Indian Journal of Science and Technology
Year: 2015, Volume: 8, Issue: 35, Pages: 1-5
Jawahar Annabattula1*, S. Koteswara Rao1 , A. Sampath Dakshina Murthy2 , K. S. Srikanth1 and Rudra Pratap Das2
1 School of Electrical Sciences, KLEF, KL University, Guntur - 522502, Andhra Pradesh, India; [email protected], [email protected]
2 Department of ECE, Vignan’s Institute of Information Technology, Visakhapatnam - 530046, Andhra Pradesh, India; [email protected], [email protected]
Background/Objectives: The modern submarines use mutlitple sensors for tracking multiple targets in sea environment. In general, multiple sensor data can be handled in two ways: measurement fusion and state vector fusion. Methods/ Statistical Analysis: Measurement fusion is not practical for implementation due to various reasons and hence state vector fusion is proposed. Target trackingusing Modified Gain Bearings only Extended Kalman Filter in generic two-dimensional platform is carried out in each channel. Findings: In this approach, a state vector and its corresponding covariance matrix are extracted from the sensor measurements by an estimator equipped on each sensor. The output of each channel is transported via a data link in to order to be reach the fusion center. Applications/Improvements: A composite target state vector is obtained by performing track-to-track correlation and fusion at the fusion center.Monte-Carlo simulation is carried outand the results are presented for a typical scenario.
Keywords: Estimation, Fusion, Kalman Filter, Simulation, Tracking
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