Search Results (57)

This article presents a low ripple, high voltage-conversion-ratio (VCR = 6), two-stage step-up converter intended for power-burst applications. The first boost stage raises the battery voltage to a maximum of 35 V, while the subsequent low dropout regulator (LDO) stage suppresses the ripple of the final output. Unlike conventional structures in which control circuits operate above a ground-referenced rail, the proposed shunt-current-reusing technique places most of the control circuits within a narrow floating dropout region (V_DROP) between the boost output (V_BST) and the LDO output (V_OUT), thereby achieving nearly 100% current efficiency through current recycling. Adaptive adjustment of V_DROP (0.5 V at light load and 0.65 V at heavy load) balances output ripple against the loss of the LDO stage. Consequently, the proposed converter achieves both high efficiency (>85%) and low ripple (<2 mV) over a load range from 200 μA to 100 mA, with a peak efficiency of 90.4% at a 20 mA load. Hysteretic control of the boost stage combined with the high bandwidth (BW = 1.2 MHz) of the LDO stage yields a fast transient response (<20 μs). The proposed techniques address the requirements of applications that demand high intermittent power bursts (>1 W) at high supply voltage (>20 V) while maintaining low quiescent current consumption under most load conditions (<10 mA), as exemplified by light detection and ranging (LiDAR), haptic sensors, and micro electromechanical system (MEMS) drivers. Full article

Autonomous vehicles at level 3 and above must maintain high navigation accuracy, particularly in global navigation satellite system (GNSS)-denied environments. The main innovations of this work are threefold. First, we integrate visual inertial odometry (VIO) and light detection and ranging (LiDAR) inertial odometry (LIO) as external updates to mitigate the rapid drift of micro-electromechanical system (MEMS)-based industrial-grade inertial measurement units (IMUs) during long-term GNSS outages. Second, we adopt a redundant IMU (RIMU) approach that fuses multiple low-cost IMUs to reduce sensor noise and improve reliability. Third, we propose a system calibration methodology using both static and dynamic vehicle motion to estimate extrinsic parameters (boresight angles and lever arms) of the sensors, achieving an overall boresight angle root-mean-square error of 0.04 degrees in the simulation. Experiments were conducted under a 7 min GNSS-denied scenario in an underground parking lot, allowing for comparison of the error characteristics of multi-sensor fusion schemes against a navigation-grade reference. The INS/GNSS/LIO framework achieved a two-dimensional root-mean-square position error of 1.22 m (95% position error within 2.5 m), meeting the lane-level (1.5 m) accuracy requirement under a GNSS outage exceeding 7 min without prior maps. In contrast, the RINS/GNSS/VIO framework yielded a 4.71 m 2D mean position error under the same conditions. This paper provides a quantitative comparison of the baseline error characteristics of VIO-, LIO-, and RIMU-assisted INS/GNSS fusion under a GNSS-denied navigation scenario. Full article

Moso bamboo, widely distributed in subtropical regions of China, plays an important role in forest management and carbon cycle research. However, accurate estimation of tree density and aboveground biomass (AGB) remains challenging due to the unique characteristics of Moso bamboo forests in their growth and stand structure. This research aims to develop a new procedure for bamboo tree density and AGB estimation based on UAV-LiDAR and sample plots from multiple sites through comparative analysis of the incorporation of two groups of variables—regular point cloud metrics (e.g., height, point density) and layered texture metrics—and three modeling methods—multiple linear regression (MLR), mixed-effects modeling (MEM), and hierarchical Bayesian modeling (HBM). The results showed that incorporating layered texture metrics with regular variables substantially improved the estimation accuracy of both tree density and AGB. Among these models, HBM achieved the highest predictive performance, yielding coefficient of determination (R²) values of 0.54 for tree density and 0.59 for AGB, with corresponding relative root mean square errors (rRMSE) of 21.46% and 17.97%. This study presents a novel and effective method for estimating Moso bamboo tree density and AGB using multi-site UAV-LiDAR and sample plots, offering a scientific basis for precise management and carbon stock assessment. Full article

