Attitude Measurement Research Articles

3D position and pose measurement based on coded light field

AbstractHigh‐precision relative position and attitude measurement technology has a wide range of applications in aerospace and industrial production. Currently, the commonly used method for measurement is based on visual cooperative signs. However, its accuracy significantly decreases as the distance increases. Therefore, a relative positioning system is designed based on light field spatial coding and visual recognition. The projector emits spatially encoded structured light within the coverage of the light field, while the receiving end captures, identifies, measures the code, and calculates its pose in the light field coordinate system. Compared with the traditional measurement method, the measurement accuracy of this system does not decrease greatly with the increase in distance, the measurement distance can be adjusted in real‐time and does not depend on an external light source. By changing the projection pattern with different resolutions without changing hardware systems, it can adjust effective measurement distance accordingly. Theoretical and experimental results show that the proposed method can maintain measurement accuracy with the increase in distance.

Redundant Configuration Method of MEMS Sensors for Bottom Hole Assembly Attitude Measurement.

Micro-electro-mechanical systems inertial measurement units (MEMS-IMUs) are increasingly being employed for measuring the attitude of bottom hole assemblies (BHAs). However, the reliability and measurement precision of a single MEMS-IMU may not meet drilling's stringent needs. Redundant MEMS-IMU systems can effectively enhance the reliability and precision. This paper proposes a redundant configuration method for MEMS sensors tailored to BHA attitude measurement. Firstly, based on reliability theory and a cost-benefit analysis, considering factors such as cost, size, and reliability, the optimal number of sensors in the redundant system was determined to be six. Considering the structural characteristics of the BHA, a hollow hexagonal prism-shaped redundant configuration scheme was proposed, ensuring the circulation of drilling fluid within the drill pipe. Next, by employing Kalman filtering to integrate the output data from the six sensors, a virtual IMU (VIMU) was formed. Finally, experimental verification was carried out. The results confirmed that, after redundancy implementation, the velocity random walk of the accelerometer decreased by an average of 58% compared to a single MEMS-IMU, and bias instability was reduced by an average of 54%. The angular random walk of the gyroscope decreased by an average of 58%, and bias instability was reduced by an average of 37%. This research provides a theoretical foundation for enhancing the precision and reliability of BHA attitude measurements.

Interfering implicit attitudes of adopting recycled products from construction wastes

The rapid growth of the construction industry has led to significant environmental issues, notably the sharp escalation in construction waste. Recent endeavors have prioritized on recycling and reusing of construction waste. Nevertheless, despite the evident public support, the adoption of recycled products remains constrained, primarily as a result of subsequent unfavorable implicit perceptions. To understand the end users’ implicit attitudes, this study employed a Single-Category Implicit Association Test (SC-IAT) and functional near-infrared spectroscopy (fNIRS) for analysis. The experiment results confirm the existence of detrimental implicit attitudes, even as self-reported attitudes remained positive. The experiment results, D-scores, suggest that emotional interventions have stronger impact as they reach peak (15.9s) 36% faster that the rational interventions. The proposed implicit attitude measurement approach can be extended to understand and promote other green products and recycled materials.

Kepuasan Konsumen Terhadap Bauran Pemasaran Rumah Makan “Juli Kuliner” Di Boulevard Kota Manado

This study aims to determine the level of customer satisfaction with the marketing mix of Juli Culinary Restaurant in Manado City Boulevard. The data collected in this study are primary data taken by survey with the technique of asking questions directly to consumers, using a questionnaire, and secondary data obtained from the business related to this research, such as the history of the “juli kuliner” restaurant. Sampling by accidental sampling and obtained as many as 88 respondents. The data analysis used in this study is descriptive analysis which is analyzed using an attitude measurement scale or Likert scale. The results showed that in general the level of consumer satisfaction was in the very satisfied category of 84%, with the highest level of satisfaction being the strategic location of 90%. However, there is one variable, namely promotion, which is still in the satisfied category with a satisfaction index of 79%.

Sea Surface Height Measurements Based on Multi-Antenna GNSS Buoys.

