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New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition

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A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A：Physics".

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 16845

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Dr. Changhui Jiang

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Guest Editor

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: hyperspectral LiDAR; GNSS; INS; Kalman filter; mobile mapping
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Prof. Dr. Shuai Chen

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Guest Editor

School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
Interests: inertial navigation system; GNSS/INS integration; GNSS
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Dr. Yuwei Chen

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Guest Editor

Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, 02430 Masala, Finland
Interests: hyperspectral LiDAR; mobile mapping
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Dr. Jianxin Jia

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Guest Editor

Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, Vuorimiehentie 5, FI-02150 Espoo, Finland
Interests: hyperspectral imaging technology; hyperspectral LiDAR; infrared imaging; machine learning
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Special Issue Information

Dear Colleagues,

MEMS technology opens up a new avenue for manufacturing low-cost and small-volume inertial measurement units. Micro inertial sensors are ubiquitous, and can be found in smartphones, cars, and smartwatches. Signals for the micro inertial sensors are sampled and processed for various applications, e.g., health monitoring, vibration sensing, position, and navigation. For position and navigation applications in particular, micro inertial sensors are utilized for measuring the position, velocity, and attitude information, i.e., the accelerometer is utilized to detect the pedestrian step and update the position; the micro inertial sensors are employed in a car to integrate with the GNSS to provide more reliable positional information; the UAV measures its attitude using the measurements from the micro inertial sensor. Minimizing the micro inertial sensor volume and improving the quality of its measurements have attracted much attention in the scientific community. New principles, advanced manufacturing technology, and novel signal processing algorithms are expected to improve its performance and extend its applications. This Special Issue of Micromachines aims to provide a platform for researchers to publish innovative work on advances, methods, and applications as they pertain to micro inertial sensors. Potential topics include, but are not limited to, the following:

Deep Learning methods for processing micro inertial sensor measurements.
New methods for GNSS/MEMS IMU integration and MEMS IMU auto-calibration.
New manufacturing technology for MEMS IMU Gyroscope array or accelerometer array technology.
New applications for MEMS IMUMEMS IMU-based pedestrian dead reckoning.
Advanced methods for MEMS IMU noise modeling and its position error suppression without GNSS.

Dr. Changhui Jiang
Prof. Dr. Shuai Chen
Dr. Yuwei Chen
Dr. Jianxin Jia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

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Dr. Jianxin Jia
Dr. Yuwei Chen
Dr. Changhui Jiang
Prof. Dr. Shuai Chen
Guest Editors

Manuscript Submission Information

Keywords

micro inertial sensor
MEMS IMU
position
navigation
deep learning
GNSS

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New Advances, Methods, and Applications for Micro Inertial Sensors in Micromachines (8 articles)

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Research

20 pages, 5658 KiB

Open AccessArticle

Microelectromechanical System Resonant Devices: A Guide for Design, Modeling and Testing

by Carolina Viola, Davide Pavesi, Lichen Weng, Giorgio Gobat, Federico Maspero and Valentina Zega

Micromachines 2024, 15(12), 1461; https://doi.org/10.3390/mi15121461 - 30 Nov 2024

Viewed by 3402

Abstract

Microelectromechanical systems (MEMSs) are attracting increasing interest from the scientific community for the large variety of possible applications and for the continuous request from the market to improve performances, while keeping small dimensions and reduced costs. To be able to simulate a priori and in real time the dynamic response of resonant devices is then crucial to guide the mechanical design and to support the MEMSs industry. In this work, we propose a simplified modeling procedure able to reproduce the nonlinear dynamics of MEMS resonant devices of arbitrary geometry. We validate it through the fabrication and testing of a cantilever beam resonator functioning in the nonlinear regime and we employ it to design a ring resonator working in the linear regime. Despite the uncertainties of a fabrication process available in the university facility, we demonstrate the predictability of the model and the effectiveness of the proposed design procedure. The satisfactory agreement between numerical predictions and experimental data proves indeed the proposed a priori design tool based on reduced-order numerical models and opens the way to its practical applications in the MEMS industry. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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17 pages, 4331 KiB

