Multi-Sensor Submarine Surveillance System using MGBEKF

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.