Sea level monitoring is an essential foundational project for studying global climate change and the rise in sea levels. Satellite radar altimeters, which can sometimes provide inaccurate sea surface height data near the coast, are affected by both the instrument itself and geophysical factors. Buoys equipped with GNSS receivers offer a relatively flexible deployment at sea, allowing for long-term, high-precision measurements of sea surface heights. When operating at sea, GNSS buoys undergo complex movements with multiple degrees of freedom. Attitude measurements are a crucial source of information for understanding the motion state of the buoy at sea, which is related to the buoy's stability and reliability during its development. In this study, we designed and deployed a four-antenna GNSS buoy with both position and attitude measurement capabilities near Jimiya Wharf in Qingdao, China, to conduct offshore sea surface monitoring activities. The GNSS data were processed using the Precise Point Positioning (PPK) method to obtain a time series of sea surface heights, and the accuracy was evaluated using synchronous observation data from a small sea surface height radar. The difference between the GNSS buoy and the full-time radar was calculated, resulting in a root-mean-square error (RMSE) of 1.15 cm. Concurrently, the attitude of the GNSS buoy was calculated using multi-antenna technology, and the vertical elevation of the GNSS buoy antenna was corrected using the obtained attitude data. The RMSE between the corrected GNSS buoy data and the high ground radar was 1.12 cm, indicating that the four-antenna GNSS buoy can not only acquire high-precision coastal sea level data but also achieve synchronous measurement of the buoy's attitude. Furthermore, the data accuracy was also improved after the sea level attitude correction.

Investigating the Nurses and Doctors Attitudes' Regarding the Management of Acute Myocardial Infarction Patients Who Used the Thrombolytic Agents in Babylon Teaching Hospitals 2022rses and Doctors Regarding Management of Patients with Acute Myocardial Infarction Using Thrombolytic Agents in the Teaching Hospitals of Babylon, Iraq in 2022

Introduction and purpose: Ischemic heart disease and myocardial infarction are the most common causes of death in the world, and nurses play a key role in the management of these patients. Adequate attitude of health care workers towards the management of patients with acute myocardial infarction using thrombolytic agents is very important and this issue is part of patients' rights. Aims: The present study was conducted with the aim of study investigate the attitude of nurses and doctors regarding the management of patients with acute myocardial infarction using thrombolytic agents in the teaching hospitals of Babylon, Iraq in 2022. Research method: In this comparative study, 103 nurses and 13 doctors were selected in 2022 by available sampling method the type of sample was purposive and was conducted on nurses and doctors working in cardiac and coronary resuscitation units in Babylon Specialized Hospitals. Information was collected using two questionnaires including demographic questionnaire and attitude measurement questionnaire the attitudes questionnaire contained parts that included nurses and doctors, and a section specific to nurses only. Results: Among the studied nurses, the largest number were university nurses (36.9% bachelor, 8.7% master). (89.3%) of the nurses had work experience in the coronary care department and (73.8%) of them were currently working in the coronary care department. (78.6%) worked in the morning shift. (76.7%) of the nurses did not have a history of passing the training course in the coronary care department. (54.4%) of the nurses have a diploma and only (2.9%) of them have completed an academic course. The score of doctor’s attitude about the management of patients with acute myocardial infarction using thrombolytic agents was in the range of 68 to 98 with a mean and standard deviation of 83.62 ± 9.62. Based on the results of the independent t-test, there was no significant difference between nurses and doctors regarding the management of patients with acute myocardial infarction using thrombolytic agents (p=0.210). Conclusion: The study concludes that both nurses and doctors in Babylon Teaching Hospitals show a positive attitude towards managing acute myocardial infarction patients using thrombolytic agents. Despite variations in experience and training, both groups are prepared to provide effective care for these patients. The findings suggest a readiness within the medical staff to handle cases of AMI with thrombolytic therapy, highlighting the importance of continued education and training in coronary care management.

Comprehensive Vibration Analysis and Modeling for ZY-3 Satellite's Lifecycle

Abstract. A stable platform environment is essential for achieving high-quality imaging and accurate attitude measurement of the ZY-3's stereo camera. It serves as the fundamental guarantee for the satellite's high geometric precision. Throughout its orbital operation, the platform encounters periodic vibrational occurrences resulting from internal load mechanics and significant external environmental variations, thereby impeding the high-fidelity collection of information by the satellite payload. The detection and modeling of vibrations are crucial tasks for the satellite ground system, as they provide reliable parameter inputs for optimizing attitude accuracy and image quality. This paper presents a method for developing a comprehensive frequency variation vibrational model of the ZY-3 satellite platform throughout its lifecycle, utilizing the inertial gyroscopes (gyros) data of the ZY-3 satellite. The instrument has identified vibrations at three specific frequencies: 0.21 Hz, 0.56 Hz, and 1.12 Hz, each with amplitudes of 0.07″, 0.04″, and 0.04″, respectively. Additionally, it has detected two fluctuating frequencies around 0.3 Hz and 0.6Hz. The period of frequency variation is approximately one year, with vibration ranges of (0.267, 0.299) and (0.603, 0.695). Following a malfunction of the solar panels on the satellite, there has been a shift in the vibration range. Moreover, as the satellite's on-orbit duration increases, this range is also undergoing gradual changes.

