Attitude Determination Accuracy Research Articles

Space optical communication system for space optical networks and deep space exploration

The acquisition time of tens to hundreds of seconds in the optical link between satellites makes it difficult to meet the needs of constructing spatial optical networks. In addition, as a basic requirement for deep space explorers, autonomous attitude determination and autonomous navigation demand the installation of separate, expensive, and complex inertial devices, and the communication data rate is too low to meet the timely transmission of large amounts of data. In this paper, we proposed and developed a multifunctional fusion space optical communication system for space optical networks and deep space exploration, which has the functions of autonomous attitude determination, autonomous navigation, and high-speed optical communication. The sub-second acquisition time can meet the requirements of space optical network construction, and the ability of autonomous attitude determination and autonomous navigation significantly reduce the amount of R&D expenses of the explorer; decrease the volume, weight, and power consumption of the explorer; and improve the reliability and autonomous survival ability of the explorer. The paper provides the structure, working principle, and main algorithm models and conducts a feasibility analysis and field experiments. The experimental results showed that the average open-loop pointing accuracy of the optical terminal is 95.8 µrad (attitude determination accuracy), which can be improved to 39.1 µrad after filtering, and the acquisition time is less than 1 s. For deep space exploration, the navigation accuracy is less than 67.6 km in the cruise phase and 10 km in the acquisition phase, and field experiments have also proven its feasibility. The significance of our research work lies in proposing what we believe to be a new system operation scheme and design method for optical communication systems, and its results can be widely applied in all fields of space optical communication.

Developing an eyeball positioning method in the eye orbit for craniofacial identification in Korean population

We analysed the skulls and faces of Korean subjects using anthropometric methods to understand the anatomical characteristics of the eyeball and eye orbit region of Korean population and to determine the correlations between the hard and soft tissues around the eyeball and eye orbit region. In total, 82 sections in the region were measured to determine the correlations; among them, 34 showed significant differences by sex, and 6 showed significant differences by age. As the distance from the centre of the eye lens to the eye orbit is calculated as a ratio, we determined that the centre of the eye lens is located relatively on the lateral and superior position in each eye orbit in front view. Fourteen sections that could be used for craniofacial reconstruction/approximation in men and women were selected. Regression equations were derived according to the correlation of each section, and their reliabilities were verified by out of sample validation tests. Therefore, our results increase the accuracy of eyeball position determination, which would be useful for more efficient craniofacial reconstruction/approximation of the Korean population and should improve the efficiency of facial recognition.

Multidimensional Position And Displacement Estimation Using Periodic Coded Optical Apertures In A Single Camera Imaging System

Accurately estimating multidimensional positions and displacements in fluid dynamic experiments is essential for understanding complex flow phenomena. This paper presents a novel optical measurement setup capable of determining velocity fields using periodic coded optical apertures in a single-camera imaging system. Our method involves placing a periodic transmission grating in front of the optical system and aligning a laser beam along the system’s optical axis. When particles intersect the laser beam, they scatter light, producing out-of-focus images on the imaging sensor resembling the periodic grating. The size and position of these images vary with the distance to the imaging system and the offset from the optical axis, allowing for accurate determination of particle positions. We derive mathematical formulas describing the imaging system and the relationship between image properties and particle positions and verify them through simulations. Additionally, we develop a calibration method enabling arbitrary optical imaging systems to be used with this technique. Finally, we demonstrate the effectiveness of our approach by measuring velocity fields near a ducted ship propeller, a practical application that underscores the real-world impact of our research in fluid dynamics.

Single-Track Magnetic Tape Absolute Position Sensor with Self-Adaptivity.

In this study, we demonstrate a single-track magnetic code tape-based absolute position sensor system. Unlike traditional dual-track systems, our method simplifies manufacturing and avoids crosstalk between tracks, offering higher tolerance to alignment errors. The sensing system employs an array of magnetic field sensing elements that recognize the bit sequence encoded on the tape. This approach allows for accurate position determination even when the number of sensing elements is fewer than the number of bits covered, and without the need for specific spacing between sensing elements and bit length. We demonstrate the system's ability to learn and adapt to various magnetic code patterns, including those that are irregular or have been altered. Our method can identify and localize the sensed magnetic field pattern directly within a self-learned magnetic field map, providing robust performance in diverse conditions. This self-adaptive capability enhances operational safety and reliability, as the system can continue functioning even when the magnetic tape is misaligned or has undergone changes.

