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Practical method to predict an upper bound for minimum variance track-to-track fusion
, Article IET Signal Processing ; Volume 11, Issue 8 , 2017 , Pages 961-968 ; 17519675 (ISSN) ; Malaek, S. M. B ; Sharif University of Technology
Abstract
This study deals with the problem of track-to-track fusion in a sensor network when the correlation terms between the estimates of the agents are unknown. The proposed method offers an upper bound for the optimal minimum variance fusion rule through construction of the correlation terms according to an optimisation scheme. In general, the upper bound filter provides an estimate that is more conservative than the optimal estimate generated by the minimum variance fusion rule, while at the same time is less conservative than one obtained by the widely used covariance intersection method. From the geometrical viewpoint, the upper bound filter results in the inscribed largest volume ellipsoid...
Statistical Interpolation of Non-Gaussian AR Stochastic Processes
, M.Sc. Thesis Sharif University of Technology ; Amini, Arash (Supervisor)
Abstract
white noise or an innovation process through an all-pole filter. Applications of these processes include speech processing, RADAR signals and stock market data modeling. There exists an extensive research material on the AR processes with Gaussian innovation, however studies about the non-Gaussian case have been much more limited, while in many applications the asymptotic behavior of the signal is non-Gaussian. Non-Gaussian processes have an advantage over Gaussian ones in being capable of modeling sparsity. Assuming an appropriate non-Gaussian innovation one can suggest a more realistic description of sparse signals and predict their behavior or estimate their unknown values successfully....
Estimating the four parameters of the Burr III distribution using a hybrid method of variable neighborhood search and iterated local search algorithms
, Article Applied Mathematics and Computation ; Volume 218, Issue 19 , 2012 , Pages 9664-9675 ; 00963003 (ISSN) ; Abbasi, B ; Niaki, S. T. A ; Abdi, M ; Sharif University of Technology
2012
Abstract
The Burr III distribution properly approximates many familiar distributions such as Normal, Lognormal, Gamma, Weibull, and Exponential distributions. It plays an important role in reliability engineering, statistical quality control, and risk analysis models. The Burr III distribution has four parameters known as location, scale, and two shape parameters. The estimation process of these parameters is controversial. Although the maximum likelihood estimation (MLE) is understood as a straightforward method in parameters estimation, using MLE to estimate the Burr III parameters leads to maximize a complicated function with four unknown variables, where using a conventional optimization such as...
Novel adaptive Kalman filtering and fuzzy track fusion approach for real time applications
, Article 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, Singapore, 3 June 2008 through 5 June 2008 ; 2008 , Pages 120-125 ; 9781424417186 (ISBN) ; Sadati, N ; Sharif University of Technology
2008
Abstract
The track fusion combines individual tracks formed by different sensors. Tracks are usually obtained by Kalman Filter (KF), since it is suitable for real-time application. The KF is an optimal linear estimator when the measurement noise has a Gaussian distribution with known covariance. However, in practice, some of the sensors do not have these properties, and the traditional KF is not an optimal estimator. In this paper, a novel adaptive Kalman filter (NAKF) is proposed. In this approach, the measurement noise covariance is adjusted by using an introduced simple mathematical function of one variable, called the degree of matching (DoM), where it is defined on the basis of covariance...