural option for data reduction. However, the data chosen...
We focus on the 3-dimensional (3D) source localization passively by using TDOA and AOA in the presence of sensor errors. Determining the position from the TDOA and AOA measurements is not an easy task because the relationship between them is nonlinear. We present a new WLS solution that the TDOA equation is simpler than relevant literature (Yin and Wan, A Simple and Accurate TDOA-AOA Localization...
In this work, we evaluate performances of four super-resolution techniques for estimating complex spectra or points under various scenarios. Suitable for resolving non-coherent signals, the two adaptive techniques (Root-MUSIC and ESPRIT) use multiple snapshots to acquire data covariance matrix, which can then be divided into signal subspace and noise subspace for estimating the desired complex parameters...
Pilot contamination is a throughput limiting factor in cellular massive MIMO systems. Previous work has shown that the impact of pilot-contamination can be reduced by exploiting structural information in form of channel covariance matrices. Additionally, significant gains can be obtained through coordinated user assignment. In this paper, we extend these approaches to a realistic scenario with imperfect...
Weighted centroid localization (WCL) based on received signal strength (RSS) measurements is an attractive low-complexity solution that enables cognitive radios (CRs) to have a geolocation awareness of the radio environment. In this paper, we propose a new analytical framework to accurately calculate the performance of WCL based on the statistical distribution of the ratio of two quadratic forms in...
This article proposed a novel method to determine the number of principal components and the optimal values of tuning factors for kernel principal component models. Existing work predominantly relies on ad-hoc rules or cross-validatory approaches to estimate. To guarantee statistical independence, the proposed technique incorporates a two-fold cross-validatory approach by omitting one variable in...
Massive MIMO is a variant of multiuser MIMO, in which the number of antennas M at the base-station is very large and generally much larger than the number of spatially multiplexed data streams to the users. It turns out that by increasing the number of antennas M at the base-station and as a result increasing the spatial resolution of the array, although the received signal from each user tends to...
In this paper, we propose a new channel tracking method for massive multiple-input multiple-output (MIMO) systems under both the time-varying and spatial-varying circumstance. With spatial-temporal basis expansion model (ST-BEM), the channel information is decomposed into the spatial information and gain information, where the former is determined by the central angle as well as the angular spread...
For the problem that traditional DOA (Direction Of Arrival) estimation algorithms often fail to deal with coherent signals, a new high accuracy DOA estimation method based on weighted noise subspace is proposed. Considering the received data matrix obtained by uniform liner array, the proposed method makes full use of the cross-covariance information of it to construct an augmented matrix and performs...
In the present paper, we consider a co-array as a coprime array or a nested array. Pal et al. proposed a method to extend a co-array to a larger virtual array, then implemented the spatial smoothing technique to construct the covariance matrix of a virtual uniform linear array (ULA). Thus subspace-based direction of arrival (DOA) estimation algorithms can be used to detect more sources than the number...
We consider the problem of factorizing a matrix with discrete-valued entries as a product of two low-rank matrices. Under a probabilistic framework, we seek for the minimum mean-square error estimates of these matrices, using full Bayes and empirical Bayes approaches. In the first case, we devise an integration scheme based on the Gibbs sampler that accounts also for hyperparameter and noise variance...
Quadrature homodyne interferometers are frequently used in dimensional metrology. Their measurement signals exhibit offsets, unequal amplitudes and phase difference. Frequently, there exists a significant component of the measurement noise common to both (Sine and Cosine) quadrature signals, such that the noise of quadrature signals is correlated. Presented is a method for estimation the unknown correlation...
In this study, speedsensorless IM drive based on unscented Kalman filter (UKF) with the online estimations of stator stationary axis components of stator currents, rotor fluxes, rotor mechanical speed, load torque including the friction term, and stator resistance is designed. Therefore, the proposed speed-sensorless IM drive is robust to load torque and stator resistance changes. Different challenging...
In this paper, a cost efficient fusion scheme, Ubiquitous Tracking with Motion and Location Sensor (UTMLS), is proposed for the accurate localization and tracking in mixed GPS-friendly, GPS-challenging, and GPS-denied scenario. The proposed drift-reduction method in UTMLS addresses the cumulating error issue in the indoor tracking with the consumer grade motion sensor. The proposed hypothesis test...
The estimator bank approach allows improving the performance of direction of arrival (DOA) estimation in the area of low signal-to-noise ratio. In the paper, the estimator bank is formed from the modified Beamspace Root-MUSIC estimator using resampling by adding pseudo-noise. The illumination of outlying roots of the modified beamspace Root-MUSIC polynomial is used instead of elimination of entire...
This paper firstly analyzes the shortcoming of a self-organizing incremental neural network (SOINN), then proposes a novel online similarity metric and online adaptive kernel density estimator to handle 2 basic problems of unsupervised learning: clustering and density estimation. Our approach is an extension of the standard Gaussian process, online density estimator and SOINN; not only does it fully...
We consider the problem of scheduling a set of sensors to observe the state of a discrete-time linear system subject to a limited energy budget. Our goal is to devise a sensor schedule that minimizes the mean squared error (MSE) of an optimal estimator (i.e., the Kalman Filter). Both the minimum-MSE and the minimum-cardinality optimal sensor scheduling problems are inherently combinatorial, and computationally...
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