Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

An Innovative Approach to More Reliable and Automated Target Characterisation Studies for Underwater Maritime Survelliance


Affiliations
1 Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India
     

   Subscribe/Renew Journal


Target Motion Analysis (TMA) using conventional passive bearing together with frequency measurements is explored. This approach offers one tactical advantage over the classical bearings-only TMA. It makes the ownship maneuver superfluous. In this paper, TMA is carried out using Unscented Kalman Filter (UKF). Inclusion of range, course and speed parameterization is proposed in UKF target state vector to obtain the convergence of the solution fast. Finally the results of various scenarios in Monte-Carlo simulation are presented. This method can be easily adopted for underwater passive target tracking application.


Keywords

Sonar, Estimation, Target Tracking, Ownship, Range, Course, Speed.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 220

PDF Views: 2




  • An Innovative Approach to More Reliable and Automated Target Characterisation Studies for Underwater Maritime Survelliance

Abstract Views: 220  |  PDF Views: 2

Authors

A. Jawahar
Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India
Rajya Lakshmi
Department of Electrical and Electronics Engineering, Sanketika Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India

Abstract


Target Motion Analysis (TMA) using conventional passive bearing together with frequency measurements is explored. This approach offers one tactical advantage over the classical bearings-only TMA. It makes the ownship maneuver superfluous. In this paper, TMA is carried out using Unscented Kalman Filter (UKF). Inclusion of range, course and speed parameterization is proposed in UKF target state vector to obtain the convergence of the solution fast. Finally the results of various scenarios in Monte-Carlo simulation are presented. This method can be easily adopted for underwater passive target tracking application.


Keywords


Sonar, Estimation, Target Tracking, Ownship, Range, Course, Speed.