Optimal robust fault-detection filter for micro-electro-mechanical system-based inertial navigation system/global positioning system

Shi, Jingping; Liu, Miao; Ni, Maolin; Shen, Jiajun

doi:10.1049/iet-cta.2010.0639

Cited by 16 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar as what was found by Shi et al [4], the presented method based on generic algorithm can obtain accuracy optimizing results with acceptable time requirement compared to the method based on another optimizing algorithm.…”

Section: Design Methodssupporting

confidence: 82%

See 1 more Smart Citation

Research on Formation of Microsatellite Communication with Genetic Algorithm

Bai

Sun

2013

The Scientific World Journal

View full text Add to dashboard Cite

For the formation of three microsatellites which fly in the same orbit and perform three-dimensional solid mapping for terra, this paper proposes an optimizing design method of space circular formation order based on improved generic algorithm and provides an intersatellite direct spread spectrum communication system. The calculating equation of LEO formation flying satellite intersatellite links is guided by the special requirements of formation-flying microsatellite intersatellite links, and the transmitter power is also confirmed throughout the simulation. The method of space circular formation order optimizing design based on improved generic algorithm is given, and it can keep formation order steady for a long time under various absorb impetus. The intersatellite direct spread spectrum communication system is also provided. It can be found that, when the distance is 1 km and the data rate is 1 Mbps, the input wave matches preferably with the output wave. And LDPC code can improve the communication performance. The correct capability of (512, 256) LDPC code is better than (2, 1, 7) convolution code, distinctively. The design system can satisfy the communication requirements of microsatellites. So, the presented method provides a significant theory foundation for formation-flying and intersatellite communication.

show abstract

Section: Design Methodssupporting

confidence: 82%

“…To make use of recent advances in MEMS, robust microsatellites can be built [2–4]. In order to integrate the resources of autonomous and formation-flying groups of microsatellites effectively, the satellites must have good ability to communicate with each other.…”

Section: Introductionmentioning

confidence: 99%

Research on Formation of Microsatellite Communication with Genetic Algorithm

Bai

Sun

2013

The Scientific World Journal

View full text Add to dashboard Cite

show abstract

“…Therefore the statistical features of the measurement and system noises cannot be predefined as required by the standard CKF or standard FKF. The navigation sensors are prone to faults and environmental effects in real applications [20][21][22] . Incorrect a priori information of the sensor statistics can seriously worsen the standard filter performance.…”

Section: Adaptive Filtering and Fault Detection In Local Kfmentioning

confidence: 99%

A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

Ushaq

Fang

2013

SPIE Proceedings

View full text Add to dashboard Cite

Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be applied to the navigation system of aircraft or unmanned aerial vehicle (UAV).

show abstract

“…Alternatively, the H∞ filter has been developed as a robust filtering method. The H∞ filter does not make any assumptions about the error’s characteristics, but regards it as energy-bounded signal [ 23 , 24 , 25 , 26 , 27 ]. In other words, the H∞ filter does not need to have predefined error models.…”

Section: Introductionmentioning

confidence: 99%

A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning

Liu

et al. 2016

Sensors

View full text Add to dashboard Cite

In this paper, we propose a novel positioning solution for land vehicles which is highly reliable and cost-efficient. The proposed positioning system fuses information from the MEMS-based reduced inertial sensor system (RISS) which consists of one vertical gyroscope and two horizontal accelerometers, low-cost GPS, and supplementary sensors and sources. First, pitch and roll angle are accurately estimated based on a vehicle kinematic model. Meanwhile, the negative effect of the uncertain nonlinear drift of MEMS inertial sensors is eliminated by an H∞ filter. Further, a distributed-dual-H∞ filtering (DDHF) mechanism is adopted to address the uncertain nonlinear drift of the MEMS-RISS and make full use of the supplementary sensors and sources. The DDHF is composed of a main H∞ filter (MHF) and an auxiliary H∞ filter (AHF). Finally, a generalized regression neural network (GRNN) module with good approximation capability is specially designed for the MEMS-RISS. A hybrid methodology which combines the GRNN module and the AHF is utilized to compensate for RISS position errors during GPS outages. To verify the effectiveness of the proposed solution, road-test experiments with various scenarios were performed. The experimental results illustrate that the proposed system can achieve accurate and reliable positioning for land vehicles.

show abstract

Optimal robust fault-detection filter for micro-electro-mechanical system-based inertial navigation system/global positioning system

Cited by 16 publications

References 18 publications

Research on Formation of Microsatellite Communication with Genetic Algorithm

Research on Formation of Microsatellite Communication with Genetic Algorithm

A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

A Highly Reliable and Cost-Efficient Multi-Sensor System for Land Vehicle Positioning

Contact Info

Product

Resources

About