Light Detecting and Ranging (LiDAR) has been a promising solution for autonomous vehicles. For beam-steering mechanisms, solid-state LiDAR with microelectromechanical systems (MEMS) and optical phased arrays (OPAs) have demonstrated robust and compact alternatives to mechanical LiDAR with 360° rotating mirrors. Two-dimensional optical metasurfaces can be used for phase shift, deflecting the angle in LiDAR. If a LiDAR system only needs a fixed beam direction, then static metasurfaces can be used. If a LiDAR system requires beam scanning, dynamic (tunable) metasurfaces are necessary for efficient and adaptable operation. In this review article, we will discuss the principles of metasurface beam-steering mechanisms and discuss how metasurfaces can shift the incoming light’s phase and deflect the angle. LiDAR based on metasurfaces provides promising solutions due to its flat optics feature, robust nature, and non-moving parts. Additionally, we will discuss and compare the field of view (FOV) of LiDAR based on metasurfaces. Tunable metasurfaces in LiDAR systems are crucial for real-time beam scanning, and they have advantages over traditional mechanical scanning mechanisms like faster scanning rates, increased reliability, more compact form factors, and larger fields of view. Full article

Mobile mapping systems using LiDAR technology are becoming a reliable surveying technique to generate accurate point clouds. Mobile mapping systems integrate several advanced surveying technologies. This research investigated the development of a low-cost, accurate Microelectromechanical System (MEMS)-based INS/GNSS georeferencing system for LiDAR mobile mapping applications, enabling the generation of accurate point clouds. The challenge of using the MEMS IMU is that it is contaminated by high levels of noise and bias instability. To overcome this issue, new denoising and filtering methods were developed using a wavelet neural network (WNN) and an optimal maximum likelihood estimator (MLE) method to achieve an accurate MEMS-based INS/GNSS integration navigation solution for LiDAR mobile mapping applications. Moreover, the final accuracy of the MEMS-based INS/GNSS navigation solution was compared with the ASPRS standards for geospatial data production. It was found that the proposed WNN denoising method improved the MEMS-based INS/GNSS integration accuracy by approximately 11%, and that the optimal MLE method achieved approximately 12% higher accuracy than the forward-only navigation solution without GNSS outages. The proposed WNN denoising outperforms the current state-of-the-art Long Short-Term Memory (LSTM)–Recurrent Neural Network (RNN), or LSTM-RNN, denoising model. Additionally, it was found that, depending on the sensor–object distance, the accuracy of the optimal MLE-based MEMS INS/GNSS navigation solution with WNN denoising ranged from 1 to 3 cm for ground mapping and from 1 to 9 cm for building mapping, which can fulfill the ASPRS standards of classes 1 to 3 and classes 1 to 9 for ground and building mapping cases, respectively. Full article

As a core component of MEMS LiDAR, the 2D MEMS mirror, with high-precision optical angle detection, is a key technology for radar scanning and imaging. Existing piezoresistive detection schemes of mirrors suffer from high fabrication complexity, high temperature sensitivity, and a limited accuracy of only 0.08°, failing to meet the requirements for vehicular and airborne scanning applications. This study focuses on a two-dimensional electromagnetic MEMS mirror. Based on the reflection principles of geometric optics, angle detection schemes with photodiode (PD) arrays are analyzed. A novel four-quadrant optical measurement sensor featuring a 16-PD array is proposed. This design replaces conventional large-area PDs with a compact PD array, effectively mitigating nonlinearity and low accuracy issues caused by oversized PD trenches and edge dimensions. High-precision detection of the mirror’s deflection angle is achieved by measuring the current variations induced by the reflected spot position on the PDs in each quadrant. The experimental results demonstrate that the 16-PD array optical angle sensor achieves an accuracy between 0.03° and 0.036° over a detection range of ±8°. Full article