Open AccessArticle

A Method for Measuring the Error Rules in Visual Inertial Odometry Based on Scene Matching Corrections

by Haiqiao Liu, Zichao Gong, Jinxu Shen, Ya Li and Qing Long

Micromachines 2024, 15(11), 1362; https://doi.org/10.3390/mi15111362 - 11 Nov 2024

Cited by 1 | Viewed by 1637

Abstract

To address problems in the integrated navigation error law of unmanned aerial vehicles (UAVs), this paper proposes a method for measuring the error rule in visual inertial odometry based on scene matching corrections. The method involves several steps to build the solution. Firstly, separate models were constructed for the visual navigation model, the Micro-Electromechanical System (MEMS) navigation model, and the scene matching correction model. Secondly, an integrated navigation error measurement model based on scene matching corrections and MEMS navigation was established (the MEMS+SM model). Finally, an integrated navigation error measurement model based on scene matching corrections, visual navigation, and MEMS navigation was constructed (the VN+MEMS+SM model). In the experimental part, this paper first calculates the average error of the VN+MEMS+SM model and the MEMS+SM model under different scene matching accuracies, scene matching times, and MEMS accuracies. The results indicate that, when the scene matching accuracy is less than 10 m and the scene matching time is less than 10 s, the errors of the VN+MEMS+SM model and the MEMS+SM model are approximately equal. Furthermore, the relationship between the scene matching time and the scene matching accuracy in the EMS+SM model was calculated. The results show that, when the scene matching time is 10 s, the critical values of the image matching accuracies required to achieve average errors of 10 m, 30 m, and 50 m are approximately 160 m, 240 m, and 310 m. Additionally, when the MEMS accuracy is 150, the scene matching accuracy is 50 m, and the scene matching time exceeds 135 s, the average error of the VN+MEMS+SM model will be smaller than that of the MEMS+SM model. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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24 pages, 13744 KiB

Open AccessArticle

When-to-Loop: Enhanced Loop Closure for LiDAR SLAM in Urban Environments Based on SCAN CONTEXT

by Xu Xu, Lianwu Guan, Jianhui Zeng, Yunlong Sun, Yanbin Gao and Qiang Li

Micromachines 2024, 15(10), 1212; https://doi.org/10.3390/mi15101212 - 29 Sep 2024

Viewed by 3482

Abstract

Global Navigation Satellite Systems (GNSSs) frequently encounter challenges in providing reliable navigation and positioning within urban canyons due to signal obstruction. Micro-Electro-Mechanical System (MEMS) Inertial Measurement Units (IMUs) offers an alternative for autonomous navigation, but they are susceptible to accumulating errors. To mitigate these influences, a LiDAR-based Simultaneous Localization and Mapping (SLAM) system is often employed. However, these systems face challenges in drift and error accumulation over time. This paper presents a novel approach to loop closure detection within LiDAR-based SLAM, focusing on the identification of previously visited locations to correct time-accumulated errors. Specifically, the proposed method leverages the vehicular drivable area and IMU trajectory to identify significant environmental changes in keyframe selection. This approach differs from conventional methods that only rely on distance or time intervals. Furthermore, the proposed method extends the SCAN CONTEXT algorithm. This technique incorporates the overall distribution of point clouds within a region rather than solely relying on maximum height to establish more robust loop closure constraints. Finally, the effectiveness of the proposed method is validated through experiments conducted on the KITTI dataset with an enhanced accuracy of 6%, and the local scenarios exhibit a remarkable improvement in accuracy of 17%, demonstrating improved robustness in loop closure detection for LiDAR-based SLAM. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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19 pages, 7149 KiB

