Pervasive underwater passive target tracking for the computation of standard deviation solution in a 3D environment

Abstract

PurposeNowadays advancement in acoustic technology can be explored with marine assets. The purpose of the paper is pervasive computing underwater target tracking has aroused military and civilian interest as a key component of ocean exploration. While many pervasive techniques are currently found in the literature, there is little published research on the effectiveness of these paradigms in the target tracking context.Design/methodology/approachThe unscented Kalman filter (UKF) provides good results for bearing and elevation angles only tracking. Detailed methodology and mathematical modeling are carried out and used to analyze the performance of the filter based on the Monte Carlo simulation.FindingsDue to the intricacy of maritime surroundings, tracking underwater targets using acoustic signals, without knowing the range parameter is difficult. The intention is to find out the solution in terms of standard deviation in a three-dimensional (3D) space.Originality/valueA new method is found for the acceptance criteria for range, course, speed and pitch based on the standard deviation for bearing and elevation 3D target tracking using the unscented Kalman filter covariance matrix. In the Monte Carlo simulation, several scenarios are used and the results are shown.