Spherical Inertial Sensor for Measuring Particle-Scale Interactions in Geomorphic Flows with Full Kinematic Equivalence

Autonomous landing system is an important part of unmanned aerial vehicle (UAV) autonomous flight. Large fixed‐wing UAVs often consume more onboard space and computing resources. With the improvement of system integration and the reduction of high‐performance global navigation satellite system (GNSS) costs, real‐time kinematic (RTK) GNSS has been widely used in small‐scale and low‐cost fixed‐wing UAVs. This article uses less onboard hardware and ground facility requirements to design an autonomous taking off and landing system suitable for general fixed‐wing UAVs. A modified gradient descent attitude estimator, based on microelectromechanical system (MEMS) inertial measurement unit (IMU) and RTK GNSS, and a guidance method based on a tracking differentiator for using in a high dynamic environment are proposed, and circular path following and vertical transient simulations are performed. The simulation results show that this method can improve attitude estimation accuracy, motion control accuracy, and altitudinal transient quality. Finally, the actual flight test verifies its feasibility in the actual environment. The flight test results prove that it is feasible to implement the autonomous landing process of fixed‐wing UAV with the proposed system and method.

This paper presents a navigation grade micro-electromechanical system (MEMS) inertial measurement unit (IMU) that was successfully applied for the first time in the Lobster-Eye X-ray Satellite in July 2020. A six-axis MEMS gyroscope redundant configuration is adopted in the unit to improve the performance through mutual calibration of a set of two-axis gyroscopes in the same direction. In the paper, a satisfactory precision of the gyroscope is achieved by customized and self-calibration gyroscopes whose parameters are adjusted at the expense of bandwidth and dynamics. According to the in-orbit measured data, the MEMS IMU provides an outstanding precision of better than 0.02 °/h (1σ) with excellent bias instability of 0.006 °/h and angle random walk (ARW) of around 0.003 °/h1/2. It is the highest precision MEMS IMU for commercial aerospace use ever publicly reported in the world to date.

Attitude determination based on a micro-electro-mechanical system inertial measurement unit (MEMS-IMU) has attracted extensive attention. The non-gravitational components of the MEMS-IMU have a significant effect on the accuracy of attitude estimation. To improve the attitude estimation of low-dynamic vehicles under uneven soil conditions or vibrations, a robust Kalman filter (RKF) was developed and tested in this paper, where the noise covariance was adaptively changed to compensate for the external acceleration of the vehicle. The state model for MEMS-IMU attitude estimation was initially constructed using a simplified direction cosine matrix. Subsequently, the variance of unmodeled external acceleration was estimated online based on filtering innovations of different window lengths, where the acceleration disturbance was addressed by tradeoffs in time-delay and prescribed computation cost. The effectiveness of the RKF was validated through experiments using a three-axis turntable, an automatic vehicle, and a tractor tillage test. The turntable experiment demonstrated that the angle result of the RKF was 0.051° in terms of root mean square error (RMSE), showing improvements of 65.5% and 29.2% over a conventional KF and MTi-300, respectively. The dynamic attitude estimation of the automatic vehicle showed that the RKF achieves smoother pitch angles than the KF when the vehicle passes over speed bumps at different speeds; the RMSE of pitch was reduced from 0.875° to 0.460° and presented a similar attitude trend to the MTi-300. The tractor tillage test indicated that the RMSE of plough pitch was improved from 0.493° with the KF to 0.259° with the RKF, an enhancement of approximately 47.5%, illustrating the superiority of the RKF in suppressing the external acceleration disturbances of IMU-based attitude estimation.

Due to the need for providing low-cost, small-size, and high-reliability calibration solution around the clock independently, the Micro-Electro-Mechanical System (MEMS) inertial measurement unit (IMU) is a hot topic currently. In this paper, we propose a new calibration method based on MEMS IMU with the assistance of the FOG IMU. Different from the traditional MEMS IMU calibration, a Four-Position-and-Three-Rotation (FPTR) calibration sequence is designed in the conditions of lacking turntable. The simulation result shows that all 24 calibration parameters converge through the calibration rotation scheme. An experiment result of qualitative analysis is presented, by comparing the traditional method and proposed calibration method, which reveals the repeatability and stability of the proposed method. In practical applications, this FPTR calibration method can effectively reduce the calibration time and improve the experimental efficiency. In summary, the proposed method is suitable for the mass production calibration of MEMS IMU, and possesses the ability to calibrate full parameters of MEMS IMU at once without turntable or other devices. The research outcomes can provide a practical basis for MEMS IMU plus FOG IMU calibration.

