Navigation postprocessing

When discussing navigation in autonomous operations, it is important to distinguish between performance in real time and after post-processing. The real-time performance obviously determines where the AUV actually collects its data. Depending on the application, (e.g. when creating bathymetric maps or during mine reconnaissance) it may be desirable to enhance the navigation precision further in post-processing. This is standard procedure for the HUGIN AUVs, where the post-processing is carried out using NavLab (Gade, 2004). Post-processing will improve the estimation accuracy as well as the integrity. The increased accuracy is due to the use of smoothing, which is an optimal estimation technique that utilizes both past and future measurements. Smoothing is especially effective when position updates are scarce, which is the case with GPS surface fixes, terrain navigation with few reference areas, and scattered underwater transponders. The effect of navigation postprocessing when running a 15 km straight-line trajectory with GPS fix at the end is shown in Fig. 9. The effect is smaller, but still significant, when running a lawnmower pattern. Another important feature of navigation post-processing is increased navigational integrity and increased ability to recover faulty data sets. For one thing, wild point filtering can be more reliable when both past and future measurements can be considered. The smoothing algorithm is in general more robust against degraded sensor performance, hence efficiently improving the final navigation accuracy and reliability in such cases.

Est error in naveq position and std (<5nL + 6z )

Est error in naveq position and std (<5nL + 6z )

seconds

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