TY - JOUR
T1 - Wavelet Transform Based Morphological Matching Area Selection for Underwater Gravity Gradient-Aided Navigation
AU - Wang, Bo
AU - Li, Tianjiao
AU - Deng, Zhihong
AU - Fu, Mengyin
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Selection of gravity gradient matching area is one of the key techniques for underwater gravity gradient-Aided navigation. The existing matching area selection methods ignore the high-resolution characteristics of the gravity gradient, resulting in inaccurate selection. Therefore, a frequency domain matching area selection method based on the high-resolution characteristics of the gravity gradient is proposed. The high-frequency information of gravity gradient reference map is extracted by wavelet transform, and the gravity gradient wavelet transform model is established. The morphological image texture segmentation method is proposed to extract the densely textured areas from the gravity gradient high-frequency image as the matching areas. Simulation results show that the proposed method can obtain the texture density, texture amplitude and texture direction in the matching area while obtaining the matching area with a matching rate higher than 90%. Compared with the existing methods, the matching areas obtained by the proposed method are more accurate and the calculation burden is reduced to less than 10% of the existing algorithm. Moreover, the more the trajectory is perpendicular to the texture inside the matching area, the higher is the matching rate.
AB - Selection of gravity gradient matching area is one of the key techniques for underwater gravity gradient-Aided navigation. The existing matching area selection methods ignore the high-resolution characteristics of the gravity gradient, resulting in inaccurate selection. Therefore, a frequency domain matching area selection method based on the high-resolution characteristics of the gravity gradient is proposed. The high-frequency information of gravity gradient reference map is extracted by wavelet transform, and the gravity gradient wavelet transform model is established. The morphological image texture segmentation method is proposed to extract the densely textured areas from the gravity gradient high-frequency image as the matching areas. Simulation results show that the proposed method can obtain the texture density, texture amplitude and texture direction in the matching area while obtaining the matching area with a matching rate higher than 90%. Compared with the existing methods, the matching areas obtained by the proposed method are more accurate and the calculation burden is reduced to less than 10% of the existing algorithm. Moreover, the more the trajectory is perpendicular to the texture inside the matching area, the higher is the matching rate.
KW - Gravity gradient-Aided navigation
KW - gravity gradient reference map
KW - image morphology
KW - matching area selection
KW - wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=85141635470&partnerID=8YFLogxK
U2 - 10.1109/TVT.2022.3218998
DO - 10.1109/TVT.2022.3218998
M3 - Article
AN - SCOPUS:85141635470
SN - 0018-9545
VL - 72
SP - 3015
EP - 3024
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 3
ER -