A new method of target tracking by EKF using bearing and elevation measurements for underwater environment

Underwater moving object detection/tracking is critical in various applications such as exploration of natural undersea resources, acquiring of accurate scientific data to maintain regular surveillance of missions, navigation and tactical surveillance. Real time object detection/tracking which tends to obstacle avoidance is possible with an autonomous underwater vehicle (AUV) fitted with sensor(sonar). To bring these applications into effective use, there is a need to evaluate various solutions for the safe navigation of AUV in the significant underwater environment. Convergence time becomes a problem and plays an increasingly important role in safe navigation of AUV applications. To achieve this, several methods, i.e. Kalman Filter (KF), Extended Kalman Filter (EKF) and Particle Filter (PF) have been investigated, although all these methods have their own limitations. In this paper, a new method has been developed wherein tracking algorithm using EKF has been extended to the Bearing and Elevation only Tracking (BEOT) method. By using Monte Carlo approach, the performance of this algorithm has been analyzed. Consequently, the time of convergence has been calculated and accordingly the results have been plotted.