Many multi-target tracking applications (e.g., tracking multiple targets with LiDAR or millimeter-wave radar) are challenged by closely spaced targets. In this work, we propose a method for the tracking of multiple extended targets or unresolvable group targets in such scenarios. The approach builds on the cardinality probability hypothesis density (CPHD) filtering framework for computational efficiency, models the target’s extent with the multiplicative error model (MEM), and uses variational Gaussian mixture model (VGMM)-derived responsibilities to drive probabilistic data association (PDA) measurement updates. This effectively mitigates state fusion between closely spaced targets and yields more accurate state estimation. In experiments on diverse simulated and real datasets, the proposed method consistently outperforms existing approaches, achieving the lowest localization, shape estimation, and cardinality estimation errors while maintaining an acceptable runtime and scalability. Full article

Electromagnetic micro-electro-mechanical system (MEMS) micromirrors are widely used in optical scanning systems but often encounter mechanical crosstalk due to the use of shared drive coils. This phenomenon leads to parasitic motion along the slow axis during fast-axis operation, resulting in undesirable elliptical scanning patterns that degrade image quality. To tackle this issue, a hybrid actuation scheme is proposed in which a piezoelectric actuator drives the fast axis through an S-shaped spring structure, achieving a resonance frequency of 792 Hz, while the slow axis is independently driven by an electromagnetic actuator operating in quasi-static mode. Finite element simulations and experimental measurements validate that the proposed decoupled design significantly suppresses mechanical crosstalk. When the fast axis is driven to a 40° optical scan angle, the hybrid system reduces the parasitic slow-axis deflection (typically around 1.43°) to a negligible level, thereby producing a clean single-line scan. The piezoelectric fast axis exhibits a quality factor of Q = 110, while the electromagnetic slow axis achieves a linear 20° deflection at 20 Hz. This hybrid design facilitates a distortion-free field of view measuring 40° × 20° with uniform line spacing, presenting a straightforward and effective solution for high-precision scanning applications such as LiDAR (Light Detection and Ranging) and structured light projection. Full article

Simultaneous Localization and Mapping (SLAM) is crucial for the safe navigation of autonomous systems. Its accuracy is not based solely on the robustness of the algorithm employed or the metrological performances of the sensor, but rather on a combination of both factors. In this work, we present a comprehensive comparison framework for evaluating LiDAR-SLAM systems, focusing on key performance indicators including absolute trajectory error, uncertainty, number of tracked features, and computational time. Our case study compares two LiDAR-inertial SLAM configurations: one based on a motorized optomechanical scanner (the Ouster OS1) with a 360° field of view and the other based on MEMS scanners (the Livox Horizon) with a limited field of view and a non-repetitive scanning pattern. The sensors were mounted on a UGV for the experiments, where data were collected by driving the UGV along a predefined path at different speeds and angles. Despite substantial differences in field of view, detection range, and noise, both systems demonstrated comparable trajectory estimation performance, with average absolute trajectory errors of 0.25 m for the Livox-based system and 0.24 m for the Ouster-based system. These findings underscore the importance of sensor–algorithm co-design and demonstrate that even cost-effective, lower-field-of-view solutions can deliver competitive SLAM performance in real-world conditions. Full article

Lidar has been extensively used in various applications, such as autonomous driving, robot navigation, and drone obstacle avoidance, due to its advantages of a high resolution, high-ranging accuracy, and strong anti-interference ability. The micro-electro-mechanical systems (MEMS) lidar technology approach has gained popularity due to its miniaturization and semi-solid state. However, the small scanning angle of the MEMS scanning micromirror and the associated radar system cause issues, such as a limited scanning range and low spatial resolution, which hinder the wider use of MEMS lidar. To address the problems caused by the small scanning angle of the MEMS micromirror and the limitations of the current optical system, this study suggests a new MEMS lidar transmitting optical system that offers a wide scanning angle and high spatial resolution. It is based on an array reflector group and a Fresnel lens, which enables the large-angle scanning of the target area while maintaining high spatial resolution. The scanning range is 120° × 60°, the spatial resolution is 0.05° × 0.25°, and the beam-filling ratio reaches 90.63%. Full article