Method for measuring non-stationary motion attitude based on MEMS-IMU array data fusion and adaptive filtering

The error characteristics of a typical commercial MEMS-IMU were analyzed. Using 15 ICM-42688 sensors, a 3*5 MEMS-IMU array was designed, and a weighted data fusion method based on Allan variance for the MEMS-IMU array was proposed. This effectively reduces the random measurement errors of the MEMS-IMU, providing a data foundation for the precise measurement of motion and attitude of robots, vehicles, aircraft, and other systems under low-cost conditions. The text describes a measurement method for non-stationary motion attitudes of sports vehicles based on adaptive Kalman-Mahony. Specifically, it first uses adaptive Kalman filter on array sensor data to calculate the measurement noise in real-time and adaptively adjust the filtering gain. Then, it determines the compensation coefficient of the accelerometer to the gyroscope angular velocity based on the motion state of the vehicle, and solves the attitude through complementary filtering to obtain the motion attitude quaternion. Finally, it converts it into the roll angle, pitch angle, and yaw angle of the sports vehicle. Experimental results show that the proposed MEMS-IMU array weighted data fusion method based on Allan variance has significant advantages over traditional single MEMS-IUM methods and traditional average weighting methods in reducing sensor angle random walk and zero drift instability. The proposed adaptive Kalman-Mahony attitude measurement method also shows a significant improvement in the accuracy of non-stationary motion attitude measurement compared to traditional methods.

Attitude Calculation Method of Drilling Tools Based on Cross-Correlation Extraction and ASRUKF

As a key component of the measurement while drilling technology, the accuracy of attitude calculation is directly related to the efficiency of resource exploration. To reduce the influence of vibration, rotation, and other disturbances on the attitude sensor during drilling, a method based on cross-correlation extraction and the adaptive square-root unscented Kalman filter (ASRUKF) is proposed to solve the attitude of the drilling tool in this paper. Firstly, the error of the signal collected by the attitude sensor is compensated, and the unscented Kalman filter (UKF) is used for filtering. Then, the effective gravitational acceleration signal is extracted by the cross-correlation method. Finally, an experimental platform for simulating the fully rotating attitude measurement system is established, and the application effects of the UKF and ASRUKF in the attitude calculation are compared. Compared with the UKF, the root mean square error of the inclination angle calculated by the ASRUKF is reduced by 12.9%, and the variance is reduced by 27.3%; the root mean square error of the azimuth angle is reduced by 29.5%, and the variance is reduced by 39.9%. The experimental results show that the attitude calculation method proposed in this paper can stably and effectively improve the accuracy of the attitude calculation of drilling tools.

GRACE-FO attitude determination: Star camera installation matrix calibration and incremental quaternion integrator

The satellite attitude error is transmitted to the gravity field through KBR antenna phase center correction and non-conservative force conversion, which affects the accuracy of gravity field inversion. Therefore, obtaining high-precision satellite attitude is one of the important research contents of gravity field inversion. Each satellite of GRACE-FO is equipped with three SCs and an IMU for satellite attitude measurement, and fusion of these two types of data can obtain high-precision satellite attitude. In this paper, we use kalman filter to fuse the original GRACE-FO 1A observation data, and take into account the calibration of the installation matrix of the SCs during the fusion process. Meanwhile, a quaternion integrator that takes angle increments as inputs is derived from the equivalent rotation vector differential equation to address the computational inefficiency of first-order quaternion integrator, the accuracy and computational efficiency are verified using measured data. The experimental results show that after the calibration of the installation matrix of the SCs, the system bias of 20′′ caused by switching from three SCs observations to two SCs observations can be eliminated. The standard deviation of the attitude difference between the obtained attitude in this paper and the attitude calculated by JPL is at most 6′′ and the proposed incremental quaternion integrator has the same accuracy as the first-order quaternion integrator but with computational efficiency improved by at least 35%.