Open AccessArticle

Continuous High-Precision Positioning in Smartphones by FGO-Based Fusion of GNSS–PPK and PDR

by Amjad Hussain Magsi, Luis Enrique Díez and Stefan Knauth

Micromachines 2024, 15(9), 1141; https://doi.org/10.3390/mi15091141 - 11 Sep 2024

Viewed by 3885

Abstract

The availability of raw Global Navigation Satellites System (GNSS) measurements in Android smartphones fosters advancements in high-precision positioning for mass-market devices. However, challenges like inconsistent pseudo-range and carrier phase observations, limited dual-frequency data integrity, and unidentified hardware biases on the receiver side prevent the ambiguity resolution of smartphone GNSS. Consequently, relying solely on GNSS for high-precision positioning may result in frequent cycle slips in complex conditions such as deep urban canyons, underpasses, forests, and indoor areas due to non-line-of-sight (NLOS) and multipath conditions. Inertial/GNSS fusion is the traditional common solution to tackle these challenges because of their complementary capabilities. For pedestrians and smartphones with low-cost inertial sensors, the usual architecture is Pedestrian Dead Reckoning (PDR)+ GNSS. In addition to this, different GNSS processing techniques like Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) have also been integrated with INS. However, integration with PDR has been limited and only with Kalman Filter (KF) and its variants being the main fusion techniques. Recently, Factor Graph Optimization (FGO) has started to be used as a fusion technique due to its superior accuracy. To the best of our knowledge, on the one hand, no work has tested the fusion of GNSS Post-Processed Kinematics (PPK) and PDR on smartphones. And, on the other hand, the works that have evaluated the fusion of GNSS and PDR employing FGO have always performed it using the GNSS Single-Point Positioning (SPP) technique. Therefore, this work aims to combine the use of the GNSS PPK technique and the FGO fusion technique to evaluate the improvement in accuracy that can be obtained on a smartphone compared with the usual GNSS SPP and KF fusion strategies. We improved the Google Pixel 4 smartphone GNSS using Post-Processed Kinematics (PPK) with the open-source RTKLIB 2.4.3 software, then fused it with PDR via KF and FGO for comparison in offline mode. Our findings indicate that FGO-based PDR+GNSS–PPK improves accuracy by 22.5% compared with FGO-based PDR+GNSS–SPP, which shows smartphones obtain high-precision positioning with the implementation of GNSS–PPK via FGO. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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21 pages, 5015 KiB

Open AccessArticle

The Improved Method for Indoor 3D Pedestrian Positioning Based on Dual Foot-Mounted IMU System

by Haonan Jia, Baoguo Yu, Hongsheng Li, Shuguo Pan, Jun Li, Xinjian Wang and Lu Huang

Micromachines 2023, 14(12), 2192; https://doi.org/10.3390/mi14122192 - 30 Nov 2023

Cited by 5 | Viewed by 1376

Abstract

Micro-Electro-Mechanical System (MEMS) inertial sensors, characterized by their small size, low cost, and low power consumption, are commonly used in foot-mounted wearable pedestrian autonomous positioning systems. However, they also have drawbacks such as heading drift and poor repeatability. To address these issues, this paper proposes an improved pedestrian autonomous 3D positioning algorithm based on dual-foot motion characteristic constraints. Two sets of small-sized Inertial Measurement Units (IMU) are worn on the left and right feet of pedestrians to form an autonomous positioning system, each integrated with low-cost, low-power micro-inertial sensor chips. On the one hand, an improved adaptive zero-velocity detection algorithm is employed to enhance discrimination accuracy under different step-speed conditions. On the other hand, considering the dual-foot gait characteristics and the height difference feature during stair ascent and descent, horizontal position update algorithms based on dual-foot motion trajectory constraints and height update algorithms based on dual-foot height differences are, respectively, designed. These algorithms aim to re-correct the pedestrian position information updated at zero velocity in both horizontal and vertical directions. The experimental results indicate that in a laboratory environment, the 3D positioning error is reduced by 93.9% compared to unconstrained conditions. Simultaneously, the proposed approach enhances the accuracy, continuity, and repeatability of the foot-mounted IMU positioning system without the need for additional power consumption. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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11 pages, 8508 KiB

