Robust Two-Stage Filtering for INS/Gravity Matching Passive Integrated Navigation Systems

Luo, Kaixin; Cai, Shaokun; Yu, Ruihang; Cao, Juliang; Guo, Yan

doi:10.1109/jsen.2021.3138793

Cited by 7 publications

(3 citation statements)

References 28 publications

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“…The shortcomings mentioned above limit the GNSS application used for AUV in the deep sea environment. At present, traditional underwater navigation could be divided into five types, namely INS [2,3], UAPS [4,5], the underwater visual navigation system (UVNS) [6], the geophysical navigation system (GNS) [7][8][9], and the underwater integrated navigation system [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…GNS realizes AUV positioning by measuring geophysical parameters in advance, matching with prior environmental map on the premise of sufficient changes in spatial distribution. GNS can be further divided into terrain assisted navigation [7], geomagnetic navigation [8], and gravity field navigation [9]. Terrain assisted navigation often use depth sounders.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Methods to Estimate Positioning and Time Offset with Underwater Acoustic Positioning System

Lv,

Ou,

Liu

et al. 2024

Frontiers in Artificial Intelligence and Applications

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The positioning of autonomous underwater vehicle (AUV) is the core technology of ocean engineering. Due to the positioning error of inertial navigation system (INS) accumulate with time, underwater acoustic positioning system (UAPS) could be used. In fact, INS/UAPS integrated navigation system is widely-used nowadays. AUV could estimate its positioning coordinates in time by receiving and processing the acoustic signals from UAPS. Few studies have focused on how to estimate the time offset of UAPS. In this paper, two method to obtain the AUV’s position and time offset are supplied based on synchronous spherical intersection model. The closed-form solution and Newton iteration could both obtain the AUV’s position and time offset. However, the positioning accuracy of closed-form solution is generally poor and cannot meet the requirements of underwater operations. Though Newton iteration method could be used to supply high positioning accuracy and time offset with UAPS, it occupies more time. Through simulation experiments by MATLAB, it could be proved that the Newton iteration method has higher positioning accuracy and accurate time offset than closed-form solution, but it takes more time to calculate.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methods to Estimate Positioning and Time Offset with Underwater Acoustic Positioning System

Lv,

Ou,

Liu

et al. 2024

Frontiers in Artificial Intelligence and Applications

View full text Add to dashboard Cite

show abstract

“…However, these individual methods have certain limitations, and therefore many scholars have proposed ways to combine different types of methods for gravity navigation. For example, Luo [21] proposed a combined the Extended Kalman Filter (EKF) and the PF that completes the gravity matching process in the first layer of filtering and ensures real-time performance in the second layer. Han [22,23] combined the ICCP with the PF and performed an iterative isochronous transformation based on the PF matching results through a two-step calculation.…”

Section: Introductionmentioning

confidence: 99%

Parallel Multiple Methods with Adaptative Decision Making for Gravity-Aided Navigation

Gao,

Cai

2023

JMSE

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Gravity-aided navigation is an effective navigation method for underwater vehicles. However, the distribution of the gravity field may affect the measurement errors of gravity anomalies and the precision of gravity-aided navigation. In this paper, the upper and lower thresholds of the gravity field standard deviation are computed by the statistical properties of the local gravity field to classify each grid in the gravity map into different levels. A parallel multiple methods with adaptive decision making (PMMADM) for gravity-aided navigation is proposed which incorporates the gravity anomaly measurements, particle filtering, and maximum correlation method into the observation equation of the extended Kalman filter. The algorithm autonomously selects the observation variables in the filter by combining the gravity field standard deviation at the current position of the carrier with a decision tree. This approach can combine the characteristics of different gravity matching algorithms, reduce the impact of random noise in the measurements, and improve the positioning accuracy of gravity-aided navigation. Physical simulation experiments demonstrated that the proposed gravity matching algorithm achieves the high navigation accuracy and long-term stability in different gravity fields, and the mean value of positioning error is 620.72 m.

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Performance analysis of oceanographic research vessel precise point positioning based on BDS/GNSS RTK receivers

Xiao

Liu

et al. 2023

Measurement

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Robust Two-Stage Filtering for INS/Gravity Matching Passive Integrated Navigation Systems

Cited by 7 publications

References 28 publications

Methods to Estimate Positioning and Time Offset with Underwater Acoustic Positioning System

Methods to Estimate Positioning and Time Offset with Underwater Acoustic Positioning System

Parallel Multiple Methods with Adaptative Decision Making for Gravity-Aided Navigation

Performance analysis of oceanographic research vessel precise point positioning based on BDS/GNSS RTK receivers

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