Fusion of a priori information and energy distribution for the centroiding method of the star sensor

The star sensor is the most accurate measurement instrument in the spacecraft attitude measurement system, and the accurate centroid of the star point is the basis for ensuring the performance of the star sensor. Currently, the centroid of the gray method is the most widely used centroid extraction method in practice. Systematic errors caused by the centroid of the gray method and random noise in the detector imaging process are the main factors contributing to the deviation of the star centroiding coordinates. Considering the relationship between the point spread function and the pixel gray value, this paper proposes a centroiding method to reduce the star point centroiding error by fusing a priori information and energy distribution. The star charts are first preprocessed using a curvature filter and Gaussian blur to reduce the random noise. Then the complexity of the point spread function is considered, and the pixel gray values are corrected based on a priori information and gray value fuzzy processing. Finally, the symmetry of the one-dimensional energy distribution is used to quickly determine the sub-pixel deviation to get the star centroid coordinates. Through simulation and physical simulation experiments, the method was verified to be effective, and the extraction accuracy met the requirements of high-precision star sensors. The night sky observation test results demonstrate that the method in this paper can improve the measurement accuracy of the star sensors.

A Double-Weighted Information Fusion Method Based on Deep Network for Attitude Measurement

A Double-Weighted Information Fusion Method Based on Deep Network for Attitude Measurement

HyperScout-1 inflight calibration and product validation

ABSTRACT Earth observation aims at monitoring the Earth in increasingly more detail by improving the spatial, spectral and temporal resolution of image acquisitions. This can now be achieved in more cost-efficient ways by the miniaturization of instruments and platforms. New initiatives have emerged to accommodate hyperspectral instruments on CubeSats despite inherent platform limitations in terms of volume, power consumption, computing and downlink capacity. However, the adoption of CubeSat data for operational and scientific applications requires sufficient trust in dependability and data quality. Achieving reliable data quality from CubeSats remains challenging and requires advanced geometric, radiometric, and spectral calibration techniques. We present the successful in-orbit calibration of the HyperScout-1 mission. This In-Orbit Demonstration (IOD) mission, equipped with a miniaturized hyperspectral instrument based on Linear Variable Filter technology (LVF), was launched in 2018 by the European Space Agency (ESA). Rigorous inflight calibration has been applied to HyperScout-1 to ensure the accuracy of its data. The radiometric calibration of the HyperScout-1 instrument was performed vicariously based on modelled spectral radiances over a desert site. Independent validation using data from a CEOS RadCalNet site showed good radiometric accuracy with absolute radiometric errors <5%. Geometric errors due to inaccuracies in attitude measurements and sensor focal plane distortions were corrected using a bundle adjustment technique combined with matching to accurate Ground Control Points. This resulted in excellent geometric performance, with sub-pixel average absolute geolocation errors (~0.48 pixels across track and 0.51 pixels along track). The very limited data budget was a major challenge, forcing us to make some trade-offs in the calibration. Despite this, our robust vicarious calibration strategy allowed effective instrument calibration. As a result, the HyperScout-1 demonstrated the capability of an LVF Hyperspectral instrument on a CubeSat to deliver high-quality imagery and serve applications like land cover classification, change detection and disaster monitoring.

Disordered eating and emotional eating in Arab, middle eastern, and north African American women

Arab, Middle Eastern, and North African (A-MENA) American women are often subject to intersectional discrimination, and they have also not been traditionally recognized as a distinct racial group in disordered eating literature. No study to date has provided descriptive information on disordered and emotional eating A-MENA American women, nor has examined perceptions of widely used measurements of eating pathology in this population. The current study generated descriptive information among A-MENA women on two widely used measures of eating pathology, the Eating Disorder Examination Questionnaire (EDE-Q) and the Emotional Eating Scale (EES). Participants (N = 244) were A-MENA adult women were recruited via social media and snowball sampling. Qualitative findings provide potential sociocultural predictors of disordered eating that should be further explored, such as bicultural identity and family pressures/comments toward appearance. Secondly, themes from the EES-R indicate adding emotion of shame and considering identity-related stress. The current study provides prevalence data and future directions of research on widely used eating pathology and appearance attitude measurements for A-MENA American women.

Motion prediction of tumbling uncooperative spacecraft during proximity operations.

The relative attitude estimation between chasers and uncooperative targets is an important prerequisite for executing in orbit service (OOS) tasks. Only by efficiently obtaining relative pose parameters can chasers design close-range rendezvous trajectories close to uncooperative targets. The focus of this article is on active systems, such as TOF cameras or LIDAR. This paper proposes an attitude estimation scheme to obtain relative attitude parameters between uncooperative targets. This scheme utilizes LIDAR to obtain three-dimensional point clouds of non-cooperative targets, extracts key points and simplifies the number of point clouds through joint farthest point sampling and point cloud feature analysis, and then uses point fast feature histograms (FPFHs) and robust iterative closest point algorithms to achieve point cloud registration between every two frames. Finally, a filtering framework was designed, whose scheme is an extended Kalman filter designed for updating measurements of relative position, velocity, attitude, and angular velocity estimation. The experimental results show that this method can effectively achieve point cloud registration for close range rotation and translation motion, and can estimate the motion state of the target.

