Multi-Sensor Measurements Fusion for Passive Target Tracking in Underwater

The pivot goal of estimation algorithms is to generate information with a quality higher than that of raw measurements available and to extract the information that can be obtained indirectly from the available measurements. To fulfill this aim, the measurements from multiple sensors are combined to get a more accurate and reliable estimate of the target. In this research work, measurements from five multiple sensors are combined to get different motion parameters of the desired target. The sub-optimal filter, Unscented Kalman filter is considered for the performance analysis of the algorithm. The simulation is carried in MATLAB software using the Monte-Carlo simulation method for better analysis of the results.