Autonomous optical navigation based on adaptive SR-UKF for deep space probes

Lichao Ma; Zaozhen Liu; Xiuyun Meng

Autonomous optical navigation based on adaptive SR-UKF for deep space probes

Lichao Ma^*, Zaozhen Liu, Xiuyun Meng

^*Corresponding author for this work

School of Aerospace Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

A novel adaptive Square-Root Unscented Kalman Filter (Adaptive SR-UKF) was proposed to solve the problem that the priori noise statistics are difficult to obtain accurately in an autonomous optical navigation for deep space probes. The adaptive SR-UKF realizes its initialization by using an approximation of the priori noise statistics, which is corrected at each step by the adaptive SR-UKF that adopts a limited memory algorithm for the estimation of the noise statistics based on noise samples. Effectiveness of the Adaptive SR-UKF is examined by the simulation of an autonomous optical navigation for the cruise phase of a cislunar probe, and results show that the Adaptive SR-UKF is much superior to UKF and SR-UKF when the priori noise statistics are inaccurate.

Original language	English
Title of host publication	Proceedings of the 29th Chinese Control Conference, CCC'10
Pages	321-325
Number of pages	5
Publication status	Published - 2010
Event	29th Chinese Control Conference, CCC'10 - Beijing, China Duration: 29 Jul 2010 → 31 Jul 2010

Publication series

Name	Proceedings of the 29th Chinese Control Conference, CCC'10

Conference

Conference	29th Chinese Control Conference, CCC'10
Country/Territory	China
City	Beijing
Period	29/07/10 → 31/07/10

Keywords

Adaptive square-root unscented Kalman Filter
Autonomous optical navigation
Deep space probe

Cite this

@inproceedings{00558c0c64b84e2badc9d9715ac6bab5,

title = "Autonomous optical navigation based on adaptive SR-UKF for deep space probes",

abstract = "A novel adaptive Square-Root Unscented Kalman Filter (Adaptive SR-UKF) was proposed to solve the problem that the priori noise statistics are difficult to obtain accurately in an autonomous optical navigation for deep space probes. The adaptive SR-UKF realizes its initialization by using an approximation of the priori noise statistics, which is corrected at each step by the adaptive SR-UKF that adopts a limited memory algorithm for the estimation of the noise statistics based on noise samples. Effectiveness of the Adaptive SR-UKF is examined by the simulation of an autonomous optical navigation for the cruise phase of a cislunar probe, and results show that the Adaptive SR-UKF is much superior to UKF and SR-UKF when the priori noise statistics are inaccurate.",

keywords = "Adaptive square-root unscented Kalman Filter, Autonomous optical navigation, Deep space probe",

author = "Lichao Ma and Zaozhen Liu and Xiuyun Meng",

year = "2010",

language = "English",

isbn = "9787894631046",

series = "Proceedings of the 29th Chinese Control Conference, CCC'10",

pages = "321--325",

booktitle = "Proceedings of the 29th Chinese Control Conference, CCC'10",

note = "29th Chinese Control Conference, CCC'10 ; Conference date: 29-07-2010 Through 31-07-2010",

}

Autonomous optical navigation based on adaptive SR-UKF for deep space probes. / Ma, Lichao; Liu, Zaozhen; Meng, Xiuyun.
Proceedings of the 29th Chinese Control Conference, CCC'10. 2010. p. 321-325 5573214 (Proceedings of the 29th Chinese Control Conference, CCC'10).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Autonomous optical navigation based on adaptive SR-UKF for deep space probes

AU - Ma, Lichao

AU - Liu, Zaozhen

AU - Meng, Xiuyun

PY - 2010

Y1 - 2010

N2 - A novel adaptive Square-Root Unscented Kalman Filter (Adaptive SR-UKF) was proposed to solve the problem that the priori noise statistics are difficult to obtain accurately in an autonomous optical navigation for deep space probes. The adaptive SR-UKF realizes its initialization by using an approximation of the priori noise statistics, which is corrected at each step by the adaptive SR-UKF that adopts a limited memory algorithm for the estimation of the noise statistics based on noise samples. Effectiveness of the Adaptive SR-UKF is examined by the simulation of an autonomous optical navigation for the cruise phase of a cislunar probe, and results show that the Adaptive SR-UKF is much superior to UKF and SR-UKF when the priori noise statistics are inaccurate.

AB - A novel adaptive Square-Root Unscented Kalman Filter (Adaptive SR-UKF) was proposed to solve the problem that the priori noise statistics are difficult to obtain accurately in an autonomous optical navigation for deep space probes. The adaptive SR-UKF realizes its initialization by using an approximation of the priori noise statistics, which is corrected at each step by the adaptive SR-UKF that adopts a limited memory algorithm for the estimation of the noise statistics based on noise samples. Effectiveness of the Adaptive SR-UKF is examined by the simulation of an autonomous optical navigation for the cruise phase of a cislunar probe, and results show that the Adaptive SR-UKF is much superior to UKF and SR-UKF when the priori noise statistics are inaccurate.

KW - Adaptive square-root unscented Kalman Filter

KW - Autonomous optical navigation

KW - Deep space probe

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M3 - Conference contribution

AN - SCOPUS:78650244122

SN - 9787894631046

T3 - Proceedings of the 29th Chinese Control Conference, CCC'10

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BT - Proceedings of the 29th Chinese Control Conference, CCC'10

T2 - 29th Chinese Control Conference, CCC'10

Y2 - 29 July 2010 through 31 July 2010

ER -

Autonomous optical navigation based on adaptive SR-UKF for deep space probes

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Conference

Keywords

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