Fast Extraction of Local Underwater Terrain Features for Underwater Terrain-Aided Navigation

Abstract

Terrain matching accuracy and real-time performance are affected by local underwater terrain features and structure of matching surface. To solve the extraction problem of local terrain features for underwater terrain-aided navigation (UTAN), real-time data model and selection method of beams are proposed. Then, an improved structure of terrain storage is constructed, and a fast interpolation strategy based on index is proposed, which can greatly improve the terrain interpolation–reconstruction speed. Finally, for the influences of tide, an elimination method of reference depth deviation is proposed, which can reduce the reference depth errors caused by tidal changes. As the simulation test shows, the proposed method can meet the requirements of real-time performance and effectiveness. Furthermore, the extraction time is considerably reduced, which makes the method suitable for the extraction of local terrain features for UTAN.

Keywords

Underwater terrain modeling / Beam selection / Mixing resolution / Terrain storage model / Index extraction

References

[1] Anonsen KB, Hagen OK (2010) An analysis of real-time terrain aided navigation results from HUGIN AUV. Oceans 2010, Seattle, 1–9. https://doi.org/10.1109/OCEANS.2010.5664076

[2] Bergman N, Ljung L (1997) Point-mass filter and Cramer-Rao bound for terrain-aided navigation. IEEE Conference on Decision and Control, San Diego, 565–570. https://doi.org/10.1109/CDC.1997.650690

[3] Carlstrom J, Nygren I (2005). Terrain navigation of the Swedish AUV62f vehicle. 14th International Symposium on Unmanned Untethered Submersible Technology, Durham, 1–10. https://doi.org/10.1109/UUST.2005.5664076

[4] Carreno S, Wilson P, Ridao P, Petillot Y (2010) A survey on terrain based navigation for AUVs. Oceans 2010, Seattle, 1–7. https://doi.org/10.1109/OCEANS.2010.5664372

[5] Chen PY, Li Y, Su YM, Chen XL, Jiang YQ. Underwater terrain positioning method based on least squares estimation for AUV. China Ocean Eng, 2015, 29(6): 859-874

[6] Eleftherakis D, Snellen M, Amiri-Simkooei A, Simons DG, Siemes K. Observations regarding coarse sediment classification based on multi-beam echo-sounder’s backscatter strength and depth residuals in Dutch rivers. J Acoust Soc Am, 2014, 135(6): 3305-3315

[7] Gao JY, Jin XL, Wu ZY. Construction of submarine DTM from raw multibeam data. Mar Sci Bull, 2003, 22(1): 30-38 (in Chinese)

[8] GeoAcoustics Limited GeoSwath Plus operation manual, 2007, London: GeoAcoustics Limited, 1-25

[9] Hagen OK, Anonsen KB. Using terrain navigation to improve marine vessel navigation systems. Mar Technol Soc J, 2014, 48(2): 45-58

[10] Lu YQ (2003) Study of the real-time rendering for large-scale terrain dataset. PhD thesis, Zhejiang University, Hangzhou, 1–6 (in Chinese)

[11] Meduna DK, Rock SM, McEwen RS (2010) Closed-loop terrain relative navigation for AUVs with non-inertial grade navigation sensors. Autonomous Underwater Vehicles (AUV), 2010 IEEE/OES, Monterey, 1-8. https://doi.org/10.1109/AUV.2010.5779659

[12] Nygren I, Jansson M. Terrain navigation for underwater vehicles using the correlator method. IEEE J Ocean Eng, 2004, 29(3): 906-915

[13] Peng DD, Zhou T, Li HS, Zhang WY (2016) Terrain-aided navigation for underwater vehicles using maximum likelihood method. 2016 IEEE/OES China Ocean Acoustics Symposium, Harbin, 1–6. https://doi.org/10.1109/COA.2016.7535750

[14] Su YM, Zhao JX, Cao J, Zhang G. Dynamics modeling and simulation of autonomous underwater vehicles with appendages. J Mar Sci Appl, 2013, 12(1): 45-51

[15] Sun L, Liu YC, Li MS. Technique on building DEM of bathymetry using multibeam data. Hydrographic Surveying and Charting, 2009, 29(1): 39-41 (in Chinese)

[16] Tan B, Xu Q, Ma DY. Real-time multi-resolution terrain rendering using restricted quadtree. Journal of Computer-aided Design & Computer Craphics, 2003, 15(3): 270-276 (in Chinese)

[17] Tian FM (2007) Research on prior map data processing based terrain-aided navigation methods for underwater vehicles. Master thesis, Harbin Engineering University, Harbin, 10–20 (in Chinese)

[18] Wang YK, Zhu YL (2012) Terrain three-dimensional visualization based on dynamic LOD quadtree arithmetic. IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, Beijing, 1–5. https://doi.org/10.1109/ICADE.2012.6330090

[19] Zhu Q, Li DR. Error analysis and processing of multibeam soundings. Journal of Wuhan Technical University of Surveying and Mapping, 1998, 23(1): 1-4 (in Chinese)