Stochastic analysis of drift error of gyroscope in the single-axis attitude determination

Understanding and mitigating the various stochastic errors in gyroscope measurements is crucial for accurate attitude determination. White noise and bias instability can introduce drift errors, reducing the system’s accuracy. Efficient sensor selection and algorithm design necessitate a thorough understanding of these influences and how they propagate throughout the system. This paper addresses the propagation of significant stochastic errors in the attitude determination system, including white noise (angle random walk), bias instability, rate random walk, and correlated noise. The paper discusses the modeling strategy and statistical characteristics of these error contributors. It then evaluates the variance propagation of these errors within the output of a single-axis attitude determination system. The presented analysis calculates and compares the impact of each source of error on the system’s precision over time. Experiments with the MPU6050 and L3G4200D sensors are conducted to validate the analytical results.

Imaging of 3 bright terrestrial gamma-ray flashes by the atmosphere-space interactions monitor and their parent thunderstorms

The Atmosphere-Space Interactions Monitor (ASIM) on the International Space Station (ISS) includes an instrument designed to geolocate Terrestrial Gamma-ray Flashes (TGF) produced by thunderstorms. It does so with a coded aperture system shadowing the pixelated Low Energy Detector of the Modular X- and Gamma-ray Sensor (MXGS). Additionally, it locates associated lightning flashes with the Modular Multispectral Imaging Array (MMIA). Here we present 3 bright TGFs with very similar duration, fluency and observation distance. The innovative imaging capabilities allow us to determine the TGF position and correlate the TGF-lightning parent event in time and position simultaneously. The accurate position determination and distance to the observer allow us to perform a comparative study of TGF characteristics. These TGFs were produced in association with lightning flashes below the highest cloud tops of developing to mature convective cells. In one event, GLM (Geostationary Lightning Mapper) cloud flash rates were slowing down after the TGF while negative cloud-to-ground flashes suddenly ceased from 10 to 5 min before the TGF. An 8-stroke (strongest: -93 kA) cloud-to-ground flash occurred 31 s before the TGF. Vertical profiles from the ERA5 reanalysis data suggest TGFs may be produced in variety of tropical environments.

Detection of Degraded Star Observation Using Singular Values for Improved Attitude Determination.

This study introduces an innovative approach aimed at enhancing the accuracy of attitude determination through the computation of star observation quality. The proposed algorithm stems from the inherent invariance of singular values under attitude transformations, leveraging the concept of assessing error magnitude through the deviation of singular values. Quantization becomes imperative to employ this error magnitude as a weighting factor within the attitude determination process. To fulfill this purpose, this study applies p-value hypothesis testing to calculate quantized error levels. Simulation results validate that the calculated weights derived from the proposed algorithm lead to a discernible enhancement in attitude determination performance.

Rotational position error correction in ptychography.

Accurate determination of scan positions is essential for achieving high-quality reconstructions in ptychographic imaging. This study presents and demonstrates a method for determining the rotation angle of the scan pattern relative to the detector pixel array using diffraction data. The method is based on the Fourier-Mellin transform and cross-correlation calculation. It can correct rotation errors up to 60deg. High-quality reconstructions were obtained for visible light and electron microscopy datasets, and intricate structures of samples can be revealed. We believe that this refinement method for rotary position errors can be valuable for improving the performance of ptychographic four-dimensional scanning transmission electron microscopy.

Research on Guide Star Distribution of Sub-Arcsecond Attitude Determination for Microsatellites Reusing Scientific Cameras

