A Line-Surface Integrated Algorithm for Underwater Terrain Matching

The current underwater terrain surface matching algorithm,which uses Hu moment as the similarity index,cannot gain accurate location due to the algorithm’s disadvantage in detecting slight differences.To solve this problem,a line-surface integrated terrain matching algorithm is presented.First,the similarity evaluation method of the traditional Terrain Contour Matching(TERCOM)algorithm is improved,and the strategy used to select the matching regions is developed.Then,a surface matching algorithm based on the geometric similarity is established to determine the optimum match between the reference maps and the actual measured terrains.Finally,a means of“line matching algorithm”and“surface matching algorithm”integration is proposed based on a fixed threshold.The experimental results show that the proposed algorithm can obtain a more accurate location and has greater robustness than that of the surface underwater matching algorithm based on Hu moment.

Terrain matching localization for hybrid underwater vehicle in the Challenger Deep of the Mariana Trench

The maximum ocean depth so far reported is about 11000 m,and is located in the Mariana Trench in the Western Pacific Ocean.The hybrid unmanned underwater vehicle,Haidou,is developed to perform scientific survey at the deepest parts of the Earth oceans.For vehicles working at the full-ocean depth,acoustic positioning is the most effective and popular method.The 11000 m class acoustic positioning system is relatively massive and complex,and it requires specialized research vessels equipped with compatible acoustic instruments.As a compact testbed platform,it is impractical for Haidou to carry an LBL/USBL beacon with its large volume and weight.During the descent to about 11000 m,horizontal drift could not be eliminated because of the hydrodynamics and uncertain ocean currents in the sea trials.The maximum depth recorded by Haidou is 10905 m,and determining the precise location of the deepest point is challenging.With the bathymetric map produced by a multibeam sonar,the terrain contour matching(TERCOM)method is adopted for terrain matching localization.TERCOM is stable in providing an accurate position because of its insensitivity to the initial position errors.The final matching results show the best estimate of location in the reference terrain map.

Underwater Terrain Positioning Method Based on Least Squares Estimation for AUV

To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation（LSE） is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.

Preliminary Pointing Bias Calibration of ZY3-03 Laser Altimeter

ZiYuan3-03(ZY3-03)satellite was launched on July 25,2020,equipped with China’s second-generation laser altimeter for earth observation.In order to preliminarily evaluate the in-orbit performance of the ZY3-03 laser altimeter,the pointing bias calibration based on terrain matching method was adopted.Three tracks of laser data were employed for the ZY3-03 laser altimeter calibration test.Three groups of pointing parameters were obtained respectively,and the mean value of pointing is considered as the optimal calibration result.After calibration,ZY3-03 laser pointing accuracy is greatly improved by the method,and its pointing accuracy is approximately 12.7 arcsec.The first-track laser data on the Black Sea surface is used to evaluate the relative elevation accuracy of ZY3-03 laser altimeter after pointing bias calibration,which is improved from 0.33 m to 0.19 m after calibration.Meanwhile,the absolute elevation accuracy of ZY3-03 laser altimeter after pointing bias calibration is evaluated by the Ground Control Points(GCPs)measured by RTK(Real-Time Kinematic),which is better than 0.5 m in the flat terrain.

Simulation research on a minimum root-mean-square error rotation-fitting algorithm for gravity matching navigation

Gravity/inertial combination navigation is a leading issue in realizing passive navigation onboard a submarine. A new rotation-fitting gravity matching algorithm, based on the Terrain Contour Matching (TERCOM) algorithm, is proposed in this paper. The algorithm is based on the principle of least mean-square-error criterion, and searches for a certain matched trajectory that runs parallel to a trace indicated by an inertial navigation system on a gravity base map. A rotation is then made clockwise or counterclockwise through a certain angle around the matched trajectory to look for an optimal matched trajectory within a certain angle span range, and through weighted fitting with another eight suboptimal matched trajectories, the endpoint of the fitted trajectory is considered the optimal matched position. In analysis of the algorithm reliability and matching error, the results from simulation indicate that the optimal position can be obtained effectively in real time, and the positioning accuracy improves by 35% and up to 1.05 nautical miles using the proposed algorithm compared with using the widely employed TERCOM and SITAN methods. Current gravity-aided navigation can benefit from implementation of this new algorithm in terms of better reliability and positioning accuracy.

Vision navigation for aircrafts based on 3D reconstruction from real-time image sequences

In this paper,we propose a novel vision navigation method based on three-dimensional(3D)reconstruction from real-time image sequences.It adapts 3D reconstruction and terrain matching to establish the correspondence between image points and3D space points and the terrain reference(by using a digital elevation map(DEM)).An adaptive weighted orthogonal iterative pose estimation method is employed to calculate the position and attitude angle of the aircraft.Synthesized and real experiments show that the proposed method is capable of providing accurate navigation parameters for a long-endurance flight without using a global positioning system or an inertial navigation system(INS).Moreover,it can be combined with an INS to achieve an improved navigation result.