A tightly coupled rotational SINS/CNS integrated navigation method for aircraft

doi:10.21629/JSEE.2019.04.14

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (4): 770-782.doi: 10.21629/JSEE.2019.04.14

• Control Theory and Application • Previous Articles Next Articles

A tightly coupled rotational SINS/CNS integrated navigation method for aircraft

Xiaolin NING(), Weiping YUAN(), Yanhong LIU*()

School of Instrument and Optoelectronic Engineering, Beihang University, Beijing 100191, China

Received:2018-08-13 Online:2019-08-01 Published:2019-09-01
Contact: Yanhong LIU E-mail:ningxiaolin@buaa.edu.cn;yuan_1166@sina.com;liu1253891321@163.com
About author:NING Xiaolin was born in 1979. She received her B.E. degree in computer science from Shandong Normal University, Shandong, China, in 2001, and Ph.D. degree in mechanical engineering from Beihang University, Beijing, China, in 2008. She has been a professor with the School of Instrument and Optoelectronic Engineering, Beihang University since 2011. From March 2014 to March 2015, she was a visiting scholar at the National University of Singapore. Her research interests include guidance, navigation, and control system of spacecraft and autonomous navigation of deep space explorers. She proposed many novel methods of astronomical navigation, and the research results are used in the Chang'e II and Mars exploration pre-research. E-mail:ningxiaolin@buaa.edu.cn|YUAN Weiping was born in 1992. He received his B.E. degree in measurement and control technology and instrument from University of Science and Technology, Beijing, in 2015. He received his master degree from Beihang University in 2018. Now, he is engaged in navigation related job as a engineer at Huawei, Beijing. His research interests include single-axis rotational SINS/CNS integrated navigation, vehicle navigation and driver-less car. E-mail:yuan_1166@sina.com|LIU Yanhong was born in 1988. She received her B.E. degree in electrical engineering and automation from Hebei University of Engineering in 2014. She received her master degree in control science and engineering from Beijing University of Technology in 2017. Since 2017, she has been working toward her doctor degree in Beihang University. In the first year, she served as a teaching assistant in the School of Instrument and Optoelectronic Engineering. Her research interests include machine vision, indoor navigation and high precision strapdown inertial navigation system/global positioning system integrated measurement system. E-mail:liu1253891321@163.com
Supported by:
the National Natural Science Foundation of China(61722301);This work was supported by the National Natural Science Foundation of China (61722301)

Abstract

Abstract:

Strapdown inertial navigation system (SINS)/celestial navigation system (CNS) integrated navigation is widely used to achieve long-time and high-precision autonomous navigation for aircraft. In general, SINS/CNS integrated navigation can be divided into two integrated modes:loosely coupled integrated navigation and tightly coupled integrated navigation. Because the loosely coupled SINS/CNS integrated system is only available in the condition of at least three stars, the latter one is becoming a research hotspot. One major challenge of SINS/CNS integrated navigation is obtaining a high-precision horizon reference. To solve this problem, an innovative tightly coupled rotational SINS/CNS integrated navigation method is proposed. In this method, the rotational SINS error equation in the navigation frame is used as the state model, and the starlight vector and star altitude are used as measurements. Semi-physical simulations are conducted to test the performance of this integrated method. Results show that this tightly coupled rotational SINS/CNS method has the best navigation accuracy compared with SINS, rotational SINS, and traditional tightly coupled SINS/CNS integrated navigation method.

Key words: celestial navigation system (CNS), rotation modulation technology, rotational strapdown inertial navigation system (SINS), rotational SINS/CNS integrated navigation

Xiaolin NING, Weiping YUAN, Yanhong LIU. A tightly coupled rotational SINS/CNS integrated navigation method for aircraft[J]. Journal of Systems Engineering and Electronics, 2019, 30(4): 770-782.

