عنوان	Noise Covariance Matrix Estimation in Target Tracking in Three Approaches: n-step Prediction, Kalman Gain Covariance and Gamma-distribution of Noise Statistics
نوع پژوهش	مقاله چاپ‌شده در مجله
کلیدواژه‌ها	Noise Covariance Matrix Estimation, Target Tracking, n-step Prediction, Kalman Gain Covariance, Gamma-distribution
چکیده	Noise parameters in many target tracking projects are assumed as known factors which is a main challenge because of uncertainty in measurement and statemodel noise. Thus, many papers are focused on the accurate estimation of noise statistics. This paper is concentrated on this subject where it is tried to present three simple efficient methods in this regard. Estimation using n-step prediction, applying Kalman filter covariance and using Gamma distribution for noise parameters are the main concepts of the three proposed methods. Simulation results show the efficiency of all methods compared to other methods in the literature where the Gamma-distributionbased method is the most efficient work among other suggested ones in term of estimation error.
پژوهشگران	صهباالسادات رجامند (نفر اول)، عبدالحمید زاهدی (نفر دوم)