Onboard scientific cameras are reused in attitude determination to meet the sub-arcsecond attitude determination accuracy requirements of microsatellites. This approach does not require an additional payload for microsatellites. It involves reusing high-quality optical lenses from the scientific camera and utilizing the peripheral high-quality imaging areas of its square-shaped detector. Separate detectors are placed within these areas as attitude determination detectors to obtain star patterns for closed-loop attitude determination, thereby achieving high-precision attitude determination for microsatellites. The star patterns obtained using this method may pose specific issues due to the relative positions of stars. Through an analysis of the theoretical model that examines the relationship between attitude determination accuracy and the main influencing factors, it is indicated that guide star distribution is one of the main, complex factors determining attitude determination accuracy. A further simulation analysis was conducted on the specific impact of two guide star distribution characteristics—namely, the coverage of guide stars in the attitude determination areas and the proportion of the average field of view occupied by the guide star triangles to the total field of view of the attitude determination areas—on attitude determination accuracy. This study concludes that when the measurement error of the guide stars is bigger than the attitude determination accuracy requirement for its area configuration, four attitude determination areas should be configured. Four attitude determination areas should be prioritized when the measurement error is equal to or smaller than the attitude determination accuracy requirement, followed by the option to configure three attitude determination areas or two symmetric attitude determination areas. When selecting guide stars for star pattern recognition, the guide stars should cover the attitude determination areas as much as possible, and guide stars with a higher proportion of the average field of view occupied by the guide star triangles to the total field of view should be chosen. Finally, experimental validation was conducted using star patterns from dense star fields and sparse star fields. The research results provide an important reference for the optimization of attitude determination area configuration, navigation star catalog construction, and star pattern recognition algorithm research for microsatellites equipped with scientific cameras.

Marker Set Configuration and Rigid Body Attitude Determination.

Image-based motion-analysis systems typically place markers on the bodies of interest. The error in determining segment attitude from these markers is a function the marker position errors, the number of markers, and the spatial distribution of the markers. The spatial distribution includes two factors: the mean square distance of these markers to their geometric center, and the degree of anisotropy in the marker distribution. The purposes of this study were to: (1) present a metric which quantifies the marker spatial distribution (anisotropic to isotropic) and (2) examine the influence of marker distribution on the accuracy of rigid body attitude determination. To test the influence of the marker distribution on body attitude determination 1000 criterion attitudes were determined. These attitudes then had to be estimated for two marker sets for which the marker distribution metric, noise levels, and root-mean-square distance of the markers were systematically varied. Anisotropic marker distributions were shown to negatively affect the accuracy of attitude determination. The influence of anisotropic marker distributions on attitude accuracy could be blunted by increasing the number of markers, increasing the root-mean-square distance of markers from their geometric center, and reducing noise levels. These results have implications for the measurement of the attitudes of body segments. For example, the ability to have a large spatial distribution of markers and a large number of markers to maximize the measurement accuracy of segment attitude is different for a small segment such as the fifth metacarpal compared with the thigh.

Updating nucleosome positions within individual genes using molecular modeling methods and mnase sequencing data

Organization of chromatin plays an important role in regulating the genetic machinery of the cell. The basic unit of chromatin packaging is a nucleosome, which harbors DNA of about 145 base pairs in length. The packaging of genetic material and its accessibility to transcription enzymes and other regulatory chromatin proteins depends on the positions of nucleosomes. MNase sequencing is used to examine nucleosome positions in a genome. MNase sequencing data are sufficient for detecting the presence of nucleosomes on the sequence, but a determination of the precise locations of nucleosomes can be problematic. Accurate determination of nucleosome positions requires additional data filtering and processing. In this study, using MNase sequencing data, a combined method based on geometric analysis of nucleosome chain molecular models is proposed for selecting possible nucleosome positions. The developed algorithm efficiently eliminates inaccessible nucleosome chain combinations and conformationally prohibited nucleosome positions.

Star-Identification System Based on Polygon Recognition

Accurate attitude determination is crucial for satellites and spacecraft. Among attitude determination devices, star sensors are the most accurate. Solving the lost-in-space problem is the most critical function of the star sensor. Our research introduces a novel star-identification system that utilizes a polygon-recognition algorithm to assign a unique complex number to polygons created by stars. This system aims to solve the lost-in-space problem. Our system includes a full solution with a lens, image sensor, processing unit, and algorithm implementation. To test the system’s performance, we analyzed 100 night sky images that resembled what a real star sensor in orbit would experience. We used a k-d tree algorithm to accelerate the search in the star catalog of complex numbers. We implemented various verification methods, including internal polygon verification and a voting mechanism, to ensure the system’s reliability. We obtained the star database used as a reference from the Gaia DR2 catalog, which we filtered, to eliminate irrelevant stars, and which we arranged by apparent magnitude. Despite manually introducing up to three false stars, the system successfully identified at least one star in 97% of the analyzed images.

