A SINS Aided Correct Method for USBL Range Based on Maximum Correntropy Criterion Adaptive Filter

The integrated navigation system for strap-down inertial navigation system and ultrashort baseline (SINS/USBL) is one of the main approaches to realize the high-precision navigation and positioning of autonomous underwater vehicle (AUV). The relatively low frequency with seconds and the noise caused...

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Veröffentlicht in:IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-13
Hauptverfasser: Liu, Shede, Zhang, Tao, Zhang, Liang
Format: Artikel
Sprache:eng
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Zusammenfassung:The integrated navigation system for strap-down inertial navigation system and ultrashort baseline (SINS/USBL) is one of the main approaches to realize the high-precision navigation and positioning of autonomous underwater vehicle (AUV). The relatively low frequency with seconds and the noise caused by the complex environment for USBL measurements have an obviously influence on the accuracy of positioning system. To solve the above problems, a correct method for USBL range measurement and a robust filter based on maximum correntropy criterion (MCC) are proposed in this article. First, the influence of motion effect on the range calculation results in the process of USBL transmission and reception is analyzed. Then, a simple correction method based on short-term high-precision characteristics of SINS is proposed. The short-term high-precision attitude, velocity, and position information of SINS in the process of USBL transmission and reception is used to correct the range error caused by motion effect. Finally, an adaptive filter based on MCC and dynamic model error adaptive factor is proposed to suppress the influence of outliers on positioning accuracy. The simulation and Yangzi River experiments are conducted to evaluate the feasibility of the proposed algorithm. The results shows that the proposed range correction method has a good correction effect on range error between sending and receiving epoch, and the proposed algorithm has better ability to suppress outliers.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2022.3162279