The Fusion of Bearing and Frequency Measurements from Multi-sensor Arrays for Underwater Target Tracking

Estimation is the process of generating information that is not directly available from raw measurements to obtain different target motion parameters. To fulfil this aim, different measurements from various sensors are fused to obtain a more accurate and reliable estimate of the target state. This task is more complex when the sensors operate in passive mode. In this research work, passive measurements i.e., bearings from an array mounted on the hull (HMA) and array sensors towed behind the observer along with doppler shifted frequency measurements from the towed array are fused to obtain kinematic parameters of the desired target. The sub-optimal filter, Unscented Kalman filter is considered for the performance analysis. The results are compared to that of simple doppler-bearing tracking using measurements from HMA. The simulation is carried in MATLAB software using the Monte-Carlo simulation method for better analysis of the results.