Retracted: Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Retracted: Fast and Accurate Position Determination of Multimodal Couplings of Steel Rolling Machinery and Equipment Combined with Multimedia Optimized Particle Filters

Adaptive Absolute Attitude Determination Algorithm for a Fine Guidance Sensor

In order to ensure the attitude determination accuracy and speed of a fine guidance sensor (FGS) in a space telescope with limited onboard hardware computing resources, an adaptive absolute attitude determination algorithm was proposed. The more stars involved in the attitude determination, the higher the attitude accuracy, but more hardware resources will be consumed. By analyzing the relationship between the attitude determination accuracy and the number of stars (NOS) in the field of view (FOV), and the relationship between the detector exposure time and the NOS, an adaptive method of adjusting the NOS in the FOV was proposed to keep the number of observed stars in the FOV of the detector at a target value. The star map recognition algorithm based on improved log-polar transformation has a higher recognition speed than the traditional algorithm but cannot accurately identify and match the corresponding guide star when the number of observed stars is less than the number of guide stars. Thus, a comparison-AND star identification algorithm based on polar coordinates was proposed. In the case of a given line-of-sight pointing and 100-frame image simulation calculation, the root mean square (RMS) value of the line-of-sight pointing error was less than 37 mas in the direction of a right ascension, and less than 25 mas in the direction of declination, as concluded from the experimental simulation.

Dual-antenna GPS-based UAV Attitude Determination Method and Accuracy Analysis

Accurate attitude information of small-sized unmanned aerial vehicles (UAVs) is required to obtain absolute azimuth information of a target via an airborne electro-optical imaging system. The direct attitude solution method of dual-antenna Global Position System (GPS) is investigated in this paper to address this need. We analyzed the attitude measurement principle of the direct method, gave the error estimation model, and estimated the inner and outer precision through simulation. The simulation results demonstrated that to achieve the requirement of UAV yaw angle error within 1°, the baseline length should be no less than 1 m. The applicability of the model and algorithm was confirmed.

Development and In-Orbit Operation of Deep Learning Attitude Sensor

This study presents in-orbit demonstrations of a deep learning attitude sensor (DLAS) aboard the Japan Aerospace Exploration Agency (JAXA) small-satellite, Rapid Innovative Payload Demonstration Satellite 1. The DLAS is a spaceborne component that consists of star trackers, Earth cameras, and onboard computers. We propose a novel attitude determination method that uses a small camera and image recognition algorithm on board the DLAS to achieve three-axis attitude determination with minimal weight and volume. The DLAS mission further includes a demonstration of a low-cost high-performance star tracker that integrates consumer products. The development of the DLAS began in 2016 when it was adopted as the theme of the JAXA Innovative Satellite Technology Demonstration program. It was launched into a sun-synchronous orbit at an altitude of 500 km in January 2019 for approximately one year. This paper describes the results obtained from the DLAS operation and its future applications. The DLAS demonstrated an Earth camera image identification accuracy of more than 70%. Moreover, the obtained attitude determination accuracy was approximately 2.8 deg for the Earth camera and approximately 14 arcs for the star trackers. The technologies developed in the DLAS have been implemented in a subsequent microsatellite (HIBARI) of the Tokyo Institute of Technology.

Impact of Motion-Dependent Errors on the Accuracy of an Unaided Strapdown Inertial Navigation System

The selection of an appropriate measurement system for an inertial navigation system requires an analysis of the impact of sensor errors on the position and orientation determination accuracy to ensure that the selected solution is cost-effective and complies with the requirements. In the current literature, this problem is solved based on the navigation duration only by considering the time-dependent errors due to sensor bias and random walk parameters or by conducting numerous simulations. In the former case, oversimplifying the analysis will not allow accurate values to be determined, while the latter method does not provide direct insight into the emerging dependencies. In contrast, this article introduces an analytic approach with a detailed model. This article presents general formulas, also written in detail for the measurement system model adopted and various manoeuvres. Although general equations are complicated, the use of piecewise constant motion variables allow us to discern fragments of equations corresponding to individual error sources. The results confirm the effect the carouseling has on the reduction of navigation errors. The general formulas presented extend the potential to analyse the influence of the entire host vehicle motion, while the detailed formulas make dependencies between motion and navigational errors evident.

