TY - JOUR
T1 - Resolving Ambiguity Using Fusion Classification for Ultra-short Baseline Positioning Systems
AU - Wang, Yan
AU - Li, Qing
AU - Fu, Jin
AU - Liang, Guolong
N1 - Publisher Copyright:
© 2017, Science Press. All right reserved.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - To solve the phase-difference ambiguity problem in Ultra-Short BaseLine (USBL) underwater acoustic positioning systems, an ambiguity resolution and localization method based on Multiple Classifier Fusion (MCF) is proposed. Firstly, the multiple classifier system is built. Then, ambiguity resolution problem is formulated as classifying and recognizing the ambiguity integer, and Choquet integral is utilized for fusing the results of multiple classifiers. Finally, the category of ambiguity integer is obtained and the target is located. The unambiguous observation condition of the target position is derived. Without constructing an inter-sensor spacing less than half the wavelength, unambiguous aperture of the array is effectively enlarged. Moreover, as statistical characteristics of the observation data are fully utilized, the positioning accuracy approaches the Cramer-Rao bound. Simulation results verify the effectiveness of the proposed method.
AB - To solve the phase-difference ambiguity problem in Ultra-Short BaseLine (USBL) underwater acoustic positioning systems, an ambiguity resolution and localization method based on Multiple Classifier Fusion (MCF) is proposed. Firstly, the multiple classifier system is built. Then, ambiguity resolution problem is formulated as classifying and recognizing the ambiguity integer, and Choquet integral is utilized for fusing the results of multiple classifiers. Finally, the category of ambiguity integer is obtained and the target is located. The unambiguous observation condition of the target position is derived. Without constructing an inter-sensor spacing less than half the wavelength, unambiguous aperture of the array is effectively enlarged. Moreover, as statistical characteristics of the observation data are fully utilized, the positioning accuracy approaches the Cramer-Rao bound. Simulation results verify the effectiveness of the proposed method.
KW - Fuzzy integral
KW - Multiple Classifier Fusion (MCF)
KW - Phase-difference ambiguity
KW - Ultra-Short BaseLine (USBL) positioning
UR - https://www.scopus.com/pages/publications/85028423737
U2 - 10.11999/JEIT160825
DO - 10.11999/JEIT160825
M3 - 文章
AN - SCOPUS:85028423737
SN - 1009-5896
VL - 39
SP - 1348
EP - 1354
JO - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
JF - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
IS - 6
ER -