The Unaided Single Frequency/Single Epoch Global Navigation Satellite System (SF/SE GNSS) model is the most challenging scenario for ambiguity resolution in the GNSS attitude determination application. To improve the performance of SF/SE-GNSS ambiguity resolution without excessive cost, the Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS-IMU) is a proper choice for the auxiliary sensor that carries out the inertial attitude augmentation. Firstly, based on the SF/SE-GNSS compass model, the Inertial Derived Baseline Vector (IDBV) is defined to connect the MEMS-IMU attitude measurement with the SF/SE-GNSS ambiguity search space, and the mechanism of inertial attitude augmentation is revealed from the perspective of geometry. Then, through the quantitative description of model strength by Ambiguity Dilution of Precision (ADOP), two ADOPs are specified for the unaided SF/SE-GNSS compass model and its inertial attitude augmentation counterparts, respectively, and a sufficient condition is proposed for augmenting the SF/SE-GNSS model strength with inertial attitude measurement. Finally, in the framework of an integer aperture estimator with fixed failure rate, the performance of SF/SE-GNSS ambiguity resolution with inertial attitude augmentation is analyzed when the model strength is varying from strong to weak. The simulation results show that, in the SF/SE-GNSS attitude determination application, MEMS-IMU can satisfy the requirements of ambiguity resolution with inertial attitude augmentation.

The field of automatic driving has always been a research hotspot. Based on inertial and odometer, dead reckoning is used to navigate for L4 and above level autonomous vehicles with less human intervention when GPS is blocked. The navigation accuracy is mainly determined by the alignment error and the drift accumulated over time. In this paper, we proposed a novel method to achieve initial alignment of inertial navigation for L4 and above level autonomous vehicles. The alignment is accomplished with a MEMS inertial measurement unit (MIMU) and single antenna global positioning system real-time kinematic (GPS-RTK). By matching the trajectory obtained from MIMU dead reckoning with the trajectory obtained from RTK, the initial heading angle is obtained, and the heading angle accuracy is improved through multiple iterations. In the case of RTK precision decreasing, the MIMU can still achieve lane-level navigation after the initial alignment. Because the alignment is accomplished in motion, there is no need for additional static alignment time before the vehicle starts. The field experiment results show that the method could achieve fast initial alignment in a few seconds in moving state with an alignment accuracy of 0.05°.

To improve the accuracy and robustness of the inertial navigation systems (INS) for wheeled robots without adding additional component cost, we propose Wheel-INS, a complete dead reckoning (DR) solution based on a wheel-mounted microelectromechanical system (MEMS) inertial measurement unit (IMU) in this article. There are two major advantages of mounting IMU to the center of a non-steering wheel. Firstly, the gyroscope outputs can be used to calculate the wheel speed, so as to replace the traditional odometer to mitigate the error drift of INS. Secondly, with the rotation of the wheel, the constant bias error of the inertial sensor can be canceled to some extent. The installation scheme of the wheel-mounted MEMS IMU (Wheel-IMU), the system characteristics, and the DR error analysis are all discussed in this paper. Experimental results show that the maximum position drift of Wheel-INS in the horizontal plane is less than 1.8% of the total traveled distance, reduced by 23% compared to the conventional odometer-aided INS (ODO/INS). In addition, Wheel-INS outperforms ODO/INS because of its inherent immunity to constant bias error of gyroscopes. The source code and experimental datasets have been made available to the community ( <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/i2Nav-WHU/Wheel-INS</uri> ).

Moment of Inertia Measurement of a CubeSat Through Object Motion Tracking of Trifilar Pendulum Oscillations

Piezoelectric micromechanical actuators are featured with a low driving voltage, fast response and large-range output, which make them desirable for applications of long-term drift error self-calibration in microelectromechanical systems (MEMS) inertial measurement units. A micromechanical vibration platform supported by four folded beams and excited by 32 partitioned electrodes based on PZT film is presented in this paper. PZT-silicon on insulator based wafer-level MEMS process and packaging technique are conducted in the manufacture and integration for the micro vibration platform. The six-degree-of-freedom (6 DOF) motion of the micro vibration platform is experimentally verified. In addition, the motion behavior control, damping characteristics and fatigue characteristics are analyzed. The 6 DOF micro vibration platform has a stable capability of large-range dynamic output.

