A method for fault detection and isolation in the integrated navigation system for UAV

Yang, Bo; Yongyuan, Qin; Chai, Yuan

doi:10.1088/0957-0233/17/6/033

Cited by 14 publications

(6 citation statements)

References 11 publications

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“…A different technique for fault detection and isolation is the parity space approach [18][19][20]. However, the parity space approach is based on the assumption that the error vector has zero mean E(v) = 0 and E(vv T ) = σ I.…”

Section: Virtual Sensing Using Least-squares Based Estimation Methodsmentioning

confidence: 99%

Virtual sensing of wheel direction from redundant sensors in aircraft ground-steering systems

et al. 2021

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Many safety-critical control systems use multiple redundant sensors to estimate the same controlled signal. If the sensors were to operate perfectly, only a subset of them would need to be used for the estimation. In practice, however, the sensors are subject to uncertainty, minor or major faults and their operation may be nonlinear. It is thus important to reliably estimate the controlled signal under these conditions, and also to assess the degree of confidence with which each sensor should be treated. An example of such a control system is the ground-steering control system of an aircraft nose landing gear. A virtual sensing technique is commonly employed, which estimates the steering angle using the measurements of multiple remote displacement sensors. The wheel position is then calculated as a nonlinear function of these sensor outputs.This paper describes how a digital twin of the ground-steering system, in which the effects of uncertainties and faults can be systematically analysed and studied, is used to assess the accuracy and integrity of the steering angle estimation for a number of different estimation algorithms. Two of these algorithms are based on a least-squares approach, while another is a soft-computing technique based on fuzzy logic. These methods are investigated for several scenarios where model uncertainty, measurement noise and sensor faults are included. It is shown that the soft-computing approach is more robust than the least squares based methods under these conditions.

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Section: Virtual Sensing Using Least-squares Based Estimation Methodsmentioning

confidence: 99%

Virtual sensing of wheel direction from redundant sensors in aircraft ground-steering systems

et al. 2021

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“…Micromechanical technology has allowed huge progress in miniaturization and cost reduction for these devices [166]. Fault detection schemes devoted to IMU/INS/GPS systems can be found in references [42,45,50,52,64,67], mostly based on parity space or observers exploiting analytical redundancy from (1) and (3). Air data sensing (ADS) systems are used in addition to the previous set of sensors to measure airspeed, dynamic pressure, Mach number, or angles of attack and sideslip [167].…”

Section: Sensorsmentioning

confidence: 99%

Model-based fault diagnosis for aerospace systems: a survey

Marzat

Piet-Lahanier

Damongeot

et al. 2012

Proceedings of the Institution of Mechanical Engineers, Part G:

222

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http://pig.sagepub.com/content/early/2012/01/06/0954410011421717International audienceThis survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic nonlinear dynamical modeling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided

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“…X 1 (k), X 2 (k) and P 1 (k), P 2 (k) are the state estimation value and error covariance matrices of the celestial navigation local filter and Doppler navigation local filter, respectively. The global optimal state estimation of the master filter is obtained with the following information fusion equations [31,32]:…”

Section: Information Fusion In the Master Filtermentioning

confidence: 99%

Spacecraft autonomous navigation using unscented particle filter-based celestial/Doppler information fusion

Ning¹,

Fang²

2008

Meas. Sci. Technol.

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With the development of space missions, especially manned space missions, a reliable and secure navigation system, and assured autonomous capability in case of emergencies in space, is needed. In order to compensate for the insufficiency of ground station tracking and control, a new autonomous celestial/Doppler-integrated navigation method for a spacecraft is proposed. Celestial navigation is a fully autonomous navigation method, but in some situations the navigation accuracy of this method is subject to the inaccuracies of the measuring devices. Doppler navigation can serve as a good complement to celestial navigation. Because both the state and the measurement models of a celestial/Dopplerintegrated navigation system are nonlinear and non-Gaussian, the unscented particle filter (UPF) based information fusion method is proposed here to fuse the position signals from the celestial navigation and Doppler navigation subsystems, and to enhance the navigation accuracy. The performance of this new method is tested and examined using actual spacecraft-orbit data. Simulations show that the position and velocity accuracies are estimated to within 300 m and 0.5 m s −1 respectively, which demonstrate the feasibility and effectiveness of this method. Moreover, it can be used as a backup system to provide redundancy.

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A method for fault detection and isolation in the integrated navigation system for UAV

Cited by 14 publications

References 11 publications

Virtual sensing of wheel direction from redundant sensors in aircraft ground-steering systems

Virtual sensing of wheel direction from redundant sensors in aircraft ground-steering systems

Model-based fault diagnosis for aerospace systems: a survey

Spacecraft autonomous navigation using unscented particle filter-based celestial/Doppler information fusion

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