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

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (12): 4203-4212.doi: 10.12305/j.issn.1001-506X.2024.12.29

• 制导、导航与控制 • 上一篇

基于改进EMD-CIIT降噪算法的INS/5G组合导航方法

赵云龙¹^,², 孙骞¹^,²^,*, 简鑫¹^,², 李一兵¹^,², 于飞³

1. 哈尔滨工程大学信息与通信工程学院, 黑龙江哈尔滨 150001
2. 哈尔滨工程大学先进船舶通信与信息技术重点实验室, 黑龙江哈尔滨 150001
3. 哈尔滨工程大学数学科学学院, 黑龙江哈尔滨 150001

收稿日期:2024-01-18 出版日期:2024-11-25 发布日期:2024-12-30
通讯作者: 孙骞
作者简介:赵云龙(2000—), 男, 硕士研究生, 主要研究方向为组合导航
孙骞(1988—), 男, 副教授, 博士, 主要研究方向为组合导航、通信导航一体化设计
简鑫(2001—), 男, 硕士研究生, 主要研究方向为多传感器融合
李一兵(1967—), 男, 教授, 博士, 主要研究方向为组合导航、多传感器融合、通信导航一体化设计
于飞(1974—), 男, 教授, 博士, 主要研究方向为组合导航
基金资助:
国家自然科学基金(52271311)

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

Yunlong ZHAO¹^,², Qian SUN¹^,²^,*, Xin JIAN¹^,², Yibing LI¹^,², Fe YU³

1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2. Key Laboratory of Advanced Marine Communication and Information Technology, Harbin Engineering University, Harbin 150001, China
3. College of Mathematical Sciences, Harbin Engineering University, Harbin 150001, China

Received:2024-01-18 Online:2024-11-25 Published:2024-12-30
Contact: Qian SUN

摘要/Abstract

摘要：

以惯性导航系统(inertial navigation system, INS)/5G组合导航系统为研究对象, 首先, 针对低成本的惯性传感器信噪比(signal to noise ratio, SNR)较低进而影响组合导航精度的问题, 提出一种改进阈值的清除迭代经验模态分解间隔阈值(clear iterative empirical mode decomposition interval-thresholding, EMD-CIIT)算法, 有效提升惯性传感器的SNR, 以及提升组合导航系统的定位精度。然后, 针对同频5G机会信号的同频干扰、钟差、钟漂等因素导致伪距值异常的问题, 提出一种基于自适应卡尔曼滤波的紧组合导航算法, 利用基于马氏距离的5G伪距置信度方案, 实时调整观测协方差矩阵, 从而抑制伪距异常值对定位精度的影响, 进一步提高定位的可靠性。最后, 分别采用数值仿真与实验手段验证所提方案的有效性和优越性。

关键词: 5G机会信号定位, 经验模态分解, 自适应卡尔曼滤波, 紧组合

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

中图分类号:

赵云龙, 孙骞, 简鑫, 李一兵, 于飞. 基于改进EMD-CIIT降噪算法的INS/5G组合导航方法[J]. 系统工程与电子技术, 2024, 46(12): 4203-4212.

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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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

基于改进EMD-CIIT降噪算法的INS/5G组合导航方法

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

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