Real-time analysis of star sensor attitude accuracy

In the conventional methods of star sensor accuracy evaluation, neither the accuracy calculation formula nor the Monte Carlo method can comprehensively reflect the attitude measurement accuracy of star sensors in real-time. In this paper, a real-time analysis and calculation model for the attitude measurement accuracy of star sensors is proposed. Firstly, the basic attitude measurement model of the star sensor is established through the pinhole imaging model. Moreover, a moving frame of star sensor attitude measurement is established to avoid the defects of attitude representation by the Euler angle in the star sensor accuracy analysis. Then, combined with the error transfer of implicit overdetermined equations proposed in this paper, the error transfers of starspot extraction random error, star catalog random error, and intrinsic parameter system error are provided. Finally, simulation and field experiments are conducted to verify the accuracy of the proposed error analysis theory. The experimental results show that the attitude measurement accuracy of star sensors can be accurately estimated by using single-frame data of guide stars.

Absolute attitude measurement based on multi-sensor fusion

In the field of positioning and navigation, the measurement and transmission of absolute attitude are often used in the initial calibration process of positioning and navigation equipment. This requires higher absolute attitude measurement accuracy and lower measurement complexity. In order to solve the problems of high complexity and time-consuming of traditional absolute attitude measurement, a multi-sensor fusion absolute attitude measurement method is proposed. This method uses an optical camera to calculate the angle offset, employs a biaxial inclination sensor to measure horizontal angles, and utilizes GNSS differential positioning to introduce true azimuth angle. The experimental results of the prototype show that under the condition of 60 m baseline length, the max uncertainty of yaw, pitch, and roll angle measurement is 14.13”, 4.41”, and 3.53” respectively, and the average single measurement time consumption is 2.73 minutes.

Novel Design of Multi-DOF Motor Position Estimation Based on Wireless Power Transmission Modeling

In this paper, a multi-coil wireless power transmission model is presented. The model is applied to the multi-degree-of-freedom (multi-DOF) motor rotor position detection system. The wireless power transmission (WPT) system is evenly distributed on the upper part of the rotor, and the receiving coil is placed on the rotor shaft. When the motor rotor rotates along the three motion states of pitch, spin and tilt, the receiving coil and multi-transmit coil will produce angle deviation. The precise mutual inductance estimation method can be used to obtain the rotor position quickly and avoid the complicated finite element calculation. The system can not only realize the pose estimation of the multi-DOF motor, but also provide flexible energy supplement for the manipulator. The WPT position measurement method is used for PID control of multi-DOF motor, and it is compared with the micro-electro-mechanical-system (MEMS) attitude measurement method. The mechanical sliding measurement method of the encoder is taken as a reference. The results show that the position detection method of WPT has high accuracy, and the estimation error is less than 2%.

A fuzzy adaptive complementary filter for attitude estimation based on norm judgment

Unmanned aerial vehicle (UAV) has great application prospect because of its capability of three-dimensional space operation. The reliability of attitude and heading reference system (AHRS) for UAV attitude estimation is crucial for the application of UAV. When a UAV is subjected to unknown electromagnetic interference and force interference in flight, its attitude detection system can suffer from reduced accuracy or even failure. In this paper, a fuzzy adaptive complementary filter (CF) for attitude estimation based on norm judgment is proposed to solve the problem that the sensor is easily disturbed by the complex flight environment and the fixed filter parameters are difficult to obtain the UAV attitude accurately under different flight states. Firstly, the correction model of the gyroscope, which includes four filter parameters, namely accelerometer weight, magnetometer weight, proportional gain P and integral gain I, is established. Secondly, the influence of the four parameters on the estimation accuracy is analyzed. Finally, the adaptive adjustment rules are designed to adjust the filter parameters online and thus achieve the accurate and reliable measurement of UAV attitude. The feasibility of the proposed algorithm is verified through static, dynamic and interference experiments with the specially designed AHRS test platform. And the results show that the attitude estimation algorithm designed in this paper can ensure the high accuracy of the system in both steady state and high-speed rotation, shield the pitch and roll angles from the acceleration of motion, and keep the yaw angle from the external magnetic field.

A Multimodal Approach for Attitude Measurement of Near-Earth Daytime Star Sensors

A Multimodal Approach for Attitude Measurement of Near-Earth Daytime Star Sensors