Indian Journal of Science and Technology

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Underwater Passive Target Tracking in Constrained Environment


Affiliations
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, India
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, India
 

In underwater scenario, observer manoeuvre is required to find out target motion parameters in bearings only passive target tracking. Sometimes, due to tactical constraints, observer is not able to carry out manoeuvre. In this paper, it is shown that target motion parameters can be obtained in such situation, if the knowledge of any one of the target motion parameters is available. There are other practical problems like spurious bearings are generated by sonar, etc. In addition, auto tracking fails often and some bearings will be missed. Pseudo Linear Kalman Filter is made flexible to address these practical problems.

Keywords

Constrained Environment, Direction of Arrival Estimation, Kalman Filtering, Monte Carlo Simulation, Passive Target Tracking, Target Detection
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  • Underwater Passive Target Tracking in Constrained Environment

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Authors

Jawahar Annabattula
School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, India
S. Koteswara Rao
School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, India
A. Sampath Dakshina Murthy
Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, India
K. S. Srikanth
School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, India
Rudra Pratap Das
Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, India

Abstract


In underwater scenario, observer manoeuvre is required to find out target motion parameters in bearings only passive target tracking. Sometimes, due to tactical constraints, observer is not able to carry out manoeuvre. In this paper, it is shown that target motion parameters can be obtained in such situation, if the knowledge of any one of the target motion parameters is available. There are other practical problems like spurious bearings are generated by sonar, etc. In addition, auto tracking fails often and some bearings will be missed. Pseudo Linear Kalman Filter is made flexible to address these practical problems.

Keywords


Constrained Environment, Direction of Arrival Estimation, Kalman Filtering, Monte Carlo Simulation, Passive Target Tracking, Target Detection



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i35%2F124852