Optimal navigation landmark selection for the mars landing phases based on visual constraint observability matrix

doi:10.23919/JSEE.2025.000162

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (6): 1645-1657.doi: 10.23919/JSEE.2025.000162

• CONTROL THEORY AND APPLICATION • Previous Articles

Optimal navigation landmark selection for the mars landing phases based on visual constraint observability matrix

Xinyu ZHAO¹(), Jiongqi WANG¹(), Bowen HOU¹(), Chao XU²(), Xuanying ZHOU¹^,*()

¹ College of Sciences, National University of Defense Technology, Changsha 410073, China
² Beijing Institute of Spacecraft System Engineering, Beijing 100190, China

Received:2024-04-23 Online:2025-12-18 Published:2026-01-07
Contact: Xuanying ZHOU E-mail:zhaoxinyunudt@nudt.edu.cn;wjq_gfkd@163.com;houbowen95@126.com;xc_1987@126.com;Julia_chow07@163.com
About author:
ZHAO Xinyu was born in 2002. He received his B.A. degree in electronic commerce from the Law & Business College of Hubei University of Economics, Wuhan, China, in 2023. He is pursuing his M.S. degree in the National University of Defense Technology. His current research interests include information fusion and autonomous navigation. E-mail: zhaoxinyunudt@nudt.edu.cn

WANG Jiongqi was born in 1979. He received his B.S. degree in applied mathematics from Zhejiang University, Hangzhou, China, in 2002, and M.S. and Ph.D. degrees in system science from National University of Defense Technology, in 2004 and 2008, respectively. He is a professor with the College of Sciences, National University of Defense Technology, Changsha, China. His research interests include measurement data analysis, parameter estimation, system identification, and space target state filter and its applications. E-mail: wjq_gfkd@163.com

HOU Bowen was born in 1995. He received his M.S. and Ph.D. degrees in system science from National University of Defense Technology, Changsha, China, in 2018, and 2023, respectively. He is an associate professor with the College of Sciences, National University of Defense Technology, Changsha, China. His current research interests include Kalman filter, signal processing, and integrated navigation. E-mail: houbowen95@126.com

XU Chao was born in 1987. He received his B.S. degree from Beihang University, Beijing, China, in 2010, and M.E. and Ph.D. degrees in guidance, navigation and control from China Academy of Space Technology (CAST), Beijing, China, in 2013 and 2017, respectively. He is an engineer with the Beijing Institute of Control Engineering, Beijing, China. His research interests include autonomous navigation, vision-aided navigation, and simultaneous localization and mapping. E-mail: xc_1987@126.com

ZHOU Xuanying was born in 1991. She received her B.S., M.S., and Ph.D. degrees in applied mathematics from National University of Defense Technology, Hunan, in 2013, 2016, and 2019, respectively. She is a lecturer with the College of Sciences, National University of Defense Technology, Changsha, China. Her research interests include system modelling, data processing, missiles, and signal process and its applications. E-mail: Julia_chow07@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (62203458), the Stabilisation Support Project of the Bureau of Science and Industry (HTKJ2023KL502012), and the Youth Autonomous Innovation Science Fund (ZK23-01).

Abstract

Abstract:

As the Mars probe, which has limited on-board ability in computation is unable to carry out the large-scale landmark solution, it is necessary to achieve optimal selection of landmarks while ensuring autonomous navigation accuracy during landing phase. This paper proposes an optimal landmark selection method based on the observability matrix for the Mars probe. Firstly, an observability matrix for navigation system is constructed with Fisher information quantity. Secondly, the optimal configuration of the landmark distribution is given by maximizing the scalar function of the observability matrix. Based on the optimal configuration, the greedy algorithm is used to determine the number of the landmarks at each moment adaptively. In addition, considering the fact that the number of the observable landmarks gradually decreases during the landing process, the convergence threshold of the greedy algorithm is set to a dynamic value regarding landing time. Finally, mathematical simulation verification is conducted, and the results show that the proposed optimal landmark selection method has higher navigation accuracy compared with the random landmark selection method. It can effectively suppress the influence of the measurement model errors and achieve a higher landing accuracy.

Key words: Mars landing, landmark selection, observability matrix, adaptive threshold

Xinyu ZHAO, Jiongqi WANG, Bowen HOU, Chao XU, Xuanying ZHOU. Optimal navigation landmark selection for the mars landing phases based on visual constraint observability matrix[J]. Journal of Systems Engineering and Electronics, 2025, 36(6): 1645-1657.

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State component	Real value
${{\boldsymbol{r}}_0}$/m	${\left[ {1\;300},{870},{2570} \right]^\text{T}}$
${{\boldsymbol{v}}_0}$/(m/s)	${\left[ { - 28},{ - 10},{ - 90} \right]^\text{T}}$
${{\boldsymbol{q}}_0}$	${\left[ {0.969},{0.247}, 0,0 \right]^\text{T}}$
${{\boldsymbol{b}}_\alpha }$/(m/s²)	${\left[ {3 \times {{10}^{ - 3}}},{3 \times {{10}^{ - 3}}},{3 \times {{10}^{ - 3}}} \right]^\text{T}}$
${{\boldsymbol{b}}_\omega }$/(rad/s)	${\left[ {4.8 \times {{10}^{ - 6}}},{4.8 \times {{10}^{ - 6}}},{4.8 \times {{10}^{ - 6}}} \right]^\text{T}}$

${U_{\min }}$	Maximum number of landmarks	Maximum running time/s	Average running time/s
${U_{\min }} = \min (U(D))/100$	5	0.02524	0.0013
${U_{\min }} = \min (U(D))/150$	8	0.02008	0.0019
${U_{\min }} = \min (U(D))/200$	19	0.03080	0.0030
Not set ${U_{\min }}$	650	0.83230	0.0400

Optimal navigation landmark selection for the mars landing phases based on visual constraint observability matrix

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