Magnetic compass fault detection method for GPS/INS/magnetic compass integrated navigation systems

Park, Sul Gee; Jeong, Ho Cheol; Kim, Jeong Won; Hwang, Dong-Hwan; Lee, Sang Jeong

doi:10.1007/s12555-011-0209-0

Cited by 25 publications

(14 citation statements)

References 7 publications

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“…But in early occurrence phase of gradual failures, resid ual chi -sq uare test uses co rrup ted measurements for fault detection, leading to an insensitivity to gradual faults. Thereby some improved methods [20][21][22][23][24] are proposed. The chi-square test with two state propagators [20][21] is designed for quick fault detection.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Approach for Fault Detection in Integrated Navigation Systems

Zhu

Zhou

2020

IEEE Access

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Detecting subsystem faults quickly is critical to the accuracy and reliability of integrated navigation systems. This paper, therefore, proposes an effective approach based on the novel test statistic to detect faults. Machine learning is introduced to estimate the innovation and its variance of local filter. The estimates combined with the actual ones are used to construct the test statistic, which is then proved to obey chi-square distribution. Thus fault detection can be realized by chi-square test. However, the special structure of the test statistic makes it sensitive to faults, even to the gradual faults. The experimental results demonstrate that the approach can detect faults quickly. Especially for gradual fault detection, the proposed test statistic has a marked superiority compared with the traditional test statistic of residual chi-square test.

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Section: Introductionmentioning

confidence: 99%

“…completely new detection test statistics [22][23][24]. Joerger et al [22] built the KF-based test statistic by adding the currenttime residual contribution to a previously computed weighted norm of past-time residuals.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach for Fault Detection in Integrated Navigation Systems

Zhu

Zhou

2020

IEEE Access

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“…In [34], an adaptive two-stage EKF was introduced to improve the reliability of coupled INS/GPS system with unknown bias fault. A magnetic compass fault detection approach for GPS/INS/Magnetic compass integrated navigation systems was proposed in [35], where the abrupt fault was supposed to be caused by the hard iron and soft iron effect. In [36], a fault tolerant Strapdown INS (SIN-S)/Global Navigation Satellite System (GNSS) approach was presented based on modified EKF and divided difference KF.…”

Section: Introductionmentioning

confidence: 99%

Anti-disturbance fault tolerant initial alignment for inertial navigation system subjected to multiple disturbances

Cao

Guo

Chen

2018

Aerospace Science and Technology

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Modeling error, stochastic error of inertial sensor, measurement noise and environmental disturbance affect the accuracy of an inertial navigation system (INS). In addition, some unpredictable factors, such as system fault, directly affect the reliability of INSs. This paper proposes a new anti-disturbance fault tolerant alignment approach for a class of INSs subjected to multiple disturbances and system faults. Based on modeling and error analysis, stochastic error of inertial sensor, measurement noise, modeling error and environmental disturbance are formulated into different types of disturbances described by a Markov stochastic process, Gaussian noise and a norm-bounded variable, respectively. In order to improve the accuracy and reliability of an INS, an anti-disturbance fault tolerant filter is designed. Then, a mixed dissipative/guarantee cost performance is applied to attenuate the norm-bounded disturbance and to optimize the estimation error. Slack variables and dissipativeness are introduced to reduce the conservatism of the proposed approach. Finally, compared with the unscented Kalman filter (UKF), simulation results for self-alignment of an INS are provided based on experimental data. It can be shown that the proposed method has an enhanced disturbance rejection and attenuation performance with high reliability.

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“…For instance, [14] proposed to utilize a setup based on two state propagators, alternatively selected based on the Kalman filter’s output, to prevent the risk of using a corrupted propagator for failure detection purposes resulting in an increased failure detection sensitivity. Traditionally, however, the chi-square test is applied for single failure detection and isolation by setting a threshold to judge whether the system is failed or not [15,16]. For instance, [17] employed fuzzy logic and weighted average to deal with the threshold and to reduce the percentage of incorrect alarm effectively.…”

Section: Introductionmentioning

confidence: 99%

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter

Yang

Mohammadi

Chen

2016

Sensors

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Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system’s error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts.

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Magnetic compass fault detection method for GPS/INS/magnetic compass integrated navigation systems

Cited by 25 publications

References 7 publications

A Novel Approach for Fault Detection in Integrated Navigation Systems

A Novel Approach for Fault Detection in Integrated Navigation Systems

Anti-disturbance fault tolerant initial alignment for inertial navigation system subjected to multiple disturbances

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter

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