A. M. Shahri

Department of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Tehran, Iran

[ 1 ] - Implementation of a Low- Cost Multi- IMU by Using Information Form of a Steady State Kalman Filter

In this paper, a homogenous multi-sensor fusion method is used to estimate the trueangular rate and acceleration with a combination of four low cost (< 10$) MEMS Inertial MeasurementUnits (IMU). An information form of steady state Kalman filter is designed to fuse the output of four lowaccuracy sensors to reduce the noise effect by the square root of the number of sensors. A hardware isimplemen...

[ 2 ] - Generalized Aggregate Uncertainty Measure 2 for Uncertainty Evaluation of a Dezert-Smarandache Theory based Localization Problem

In this paper, Generalized Aggregated Uncertainty measure 2 (GAU2), as a newuncertainty measure, is considered to evaluate uncertainty in a localization problem in which cameras’images are used. The theory that is applied to a hierarchical structure for a decision making to combinecameras’ images is Dezert-Smarandache theory. To evaluate decisions, an analysis of uncertainty isexecuted at every...

[ 3 ] - Uncertainty Measurement for Ultrasonic Sensor Fusion Using Generalized Aggregated Uncertainty Measure 1

In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Unce...

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