Approach to dynamic error suppression in ground vehicle gravimetry based on external velocity compensation

doi:10.23919/JSEE.2025.000039

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (2): 580-596.doi: 10.23919/JSEE.2025.000039

• CONTROL THEORY AND APPLICATION • Previous Articles

Approach to dynamic error suppression in ground vehicle gravimetry based on external velocity compensation

Xinyu LI¹^,²(), Zhaofa ZHOU¹^,²^,*(), Zhili ZHANG¹^,²(), Zhenjun CHANG¹^,²(), Shiwen HAO¹^,²()

¹ College of Missile Engineering, Rocket Force University of Engineering, Xi’an 710025, China
² State Key Discipline Laboratory of Armament Launch Theory and Technology, Rocket Force University of Engineering, Xi’an 710025, China

Received:2024-01-11 Online:2025-04-18 Published:2025-05-20
Contact: Zhaofa ZHOU E-mail:1025997454@qq.com;zzftxy@163.com;zhangzl@126.com;changzj2105@163.com;wenjy70796@163.com
About author:
LI Xinyu was born in 1997. He received his B.S. degree from the Rocket Force University of Engineering, Xi’an, China, in 2021, where he is currently pursuing his M.S. and Ph.D. degrees. His research interests are related to gravity measurement and integrated navigation. E-mail: 1025997454@qq.com

ZHOU Zhaofa was born in 1973. He received his Ph.D. degree from the Rocket Force University of Engineering, Xi’an, China, in 2004. He is currently a professor with the Rocket Force University of Engineering. His research interests are integrated navigation and control engineering. E-mail: zzftxy@163.com

ZHANG Zhili was born in 1966. He received his B.S., M.S., and Ph.D. degrees from the Rocket Force University of Engineering, China, in 1988, 1991, and 2001, respectively. He is currently a professor with the Rocket Force University of Engineering. His research interests include inertial navigation theory, system simulation, and position and navigation. E-mail: zhangzl@126.com

CHANG Zhenjun was born in 1986. He received his Ph.D. degree from the Rocket Force University of Engineering, Xi’an, China, in 2019. He is currently a lecturer with the Rocket Force University of Engineering. His research interests are integrated navigation and alignment. E-mail: changzj2105@163.com

HAO Shiwen was born in 1996. He received his B.S. degree from Beijing University of Science and Technology, Beijing, China, in 2018. He is currently pursuing his Ph.D. degree with the Rocket Force University of Engineering, Xi’an, China. His research interests include gravity measurement and inertial navigation. E-mail: wenjy70796@163.com
Supported by:
This work was supported by the Shanxi Provincial Natural Science Basic Research Program Young Talent Project (S2019-JC-QN-2408).

Abstract

Abstract:

The process of ground vehicle dynamic gravimetry is inevitably affected by the carrier’s maneuvering acceleration, which makes the result contain a large amount of dynamic error. In this paper, we propose a dynamic error suppression method of gravimetry based on the high-precision acquisition of external velocity for compensating the horizontal error of the inertial platform. On the basis of platform gravity measurement, firstly, the dynamic performance of the system is enhanced by optimizing the horizontal damping network of the inertial platform and selecting its parameter. Secondly, an improved federal Kalman filtering algorithm and a fault diagnosis method are designed using strapdown inertial navigation system (SINS), odometer (OD), and laser Doppler velocimeter (LDV). Simulation validates that these methods can improve the accuracy and robustness of the external velocity acquisition. Three survey lines are selected in Tianjin, China, for the gravimetry experiments with different maneuvering levels, and the results demonstrate that after dynamic error suppression, the internal coincidence accuracies of smooth and uniform operation, obvious acceleration and deceleration operation, and high-dynamic operation are improved by 70.2%, 73.6%, and 77.9% to reach 0.81 mGal, 1.30 mGal, and 1.94 mGal, respectively, and the external coincidence accuracies during smooth and uniform operation are improved by 48.6% up to 1.66 mGal. It is shown that the proposed method can effectively suppress the dynamic error, and that the accuracy improvement increases with carrier maneuverability. However, the amount of residual error that can not be entirely eliminated increases as well, so the ground vehicle dynamic gravimetry should be maintained in the carrier for smooth and uniform operation.

Key words: ground vehicle gravimetry, dynamic error suppression, external velocity compensation, federal Kalman filter, fault diagnosis and isolation

Xinyu LI, Zhaofa ZHOU, Zhili ZHANG, Zhenjun CHANG, Shiwen HAO. Approach to dynamic error suppression in ground vehicle gravimetry based on external velocity compensation[J]. Journal of Systems Engineering and Electronics, 2025, 36(2): 580-596.

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References 30

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Method	Error
Method	Max	Min	Mean	Std
Baro-h	2.30	−1.95	0.48	0.58
SINS/OD-h	0.03	−38.27	−18.9	12.9
KF-h	1.63	−1.36	0.11	0.37

Device/Sensor	Characteristic	Accuracy
Inertial measurement unit (IMU)	Acce bias stability/mGal	10
	Acce random walk/mGal	5
	Gyro bias instability/((°)/h)	0.001
	Gyro random walk/($ ({}^ \circ) /\sqrt {\text{h}} $)	0.0001
	Sample frequency/Hz	100
OD	Installation error	[1′;1′;10′]
	Scale factor	kod = 0.9986
	Time asynchronism/s	dT = 0.01
	Fault type and time/s	Zero setting: 2 097−2 100 Uprush: 6 000−6 005
LDV	Installation error	[1′;1′;10′]
	Scale factor	kldv = 1.002
	Time asynchronism/s	dT = 0.01
	Fault type and time/s	Zero setting: 4 197−4 200

Sub-system	Fault type	Fault time/s	State detection alarm time/s	Residual detection alarm time/s	Residual-state detection alarm time/s
OD	Zero setting	2097−2100	2098−2110	2097−2100	2097−2110
OD	Uprush	6000−6005	6001−6017	6000−6005	6000−6017
LDV	Zero setting	4197−4200	4198−4210	4197−4200	4197−4210

Condition	Method	Position error/m/Velocity error/(m/s)
Condition	Method	Mean	Max	Standrad
Without fault	SINS/OD	13.49 / 0.0040	42.11 / 0.0552	8.70 / 0.0060
	SINS/LDV	31.48 / 0.0094	68.06 / 0.0688	20.15 / 0.0075
	FKF	10.38 / 0.0032	36.82 / 0.0756	6.50 / 0.0046
With fault	SINS/OD	20.59 / 0.0079	49.63 / 0.2352	10.62 / 0.0074
	SINS/LDV	48.08 / 0.0132	104.15 / 0.0746	31.07 / 0.0189
	FKF	14.32 / 0.0050	42.72 / 0.0688	7.41 / 0.0052

Device	Sensor	Characteristic	Accuracy
Double axis laser SINS	Gyroscopes	Bias instability	0.0015$ {}^ \circ /{\text{h}} $
	Gyroscopes	Random walk	0.0002$ {}^ \circ /\sqrt {\text{h}} $
	Accelerometer	Bias stability	10 μg/day
	Accelerometer	Random walk	5 μg/$\sqrt {{\text{Hz}}} $
Gravimeter	Gravity sensor	Static output	≤ 0.01 mGal
Gravimeter	Gravity sensor	Temperature control	≤ 0.001℃
OD	Pulse counter	Counting error	1×10⁻⁴
OD	Pulse counter	Velocity error	0.001 1 m/s
Barometer	Pressure sensor	Resolution	5 Pa
Barometer	Pressure sensor	Height error	2.5 m
LDV	Dual optical drive	Velocity error	≤ 1‰
	Location devices	Horizontal error	5 cm
	Location devices	Height error	0.1 m
GPS	Velocity measuring devices	Horizontal error	0.01 m/s
GPS	Velocity measuring devices	Height error	0.02 m/s

Approach to dynamic error suppression in ground vehicle gravimetry based on external velocity compensation

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Survey lines	Metric	Accuracy
Survey lines	Metric	Before error suppression	After error suppression	Percentage/%
Line 1-1	Internal coincidence	2.61	1.14	56.3
Line 1-2		3.24	0.84	74.1
Line 1-3		2.98	0.53	82.2
Line 1-4		1.83	0.57	68.9
Line 1		2.72	0.81	70.2
Line 1-1	External coincidence	3.10	0.92	70.3
Line 1-2		4.07	2.03	50.1
Line 1-3		3.32	1.54	53.6
Line 1-4		2.17	1.93	11.1
Line 1		3.23	1.66	48.6
Line 2-1	Internal coincidence	4.92	1.27	74.2
Line 2-2		4.94	1.33	73.1
Line 2		4.93	1.30	73.6
Line 3-1	Internal coincidence	8.61	1.92	77.7
Line 3-2		8.93	1.96	78.1
Line 3		8.77	1.94	77.9