Perpustakaan Digital ITB

Long-term oceanographic mooring operations require reliable underwater acoustic positioning to maintain spatial certainty during deployment and recovery. In deep-water mooring, the Acoustic Release Unit (ARU) connects the recoverable instrument package to the seabed anchor and enables acoustic release during recovery. However, commercially available ARU-positioning tools do not always provide transparent calculation procedures or quantified positioning uncertainty. This study develops a Python-based trilateration framework to determine the three-dimensional position of an ARU using post-processed acoustic range observations and ship-based coordinates from BRIN mooring deployment and recovery reports. The framework integrates coordinate transformation, nonlinear least-squares adjustment, residual analysis, positional uncertainty estimation, visualization, reporting, and Estimated Time to Surface calculation. Position quality is evaluated using two complementary approaches. The operational assessment compares the horizontal residual RMSE with a propagated horizontal tolerance derived from the IMCA 0.5% slant-range benchmark, while statistical consistency is evaluated using a chi-square test based on the combined uncertainties of acoustic ranging, DGNSS positioning, and transducer offset. The results show that the framework successfully produces latitude, longitude, and depth estimates together with residual diagnostics, positional standard deviation, operational position status, statistical consistency results, and recovery-time estimates. Three-point observations can produce coordinate solutions but cannot support the chi-square test because they have zero degrees of freedom. Additional observations provide redundancy and allow a more meaningful assessment of residuals and position quality. Overall, the framework provides an integrated and repeatable approach for ARU positioning and recovery planning in deep-water mooring operations.