Coupled Dynamics and Integrated Control for Position and Attitude Motions of Spacecraft:A Survey

Inspired by the integrated guidance and control design for endo-atmospheric aircraft,the integrated position and attitude control of spacecraft has attracted increasing attention and gradually induced a wide variety of study results in last over two decades,fully incorporating control requirements and actuator characteristics of space missions.This paper presents a novel and comprehensive survey to the coupled position and attitude motions of spacecraft from the perspective of dynamics and control.To this end,a systematic analysis is firstly conducted in details to show the position and attitude mutual couplings of spacecraft.Particularly,in terms of the time discrepancy between spacecraft position and attitude motions,space missions can be categorized into two types:space proximity operation and space orbital maneuver.Based on this classification,the studies on the coupled dynamic modeling and the integrated control design for position and attitude motions of spacecraft are sequentially summarized and analyzed.On the one hand,various coupled position and dynamic formulations of spacecraft based on various mathematical tools are reviewed and compared from five aspects,including mission applicability,modeling simplicity,physical clearance,information matching and expansibility.On the other hand,the development of the integrated position and attitude control of spacecraft is analyzed for two space missions,and especially,five distinctive development trends are captured for space operation missions.Finally,insightful prospects on future development of the integrated position and attitude control technology of spacecraft are proposed,pointing out current primary technical issues and possible feasible solutions.

An Improved Particle Filter Map Matching Algorithm for Personal Inertial Positioning

The current particle filtering map matching algorithm has problems such as low map utilization and poor accuracy of turnoff positioning, etc. This paper proposed an improved particle filtering-based map-matching algorithm for the inertial positioning of personnel. The historical moment position constraint and feasible region constraint of particles were introduced in this paper. A resampling method based on multi-stage backtracking of particles was proposed. