基于改进EMD-CIIT降噪算法的INS/5G组合导航方法

doi:10.12305/j.issn.1001-506X.2024.12.29

Abstract

Abstract:

This paper focuses on the inertial navigation system (INS)/5G integrated navigation system. Firstly, an improved thresholding algorithm called clear iterative empirical mode decomposition interval-thresholding (EMD-CIIT) is proposed to effectively enhance the signal-to-noise ratio (SNR) of inertial sensors and thereby improve the positioning accuracy of the integrated navigation system, which addresses the issue of low SNR in low-cost inertial sensors that impacts the accuracy of integrated navigation systems. Additionally, to address the issues of co-frequency interference, clock bias, and clock drift in 5G opportunity signals that cause abnormal pseudo-range values, a tightly-integrated navigation algorithm based on adaptive Kalman filtering is proposed. The proposed algorithm utilizes a 5G pseudo-range confidence scheme based on Mahalanobis distance to adjust the observation covariance matrix in real time, which mitigates the impact of abnormal pseudo-range values on positioning accuracy and further enhances the reliability of positioning. Finally, the effectiveness and superiority of the proposed solution tests are validated through numerical simulation tests and experimental methods.

Key words: 5G opportunity signals positioning, empirical mode decomposition (EMD), adaptive Kalman filtering, tightly integration

CLC Number:

Yunlong ZHAO, Qian SUN, Xin JIAN, Yibing LI, Fe YU. INS/5G integrated navigation method based on improved EMD-CIIT denoising algorithm[J]. Systems Engineering and Electronics, 2024, 46(12): 4203-4212.

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References 31

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5G基站	纬度	经度	高度/m	5G基站	纬度	经度	高度/m
gNB1	114°8′50.82″	22°17′6.94″	108.8	gNB11	114°8′49.63″	22°17′5.22″	20
gNB2	114°8′50.46″	22°17′6.43″	108.8	gNB12	114°8′49.58″	22°17′5.18″	20
gNB3	114°8′51.18″	22°17′6.76″	108.8	gNB13	114°8′49.74″	22° 17′5.04″	20
gNB4	114°8′52.3″	22°17′6.31″	108.8	gNB14	114°8′49.83″	22°17′5.02″	54
gNB5	114°8′52.32″	22°17′6.3″	68.0	gNB15	114°8′49.64″	22°17′5.43″	10
gNB6	114°8′52.45″	22°17′5.98″	68.0	gNB16	114°8′49.93″	22°17′5.76″	10
gNB7	114°8′52.91″	22°17′6.59″	20.0	gNB17	114°8′49.68″	22°17′6.29″	21
gNB8	114°8′49.98″	22°17′5.04″	41.0	gNB18	114°8′49.63″	22°17′6.68″	21
gNB9	114°8′51.58″	22°17′5.57″	20.0	gNB19	114°8′51.44″	22°17′5.96″	68
gNB10	114°8′49.92″	22°17′5.07″	20.0	gNB20	114°8′51.43″	22°17′5.31″	68

采样点	纬度	经度	高度/m
1	114°8′49.27″	22°17′2.65″	0
2	114°8′52.2″	22°17′6.27″	0
3	114°8′50.08″	22°17′4.86″	0
4	114°8′49.08″	22°17′5.64″	0
5	114°8′52.33″	22°17′3.74″	0
6	114°8′50.78″	22°17′5.35″	0
7	114°8′50.64″	22°17′ 4.38″	0

参数	数值
加速度计零偏/mg	1.0
陀螺仪零偏/(0°/h)	65
加速度计噪声/(m·s^-1·h^-0.5)	0.02
陀螺仪噪声/(°·h^-0.5)	0.15
加速度计随机游走/(m·s^-2·Hz^-0.5)	0.000 2
陀螺仪随机游走/(°·h^-0.5)	0.034 4

定位算法	RMSE	均值
改进卡尔曼滤波	1.95	1.66
卡尔曼滤波	2.05	1.73
5G伪距多边测距	7.04	5.64

定位算法	RMSE	均值
改进EMD-CIIT+改进卡尔曼滤波	6.60	6.18
改进EMD-CIIT+传统卡尔曼滤波	7.46	7.00
传统EMD-CIIT+改进卡尔曼滤波	6.93	6.48
传统EMD-CIIT+传统卡尔曼滤波	7.64	7.14
5G伪距多边测距	9.31	8.09

INS/5G integrated navigation method based on improved EMD-CIIT denoising algorithm

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