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References 28

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Method	Mean position error/m		Root mean square/m		Mean attitude error/(")			Mean velocity error/(m/s)
Method	Longitude	Latitude	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
SINS	924.39	820.53	547.85	526.16	14.43	18.66	59.20	0.66	0.60
Rotational SINS	786.85	313.39	505.08	218.87	10.05	10.10	43.38	0.43	0.39
The tightly coupled SINS/CNS integrated navigation method	234.21	173.55	113.16	100.32	4.98	6.01	5.46	0.18	0.16
The tightly coupled rotational SINS/CNS integrated navigation	33.55	33.52	27.11	22.02	1.24	0.96	0.97	0.04	0.06

$\theta_{bp}/(^\circ)$	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
$\theta_{bp}/(^\circ)$	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
0	20.51	11.94	0.16	0.24	0.60	0.01	0.02
30	17.05	10.46	0.11	0.17	0.53	0.01	0.01
45	13.24	6.94	0.11	0.14	0.49	0.01	0.01
60	15.37	8.28	0.13	0.14	0.48	0.01	0.01
90	18.52	10.46	0.15	0.16	0.46	0.01	0.01

$\theta_{bp}/(^\circ)$	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
$\theta_{bp}/(^\circ)$	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
0	33.55	33.52	1.24	0.96	0.97	0.04	0.06
30	34.75	34.64	1.27	0.98	0.94	0.04	0.06
45	34.96	35.16	1.26	0.10	0.90	0.04	0.06
60	35.67	35.92	1.28	1.01	0.94	0.04	0.06
90	36.83	37.54	1.31	1.05	0.94	0.04	0.06

Gyro accuracy/(($^\circ$)/h)	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
Gyro accuracy/(($^\circ$)/h)	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
0.000 5	33.49	33.72	1.22	0.96	0.96	0.04	0.06
0.002 5	33.57	33.44	1.24	0.96	0.97	0.04	0.06
0.005	33.55	33.52	1.24	0.96	0.97	0.04	0.06
0.007 5	33.59	33.56	1.24	0.96	0.95	0.04	0.06
0.01	33.59	32.62	1.24	0.96	0.93	0.04	0.06

Accelerometer accuracy/μg	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
Accelerometer accuracy/μg	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
5	32.27	32.18	1.23	0.92	0.93	0.03	0.05
25	32.57	32.61	1.23	0.94	0.94	0.03	0.06
50	33.55	33.52	1.24	0.96	0.97	0.04	0.06
75	34.87	34.71	1.26	1.00	0.99	0.04	0.06
100	36.39	36.15	1.30	1.05	1.02	0.04	0.07

A tightly coupled rotational SINS/CNS integrated navigation method for aircraft

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Star sensor accuracy/(")	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
Star sensor accuracy/(")	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
2	31.48	33.11	1.22	0.96	0.87	0.04	0.06
3	33.55	33.52	1.24	0.96	0.97	0.04	0.06
4	36.44	34.09	1.26	0.96	1.09	0.04	0.06
5	39.90	34.81	1.28	0.97	1.24	0.04	0.06
6	43.74	35.87	1.31	0.98	1.39	0.04	0.06

IMU installation error/(")	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
IMU installation error/(")	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
0	33.55	33.52	1.24	0.96	0.97	0.04	0.06
5	41.72	48.61	4.86	4.59	1.39	0.05	0.07
10	59.35	71.42	9.27	9.05	1.88	0.06	0.09
15	80.89	95.62	13.75	13.54	2.40	0.08	0.11
20	103.16	120.29	18.26	18.04	2.93	0.10	0.13

Star sensor installation error/(")	Mean position error/m		Mean attitude error/(")			Mean velocity error/(m/s)
Star sensor installation error/(")	Longitude	Latitude	Pitch	Roll	Yaw	Eastern	Northern
0	33.55	33.52	1.24	0.96	0.97	0.04	0.06
5	126.92	102.56	1.84	1.41	6.85	0.06	0.10
10	269.05	218.20	3.37	2.70	13.24	0.10	0.19
15	412.17	335.68	4.96	4.08	19.74	0.15	0.29
20	555.69	453.22	6.56	5.49	26.31	0.20	0.38