Understanding wave breaking phenomena is a challenging problem that still lacks satisfactory understanding. The present paper is concerned with the development of novel instrumentation adapted to obtain Lagrangian field measurements of essential variables that are intimately related to the physics of wave breaking. These miniature (6.4 cm) Lagrangian drifters are equipped with micro-electromechanical systems (MEMS) inertial measurement units (IMUs) that record acceleration, angular rate and magnetic field data at rapid sampling rates (100 Hz). Using a quaternion-based sensor fusion algorithm, multiple sensor data is filtered in postprocessing procedures to obtain the best possible estimates of particle orientation and acceleration. We show that the developed instrumentation is able to collect meaningful data of inertial particle dynamics in a controlled laboratory flow, where the instrumented particle trajectories are benchmarked against an analytical representation of the flow. Results indicate that dead reckoning errors grow quadratically in time and that for a typical wave overturning event trajectory estimates are expected to remain within a radius $r 0.7 m with a 95% confidence level. Also, special attention is given to gyroscope reliability during the actual wave breaking process through an empirical evaluation of gyroscope performance in plunging waves. Angular rate measurements from two separate gyroscopes mounted inside the same drifter show high agreement leading to the conclusion that gyroscope errors arising from wave induced vibrations are negligible. Finally, we report on the first ever Lagrangian field observations of inertial particle dynamics in plunging waves with heights on the order of 2 m. We expect that further development of the technology and analysis tools presented herein could revolutionize our understanding of the hydrodynamics of breaking waves.

Based on a micro-electromechanical system (MEMS) inertial measurement unit (IMU), ultra-wide band (UWB) and global navigation satellite system (GNSS), a hybrid indoor/outdoor positioning and orientation system is described in this paper. The dual-antenna real time kinematic (RTK) attitude measurement technique was employed to improve the precision of orientation. Considering the possibility that GNSS and UWB signals may be lost due to the influence of indoor/outdoor different complex environments, a federated Kalman filter was used. The experimental result shows that the hybrid system can obtain stable and reliable vehicle position and orientation information and can effectively resist the influence of unreliable GNSS and UWB signals caused by environmental changes.

Railway track is never perfect, as rail distortions, namely, geometric irregularities, exist at all locations along the track. However, these distortions can be regarded as valuable indicators for train localization, since track irregularities present location-dependent characteristics, the measurements of which using onboard sensors are repeatable for the same track. In this research, we study the possibility of determining a train’s position by matching the track irregularity measurements to a predefined map. A train-borne experiment on a real track is used to preliminarily demonstrate the feasibility, evaluate the performance and determine the key parameters for practical implementation. The results show that a submeter longitudinal localization accuracy can be achieved even when using a low-cost cabin-mounted microelectromechanical system (MEMS) inertial measurement unit (IMU), which measures the train’s responses to track irregularities. The proposed method can enhance the positioning accuracy and improve the robustness of multisensory train localization systems.

Recent advances in acoustic navigation methods are enabling extended autonomous underwater vehicles' (AUVs) mission time while maintaining their XY position error within appropriate limits. Furthermore, while advances in inertial sensor technology are drastically lowering the size, power consumption, and cost of these sensors, these sensors remain noisy and accrue error over time. This paper builds on the research and recent developments in single beacon one-way-travel-time acoustic navigation and investigates the degree of bounding position error for small AUVs with a minimal navigation strapdown sensor suite, relying on a consumer grade microelectromechanical system inertial measurement unit (IMU) and a vehicle's dynamic model velocity. An implementation of an extended Kalman filter that includes IMU bias estimation and coupled with a range filter is obtained in the field on two types of AUVs. Results from these field trials in controlled environments and ocean show that the reported navigation solution possesses an accuracy comparable to existing methods.

Kyphosis, an idiopathic disease, occurs in swine and humans. We induced kyphosis by altering maternal dietary vitamin D (D) and pig dietary D, Ca and P. The objective was to characterize bone traits and gene expression in the kyphosis model and assess maternal carryover effects. Traits from mechanical tests to characterize femur integrity are reported herein. Sows were fed diets with 0, 325 or 1750 IU D/kg (n = 6, 8, or 9/diet). At weaning (23 ± 2 d) pigs were fed diets with 0 (-D) or 280 (+D) IU D/kg, each with 95% (95P) or 120% (120P) of the P requirement. Pigs were killed at birth (n = 23), weaning (n = 22), and at the end of nursery (n = 185) for bone and tissue analysis. Excised femurs were subjected to a 4-point bending test to determine bending moment (BM), stress, strain, and modulus of elasticity (ME) at the yield point of load deformation curves. Mass moment of inertia (MOI) was derived from CT scans. ME encompasses of BM, stress, strain and MOI and is assumed to be a constant property of a material. No differences in ME were detected at birth. At weaning ME increased in pigs produced by sows fed 1750 (P < 0.05). At the end of nursery ME depended on maternal diets (interaction, P < 0.05). ME increased in pigs fed +D95P if produced by sows fed 0 or 325 but decreased if produced by sows fed 1750. As previously reported, DXA whole body bone mineral density also indicated maternal carryover effects, but the pattern differed among diets. Therefore whole body bone and femur integrity traits differ, but provide unique characterization of the model. As previously reported, the kyphosis model was further characterized by molecular analysis of bone and D homeostatic cell signaling mechanisms. All traits contribute to the characterization of the kyphosis model but a specific mechanism by which the deformity is induced has yet to be determined.

Head supported mass, moment of inertia, neck loads and stability: A simulation study