Open AccessArticle

Electrical Characteristics of 3D Trench Electrode Germanium Detector with Nested Complementary Cathodes

by Mingyang Wang, Zheng Li, Bo Xiong and Yongguang Xiao

Micromachines 2023, 14(11), 2051; https://doi.org/10.3390/mi14112051 - 1 Nov 2023

Viewed by 1220

Abstract

High-purity germanium detectors, widely employed in fields such as aerospace applications based on radiation detection principles, have garnered attention due to their broad detection range and fast response time. However, these detectors often require larger sensitive area volumes to achieve larger signals and higher detection efficiency. Additionally, the large distance between the electrodes contributes to an issue of incomplete charge collection, which significantly restricts their application in space applications. To enhance the electrical performance of high-purity germanium detectors, this study introduces a strategy: designing the detector’s cathode electrode into a 3D trench shape with nested complementary cathodes. This design greatly reduces the electrode spacing, endowing the detector with superior electrical characteristics, such as a smaller dead zone and improved charge collection efficiency. Performance simulations of the novel detector structure were conducted using the semiconductor device simulation software Sentaurus TCAD (2019.03). The simulation results confirmed that the nested complementary 3D trench electrode high-purity germanium detector exhibits excellent electrical features, including a larger sensitive area volume, rapid charge collection, and good cell isolations. This approach has the potential to effectively expand the application scenarios of high-purity germanium detectors. Depending on different operational environments and requirements, nested complementary 3D trench electrode high-purity germanium detectors of appropriate structural dimensions can be chosen. The experimental findings of this study hold a significant reference value for enhancing the overall structure of high purity germanium detectors and facilitating their practical application in the future. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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11 pages, 4164 KiB

Open AccessArticle

Optimized Design of a Hexagonal Equal Gap Silicon Drift Detector with Arbitrary Surface Electric Field Spiral

by Jiaxiong Sun, Zheng Li, Xiaodan Li, Manwen Liu and Hongfei Wang

Micromachines 2023, 14(10), 1943; https://doi.org/10.3390/mi14101943 - 18 Oct 2023

Cited by 1 | Viewed by 1143

Abstract

In our previous studies, the silicon drift detector (SDD) structure with a constant spiral ring cathode gap (g) and a given surface electric field has been partially investigated based on the physical model that gives an analytical solution to the integrals in the calculations. Those results show that the detector has excellent electrical characteristics with a very homogeneous carrier drift electric field. In order to cope with the implementation of the theoretical approach with a complete set of technical parameters, this paper performs different theoretical algorithms for the technical implementation of the detector performance using the Taylor expansion method to construct a model for cases where the parameter “j” is a non-integer, approximating the solution with finite terms. To verify the accuracy of this situation, we performed a simulation of the relevant electrical properties using the Sentaurus TCAD tool 2018. The electrical properties of the single and double-sided detectors are first compared, and then the effects of different equal gaps g (g = 10 μm, 20 μm, and 25 μm, respectively) on the electrical properties of the double-sided detectors are analyzed and demonstrated. By analyzing and comparing the electrical characteristics data from the simulation results, we can show that the double-sided structure has a larger transverse drift electric field, which improves the spatial position resolution as well as the response speed. The effect of the gap size on the electrical characteristics of the detector is also analyzed by analyzing three different gap bifacial detectors, and the results show that a 10 μm equal gap is the optimal design. Such results can be used in applications requiring large-area SDD, such as the pulsar X-ray autonomous navigation. in the future to provide navigation and positioning space services for spacecraft deep-space exploration. Full article

(This article belongs to the Special Issue New Advances, Methods, and Applications for Micro Inertial Sensors, 2nd Edition)

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