TY - JOUR
T1 - 基于分割嵌套三角剖分的重力场适配区选取算法
AU - Wang, Yu
AU - Xiao, Xuan
AU - Liu, Jining
AU - Deng, Zhihong
AU - Wang, Bo
N1 - Publisher Copyright:
© 2022, Editorial Department of Journal of Chinese Inertial Technology. All right reserved.
PY - 2022/2
Y1 - 2022/2
N2 - The selection algorithm of gravity field adaptation area is one of the key technologies of underwater gravity positioning system, which directly affects the positioning accuracy and matching rate of gravity matching algorithm. A gravity field adaptation region selection algorithm based on segmented nested triangulation is proposed. Firstly, the traditional grid information of gravity field is transformed into three-dimensional elevation information by using Mercator projection and gravity anomaly spatial correction. Then, using the idea of segmentation and nesting, the optimal triangle is continuously segmented from the minimum annular domain of gravity field, so as to form the triangular network of gravity field. For each small triangle in the network, the slope, aspect, fluctuation and roughness are selected as the local geometric characteristics of the gravity field, and the gravity field is divided into strong fit region, weak fit region and non-fit region by k-means clustering algorithm. The experimental results of adaptability evaluation show that in the strong adaptation area selected by the proposed adaptation area selection algorithm, the gravity matching positioning accuracy is equivalent to the grid resolution of the gravity field background map, indicating the feasibility of using segmented nested triangulation to select the gravity field adaptation area.
AB - The selection algorithm of gravity field adaptation area is one of the key technologies of underwater gravity positioning system, which directly affects the positioning accuracy and matching rate of gravity matching algorithm. A gravity field adaptation region selection algorithm based on segmented nested triangulation is proposed. Firstly, the traditional grid information of gravity field is transformed into three-dimensional elevation information by using Mercator projection and gravity anomaly spatial correction. Then, using the idea of segmentation and nesting, the optimal triangle is continuously segmented from the minimum annular domain of gravity field, so as to form the triangular network of gravity field. For each small triangle in the network, the slope, aspect, fluctuation and roughness are selected as the local geometric characteristics of the gravity field, and the gravity field is divided into strong fit region, weak fit region and non-fit region by k-means clustering algorithm. The experimental results of adaptability evaluation show that in the strong adaptation area selected by the proposed adaptation area selection algorithm, the gravity matching positioning accuracy is equivalent to the grid resolution of the gravity field background map, indicating the feasibility of using segmented nested triangulation to select the gravity field adaptation area.
KW - Computational geometry
KW - Gravity matching positioning
KW - Matching area selection
KW - Nesting ring domain
KW - Triangulation
UR - http://www.scopus.com/inward/record.url?scp=85130068837&partnerID=8YFLogxK
U2 - 10.13695/j.cnki.12-1222/o3.2022.01.008
DO - 10.13695/j.cnki.12-1222/o3.2022.01.008
M3 - 文章
AN - SCOPUS:85130068837
SN - 1005-6734
VL - 30
SP - 51
EP - 57
JO - Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology
JF - Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology
IS - 1
ER -