Object sensing, tracking and reconstructing using Extended Kalman Filter algorithm

In today's modern world 3D modeling is used in numerous practical applications. Surveillance, Traffic Control, Driver Assistance & Biomedical imaging are few to name. Higher accuracy is vital in each application. Thus accuracy enhancing techniques are used in each case. Among many other techniques Extended Kalman Filter (EKF) is best known for its recursive least-mean square algorithm for error elimination and optimum estimation. Yet detecting and tracking of objects in an unknown territory using a mobile platform remains a challenge. The purpose of this paper is to provide a practical method for detecting, tracking and reconstructing of objects in an unknown territory with a higher accuracy using EKF.