A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing

With advancements in inertial navigation measurement units (IMUs), the focus of inertial navigation accuracy has shifted from hardware limitations to algorithm performance. To effectively test algorithms using high-precision IMUs, trajectory generators are essential; however, existing generators oft...

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Main Authors: Chen Chen, Weiquan Huang, He Wang, Lu Tian
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Actuators
Subjects:
Online Access:https://www.mdpi.com/2076-0825/14/3/146
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author Chen Chen
Weiquan Huang
He Wang
Lu Tian
author_facet Chen Chen
Weiquan Huang
He Wang
Lu Tian
author_sort Chen Chen
collection DOAJ
description With advancements in inertial navigation measurement units (IMUs), the focus of inertial navigation accuracy has shifted from hardware limitations to algorithm performance. To effectively test algorithms using high-precision IMUs, trajectory generators are essential; however, existing generators often lack diverse motion patterns, making them inadequate for evaluating algorithms under complex and challenging conditions, particularly for unmanned aerial vehicle (UAV) applications. To address this, we designed a high-precision trajectory generator that enhances traditional models by incorporating coning motion, paddle motion, and coning motion with angular velocity precession to simulate high-dynamic environments. Additionally, a one-sample-plus-one-previous-per-update algorithm was developed to improve the accuracy of the IMU output inversion by generating precise gyroscope and accelerometer data for processing within inertial navigation systems. The results demonstrate that both the one-sample-plus-one-previous-per-update and three-sample algorithms significantly improve the navigation accuracy under high-dynamic motion compared to single-sample algorithms. This trajectory generator effectively validates the accuracy of inertial navigation algorithms in complex conditions, particularly for UAVs, and provides a solid foundation for testing higher-precision algorithms.The proposed methodology directly supports the development of advanced actuator control systems in UAVs by enabling rigorous validation of navigation algorithms under realistic high-dynamic scenarios, a critical requirement for next-generation autonomous platforms.
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spelling doaj-art-e98a0a4dc9dc4c96b9bad7d913c6f4352025-08-20T02:11:04ZengMDPI AGActuators2076-08252025-03-0114314610.3390/act14030146A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm TestingChen Chen0Weiquan Huang1He Wang2Lu Tian3College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaCollege of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaWith advancements in inertial navigation measurement units (IMUs), the focus of inertial navigation accuracy has shifted from hardware limitations to algorithm performance. To effectively test algorithms using high-precision IMUs, trajectory generators are essential; however, existing generators often lack diverse motion patterns, making them inadequate for evaluating algorithms under complex and challenging conditions, particularly for unmanned aerial vehicle (UAV) applications. To address this, we designed a high-precision trajectory generator that enhances traditional models by incorporating coning motion, paddle motion, and coning motion with angular velocity precession to simulate high-dynamic environments. Additionally, a one-sample-plus-one-previous-per-update algorithm was developed to improve the accuracy of the IMU output inversion by generating precise gyroscope and accelerometer data for processing within inertial navigation systems. The results demonstrate that both the one-sample-plus-one-previous-per-update and three-sample algorithms significantly improve the navigation accuracy under high-dynamic motion compared to single-sample algorithms. This trajectory generator effectively validates the accuracy of inertial navigation algorithms in complex conditions, particularly for UAVs, and provides a solid foundation for testing higher-precision algorithms.The proposed methodology directly supports the development of advanced actuator control systems in UAVs by enabling rigorous validation of navigation algorithms under realistic high-dynamic scenarios, a critical requirement for next-generation autonomous platforms.https://www.mdpi.com/2076-0825/14/3/146strapdown inertial navigation (SINS)trajectory generatorhigh-dynamic motionone-sample-plus-one-previous-per-update algorithm
spellingShingle Chen Chen
Weiquan Huang
He Wang
Lu Tian
A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
Actuators
strapdown inertial navigation (SINS)
trajectory generator
high-dynamic motion
one-sample-plus-one-previous-per-update algorithm
title A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
title_full A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
title_fullStr A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
title_full_unstemmed A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
title_short A Novel High-Precision Trajectory Generator with Complex Motion Simulation for Enhanced Inertial Navigation Algorithm Testing
title_sort novel high precision trajectory generator with complex motion simulation for enhanced inertial navigation algorithm testing
topic strapdown inertial navigation (SINS)
trajectory generator
high-dynamic motion
one-sample-plus-one-previous-per-update algorithm
url https://www.mdpi.com/2076-0825/14/3/146
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