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We consider a sensor scheduling and remote estimation problem with one sensor and one estimator. At each time step, the sensor makes an observation on the state of a source, and then decides whether to transmit its observation to the estimator or not. The sensor is charged a cost for each transmission. The remote estimator generates a real-time estimate on the state of the source based on the messages...
A convex optimization based approach is presented to perform model-data assimilation of spatial temporal dynamical systems where sensor error characteristics are not available. The key idea of the proposed technique is that one should not make any assumption regarding the statistical properties of sensor data when they are not available. Recently developed quadrature scheme, Conjugate Unscented Transformation...
This work presents a comparative study of Least Squares Filter, Kalman Filter and Unscented Kalman Filter for estimating the secondary current phasor distorted due to saturation of Current Transformers (CTs). Several distorted current signals were generated in a Real Time Digital Simulator (RTDS) and embedded in noise. Then, these signals were segmented in two kinds of regions, named saturated and...
This paper presents power system frequency estimation by using a Modified Non-Linear Least Square (MNLS) Technique. The proposed approach uses a variable and dynamically changing A matrix as per the sampling instant. So less memory is required for storage of A matrix. The performance of the proposed method is better under all conditions as compared to NLS method. The performance of the proposed method...
In this paper, three individual indices, as well as a new comprehensive index, are introduced to evaluate prediction intervals. Then, two practical methods, namely, Interval Extension Method and Optimal Scalar Method are proposed to build the prediction intervals based on an ensemble of Extreme Learning Machines. Case studies on hour-ahead load interval forecasting with respect to Chicago Metro Area...
Correntropy has been successfully applied in non-Gaussian signal processing, but the superior performance achieved is depends on appropriate selection of the kernel width. How to select a proper kernel width is a crucial problem in correntropy applications. In this paper, we propose an adaptive algorithm to update the kernel width, which is set at a maximum between the absolute value of instantaneous...
Event-based sampling strategies allow for reducing the amount of communications between a sensor and the estimation module. This reduction is interesting specially when the sensors are linked by a shared wireless network. This paper proposes new event-based sampling methods based on the Mahalanobis distance concept. Combined with an Event-Based State Estimator, they provide the same level of performance...
We consider linear continuous-time systems with multiplicative noise and polytopic type parameter uncertainty and we address the problems of H∞ state-feedback control and filtering of these systems. These problems are solved by applying a vertex dependent Lyapunov function that considerably reduces the over-design associated with the classical “quadratic” design that is based on a single Lyapunov...
Two dimensional target localization using AOA measurements is considered in this paper. By conducting repeated experiments, the complex AOA (CAOA) method found that for the two-sensor and single-target scenario, the accuracy of the intersection of two bearing lines can be divided into different layers. However, the experiments are very time consuming. Also, the division of the intersection region...
In this paper, different strategies for the calculation of the Harte's Harmonic Change Detection Function (HCDF) are discussed. HCDFs can be used for detecting chord boundaries for Automatic Chord Estimation (ACE) tasks, where the chord transitions are identified as peaks in the HCDF. We show that different audio features and different novelty metric have significant impact on the overall accuracy...
This paper presents an approach intended for tracking of biological non-stationary signals. The proposed approach utilizes a Kalman filter autoregressive model together with a method for estimation of covariance matrices of the uncorrelated process noise and measurement noise. The method was tested in simulations, where the ability of tracking of a class of time varying autoregressive processes was...
In this paper, a novel state-of-charge (SOC) estimation method is proposed for lithium-ion battery packs of electric vehicles. An equivalent circuit model, which comprises an open circuit voltage source and a resistance-capacitance network connected in series, is built for each cell to characterize its dynamic and static performance. Then, the EKF is applied to calculate each cell's SOC. By calculating...
Target localization using AOA measurements has attracted substantial attention for several decades. Traditional algorithms regard the target position as a non-random parameter and employ estimators like least squares (LS) or maximum likelihood (ML) to estimate the target location. In this paper, we propose a new framework for target localization using AOA measurements. The idea of this framework is...
In this paper a state estimator for high tech flexible systems with an inherent nonlinearity in the output dynamics is proposed. We consider an application in which sensor measurements of the flexible system become parameter (position) dependent. An LPV setting is proposed for the design of estimators that estimate flexible modes of the system. The possibility of pole placement for the error dynamics...
The localization, that allows to precisely know the orientation and position of a system in the environment, is still challenging in urban environments due to satellite occlusion. This phenomenon reduces the data redundancy and provides bad satellite geometry and reflected signals, called multipaths, that distort the measurements and make them erroneous. The RAIM method, integrated in most GPS receivers,...
In this paper, robustness and accuracy of centroiding methods that are operating as part of star extraction process are investigated. Attitude determination systems consist of star extraction, star identification and pose estimation subsystems. However, most of the time the upper limit of their performance is determined by the accuracy of the star extraction step. In order to achieve higher localization...
In this paper, we proposed a region-based approach for indoor localization based on the fingerprint of radio signal strength (RSS). Unlike conventional fingerprint-based methods that based on point information to infer user's location, we used region information for indoor localization. Our results show that the proposed system has better positioning accuracy and more robustness to signal noise and...
Simulation of higher order nonlinear device currents in RF integrated circuits becomes crucial when high linearity is a design goal. Prediction of the nonlinear behavior of passive circuits like mixers, attenuators or switches play an important role in low-distortion designs, but also causes trouble due to the inability of threshold voltage based compact models to inherently model higher order nonlinearities...
This paper presents a geometrical method for solving the non-negative Blind Source Separation (BSS) problem. The method is based on a weak sparsity condition: for each source, there should exist at least one observed vector where only this source is non-zero. The method does not require but allows the sum-to-one constraint for the mixing parameters or sources. Considering each observed vector as an...
Conventional threshold-based method, such as nulling or clipping, is simple and effective for mitigation of impulsive noise (IN) in power-line commnucations (PLC) environment. However, we raise two issues for the threshold-based approach. First, for orthogonal frequency division modulation (OFDM) broadband PLC systems, the high peak-to-average power ratio (PAPR) characteristics of the received OFDM...
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