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Paper proposes a simultaneous localisation and mapping (SLAM) scheme which is applicable to small military unmanned underwater vehicles (UUVs). The SLAM is a process which enables concurrent estimation of the position of UUV and landmarks in the environment through which the vehicle is passing. An unscented Kalman filter (UKF) is utilised to develop a SLAM suitable to nonlinear motion of UUV. A range sonar is used as a sensor to collect the relative position information of the landmark in the environment in which the UUV is navigating. The proposed SLAM scheme was validated through towing tank experiments about two degrees of freedom motion with UUV motion simulator and real range sonar system for small UUV. The results of these experiments showed that proposed SLAM scheme is capable of estimating the position of the UUV and the surrounding objects under real underwater environment.Defence Science Journal, 2012, 62(4), pp.223-227, DOI:http://dx.doi.org/10.14429/dsj.62.1002

In an active towed array sonar, it is important to find the optimal operation depth. Generally, the optimal depth can be chosen via numerical simulations for all sonar depths and this imposes great burdens of time and cost.In this paper, an efficient approach is proposed to find the optimal depth using the optimisation technique. First, the sonar performance function is newly defined as a measure of how well the active sonar might perform. This function depends on the properties of the ocean environment and the positions of sonar and underwater target. Then, the simulated annealing to find an optimal solution for maximising sonar performance is used. The optimised depth agrees well with the depth obtained from direct searching for all depths of source and receiver combinations, but its computational time is largely reduced.