This article aims to utilize a microelectromechanical system (MEMS) to modulate coupling behavior of silicon nitride (Si₃N₄) waveguides to perform an optical switch based on a directional coupling (DC) mechanism. There are two states of the switch. First state, a Si₃N₄ wire is initially positioned up suspended in the air. In the second state, this wire will be moved down to be placed between two arms of the DC waveguides, changing the coupling behavior to achieve bar and cross states of the optical switch function. In the future, the MEMS will be used to move this wire down. In this work, we present simulations of the two static states to optimize the DC structure parameters. Based on the simulated results, the device size is 8.8 μm × 55 μm. The insertion loss is calculated to be approximately 0.24 dB and 0.33 dB, the extinction ratio is approximately 24.70 dB and 25.46 dB, and the crosstalk is approximately −24.60 dB and −25.56 dB, respectively. In the C band of optical communication, the insertion loss ranges from 0.18 dB to 0.47 dB. As such, this device will exhibit excellent optical switch performance and provide advantages in many integrated optics-related optical systems applications. Furthermore, it can be used in optical communications, data centers, LiDAR, and so on, enhancing important reference value for such applications. Full article

Aircraft engines are regularly inspected with borescopes to detect faults at an early stage and maintain airworthiness. A critical part of this inspection process is accurately measuring any detected damage to determine whether it exceeds allowable limits. Current state-of-the-art borescope measurement techniques—primarily stereo camera systems and pattern projection—face significant challenges when engines lack sufficient surface features or when illumination is inadequate for reliable stereo matching. MEMS-based 3D scanners address these issues by focusing laser light onto a small spot, reducing dependency on surface texture and improving illumination. However, miniaturized MEMS-based scanner borescopes that can pass through standard engine inspection ports are not yet available. This work examines the essential steps to downsize MEMS 3D scanners for direct integration into borescope inspections, thereby enhancing the accuracy and reliability of aircraft engine fault detection. Full article

A MEMS scanning mirror is a beam scanning device based on MEMS technology, which plays an important role in the fields of Lidar, medical imaging, laser projection display, and so on. The accurate measurement of the scanning mirror index can verify its performance and application scenarios. This paper designed and built a scanning mirror benchmark platform based on a two-dimensional position-sensitive detector (PSD), which can accurately measure the deflection angle, resonance frequency, and angular resolution of the scanning mirror, and described the specific test steps of the scanning mirror parameters, which can meet the two-dimensional measurement. Secondly, this paper analyzed and calculated the angular test uncertainty of the designed test system. After considering the actual optical alignment error and PSD measurement error, when the distance between the PSD and MEMS scanning mirror is 100 mm, the range of mechanical deflection angle that can be measured is (−6.34°, +6.34°). When the mechanical deflection angle of the scanning mirror is 0.01°, the accuracy measured by the test system is 0.00097°, and when the mechanical deflection of the scanning mirror is 6.34°, the accuracy measured by the test system is 0.011°. The test platform has high accuracy and can measure the parameters of the scanning mirror accurately. Full article

MEMS-based LiDAR has showcased extensive application potential in the autonomous driving sector, attributed to its cost-effectiveness, compactness, and seamless integration capabilities. However, MEMS LiDAR suffers from a short detection range, due to the small receiving aperture of the MEMS mirror. Our early study attempted to increase the detection range of MEMS LiDAR with a semi-coaxial design. In this paper, we further investigate the synchronization method for large-aperture electromagnetic MEMS mirrors, in which a synchronous motion transfer model of electromagnetic MEMS mirrors is constructed. The results of the simulations and experiments demonstrate that two electromagnetic MEMS mirrors are synchronous with an aperture of 60 ${\mathsf{\pi }\mathrm{mm}}^2$, FoV of 60°, and scanning frequency of 220 Hz. The entire synchronization process of the electromagnetic MEMS mirrors is completed within 10 s, which verifies the feasibility of synchronizing large-aperture electromagnetic MEMS mirrors to increase the detection range of MEMS LiDAR. Full article

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