The Influence of Varying Atmospheric and Space Weather Conditions on the Accuracy of Position Determination.

Today's technological developments make it possible to use machines to perform specific tasks instead of humans. However, the challenge for such autonomous devices is to precisely move and navigate in constantly changing external environments. In this paper, the influence of varying weather conditions (air temperature, humidity, wind speed, atmospheric pressure, type of satellite systems used/satellites visible, and solar activity) on the accuracy of position determination was analyzed. To reach the receiver, a satellite signal must travel a great distance and pass through all layers of the Earth's atmosphere, the variability of which causes errors and delays. Moreover, the weather conditions for receiving data from satellites are not always favorable. In order to investigate the impact of delays and errors on position determination, the measurements of the satellite signal were conducted, the motion trajectories were determined, and the standard deviations of these trajectories were compared. The results obtained show that it is possible to achieve high precision in determining the position, but varying conditions, such as solar flares or satellites' visibility, meant that not all measurements are able to achieve the required accuracy. The use of the absolute method of satellite signal measurements contributed to this to a large extent. To increase the accuracy of positioning by GNSS systems, it is first of all proposed to use a dual-frequency receiver that eliminates ionospheric refractions.

A novel positioning method of anti-punching drilling robot based on the fusion of multi-IMUs and visual image

Anti-punching drilling robot (APDR) is the key equipment for underground rock burst relief in coal mine and the accurate position and attitude determination is the basis and premise for realizing unmanned pressure relief operation. In this paper, a novel positioning method of APDR based on spatial array inertial measurement units (IMUs) and visual image is proposed. Firstly, the spatial array layout of multiple IMUs is displayed creatively, and the data fusion model and the posture calculation process of spatial array IMUs are constructed. The superiority of proposed spatial array IMUs is verified through the motion trajectory simulation analysis and mobile carrier simulation experiments. Then, an image enhancement method (SSR-AF) is designed to overcome the problems of atomization, glare, uneven illumination and noise interference in coal mine images, so as to improve the accuracy of image feature extraction and matching. Accordingly, the positioning estimation model based on continuous frame images is established. Furthermore, the fusion positioning process of APDR is presented by using the loose coupling mode based on Kalman filtering algorithm. The position and attitude monitoring experimental platform of APDR is built in a simulated coal mine tunnel. The experimental results indicate that the calculation errors of displacement and attitude based on the proposed fusion positioning method is superior to the competing methods, which meet the actual positioning requirements, and verify the feasibility and practicability of the proposed positioning method for APDR.

Multi-dimensional particle filter-based estimation of phase line biases for single-differenced ambiguity resolution in GNSS-based attitude determination

Global navigation satellite systems (GNSSs) have been widely used to provide real-time and high-precision attitude information for land vehicles, ships and aircraft over the past few decades. With the joint use of emerging multi-GNSS common-clock receivers and the single-differenced (SD) model, the accuracy of pitch and roll can be significantly improved to the same level as that of yaw. However, the prerequisite is that the frequency-dependent phase line biases (LBs) in multiple GNSS systems and frequencies are accurately and rapidly estimated. In this contribution, we intend to solve this problem by using a multi-dimensional particle filter (PF)-based approach. We first investigate the relationship between the ratio value and the multi-dimensional phase LBs. Results have revealed that the ratio value can be used to judge the quality of multi-dimensional phase LBs and represent the likelihood function of the observations. We then present the procedure of multi-dimensional PF-based phase LBs estimation for SD ambiguity resolution and attitude determination. An improved strategy is also proposed to reduce the computation time. Finally, we take the two-dimensional case as a representative example to evaluate the performance of the proposed method in aspects of the convergence and accuracy of phase LB estimates, the attitude determination accuracy, and the computation time. Experimental results from two static datasets have demonstrated that the two-dimensional phase LBs basically rapid converge within 20 epochs. Moreover, compared with the double-differenced method, the proposed multi-dimensional PF-based SD method could provide comparable yaw accuracy and much better pitch accuracy. The pitch accuracy is improved to the same level as yaw by approximately 42.9%–50.0%. With regard to the computation time, it is found that with the proposed modification strategy, the single-epoch computation times are significantly reduced by approximately 90.7%–93.5%, and they are mostly within 0.05 s for most of the epochs on a personal computer.