An outlier rejecting and adaptive filter algorithm applied in MEMS-SINS/GPS

Jing Shi; Ling Juan Miao; Mao Lin Ni

doi:10.3873/j.issn.1000-1328.2010.12.014

An outlier rejecting and adaptive filter algorithm applied in MEMS-SINS/GPS

Jing Shi^*, Ling Juan Miao, Mao Lin Ni

^*Corresponding author for this work

School of Automation

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

An outlier rejecting and adaptive filter is proposed against the influence of outliers in measurements and inaccurate noise statistical characteristics on Kalman filter. This algorithm computes the fading factors or performs outlier rejecting calculations by real-time monitoring the predicted residuals, such that the filter can still be optimal when there are outliers in measurements and when statistical characteristics are inaccurate. This approach is applied to the MEMS-SINS/GPS integrated navigation system, and simulation results show that the new algorithm is effective at the aspect of reducing the impact of outliers and inaccurate noise statistical characteristics.

Original language	English
Pages (from-to)	2711-2716
Number of pages	6
Journal	Yuhang Xuebao/Journal of Astronautics
Volume	31
Issue number	12
DOIs	https://doi.org/10.3873/j.issn.1000-1328.2010.12.014
Publication status	Published - Dec 2010

Keywords

Adaptive
Integrated navigation
Micro electro mechanical system
Outlier rejecting
Strapdown inertial navigation system

Access to Document

10.3873/j.issn.1000-1328.2010.12.014

Cite this

@article{70fc09141fa8407fb0b9c5b872fc797e,

title = "An outlier rejecting and adaptive filter algorithm applied in MEMS-SINS/GPS",

abstract = "An outlier rejecting and adaptive filter is proposed against the influence of outliers in measurements and inaccurate noise statistical characteristics on Kalman filter. This algorithm computes the fading factors or performs outlier rejecting calculations by real-time monitoring the predicted residuals, such that the filter can still be optimal when there are outliers in measurements and when statistical characteristics are inaccurate. This approach is applied to the MEMS-SINS/GPS integrated navigation system, and simulation results show that the new algorithm is effective at the aspect of reducing the impact of outliers and inaccurate noise statistical characteristics.",

keywords = "Adaptive, Integrated navigation, Micro electro mechanical system, Outlier rejecting, Strapdown inertial navigation system",

author = "Jing Shi and Miao, {Ling Juan} and Ni, {Mao Lin}",

year = "2010",

month = dec,

doi = "10.3873/j.issn.1000-1328.2010.12.014",

language = "English",

volume = "31",

pages = "2711--2716",

journal = "Yuhang Xuebao/Journal of Astronautics",

issn = "1000-1328",

publisher = "Chinese Society of Astronautics",

number = "12",

}

TY - JOUR

T1 - An outlier rejecting and adaptive filter algorithm applied in MEMS-SINS/GPS

AU - Shi, Jing

AU - Miao, Ling Juan

AU - Ni, Mao Lin

PY - 2010/12

Y1 - 2010/12

N2 - An outlier rejecting and adaptive filter is proposed against the influence of outliers in measurements and inaccurate noise statistical characteristics on Kalman filter. This algorithm computes the fading factors or performs outlier rejecting calculations by real-time monitoring the predicted residuals, such that the filter can still be optimal when there are outliers in measurements and when statistical characteristics are inaccurate. This approach is applied to the MEMS-SINS/GPS integrated navigation system, and simulation results show that the new algorithm is effective at the aspect of reducing the impact of outliers and inaccurate noise statistical characteristics.

AB - An outlier rejecting and adaptive filter is proposed against the influence of outliers in measurements and inaccurate noise statistical characteristics on Kalman filter. This algorithm computes the fading factors or performs outlier rejecting calculations by real-time monitoring the predicted residuals, such that the filter can still be optimal when there are outliers in measurements and when statistical characteristics are inaccurate. This approach is applied to the MEMS-SINS/GPS integrated navigation system, and simulation results show that the new algorithm is effective at the aspect of reducing the impact of outliers and inaccurate noise statistical characteristics.

KW - Adaptive

KW - Integrated navigation

KW - Micro electro mechanical system

KW - Outlier rejecting

KW - Strapdown inertial navigation system

UR - http://www.scopus.com/inward/record.url?scp=78751604270&partnerID=8YFLogxK

U2 - 10.3873/j.issn.1000-1328.2010.12.014

DO - 10.3873/j.issn.1000-1328.2010.12.014

M3 - Article

AN - SCOPUS:78751604270

SN - 1000-1328

VL - 31

SP - 2711

EP - 2716

JO - Yuhang Xuebao/Journal of Astronautics

JF - Yuhang Xuebao/Journal of Astronautics

IS - 12

ER -

An outlier rejecting and adaptive filter algorithm applied in MEMS-SINS/GPS

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this