Strapdown INS/GPS Integrated Navigation Using Geometric Algebra

Wu, Dimin; Wang, Zhengzhi

doi:10.1007/s00006-013-0395-3

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…Such a system utilises specific forces (accelerometer output) and angular rates (gyro output) in three dimensions. Nonetheless, considering the intrinsic bias errors of gyros and accelerometers, INS is usually unable to perform navigation tasks independently in the presence of such gradually increasing errors (Wu and Wang, 2013;Ning et al, 2015;Shabani and Gholami, 2016). Hence, INS should adopt auxiliary sensors in order to provide the required measurements for improving navigation performance.…”

Section: Introductionmentioning

confidence: 99%

“…In ocean navigation, since satellite signals are repeatedly attenuated, and GPS signals are unavailable, it is necessary to adopt other auxiliary sensors. For underwater navigation, Doppler velocity log (DVL) measures velocity with respect to the seafloor based on the Doppler effect, with high precision (Wu et al., 2019). The emission of acoustic waves by wave-absorbing materials, or large roll and pitch caused by angular manoeuvres, are causes of malfunction of this sensor.…”

Section: Introductionmentioning

confidence: 99%

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New fault detection and fault-tolerant scheme for Doppler velocity logger outage in ocean navigation systems

Hashemi

Shami

2021

J. Navigation

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The inertial navigation system/Doppler velocity logger (INS/DVL) plays an important role in ocean navigation. Any DVL malfunction poses serious risks to navigation. A precise detection system is required to detect the initial moments of DVL signal malfunctions; moreover, with loss of DVL, a fault-tolerant scheme (FTS) is necessary for DVL signal reconstruction. In this paper, an evolutionary knowledge-based method, namely improved evolutionary TS-fuzzy (I-eTS), is adopted to build an artificial intelligence (AI)-based pseudo DVL to deal with long-term outage of DVL. By employing Gaussian process regression (GPR) models for fault detection, a new FTS is constructed. To verify the effectiveness of the new fault detection and fault tolerance system, navigation data is gathered by a test setup and algorithms are performed in the laboratory. In the tests, it is demonstrated that the proposed FTS leads to rapid detection of both gradual and abrupt faults, which leads to less interaction between fault detection and FTS.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New fault detection and fault-tolerant scheme for Doppler velocity logger outage in ocean navigation systems

Hashemi

Shami

2021

J. Navigation

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“…The IMU is composed of gyroscopes and accelerometers to measure the angular rates and the specific forces respectively. The navigation errors of the SINS increase with time due to the inherent bias errors of gyroscopes and accelerometers [3][4][5]. Therefore, in order to improve the navigation performance, it is necessary to introduce auxiliary sensors to limit the error growth of the SINS.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Approach to Deal with DVL Malfunctions for Underwater Integrated Navigation Systems

Zhu

Cheng

et al. 2017

Applied Sciences

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Abstract:As a common device for underwater integrated navigation systems, Doppler velocity log (DVL) has the risk of malfunction. To improve the reliability of navigation systems, a hybrid approach is presented to forecast the measurements of the DVL while it malfunctions. The approach employs partial least squares regression (PLSR) coupled with support vector regression (SVR) to build a hybrid predictor. As the current and past calculating velocities of strapdown inertial navigation system (SINS) are taken as the predictor's inputs, PLSR is applied to cope with the situation where there exists intense relativity among independent variables. Since PLSR is a linear regression, SVR is used to predict the residual components of the PLSR prediction to improve the accuracy. When the DVL works well, the hybrid predictor is trained online as a backup, whereas during malfunctions, the predictor offers the estimation of the DVL measurements for information fusion. The performance of the proposed approach is verified with simulations based on SINS/DVL/MCP/pressure sensor (PS) integrated navigation system. The comparison results indicate that the PLSR-SVR hybrid predictor can correctly provide the estimated DVL measurements and effectively extend the tolerance time on DVL malfunctions, thereby improving the navigation accuracy and reliability.

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Geometric foundations for radar signal processing

Sangston

2018

Academic Press Library in Signal Processing, Volume 7

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Strapdown INS/GPS Integrated Navigation Using Geometric Algebra

Cited by 6 publications

References 14 publications

New fault detection and fault-tolerant scheme for Doppler velocity logger outage in ocean navigation systems

New fault detection and fault-tolerant scheme for Doppler velocity logger outage in ocean navigation systems

A Novel Hybrid Approach to Deal with DVL Malfunctions for Underwater Integrated Navigation Systems

Geometric foundations for radar signal processing

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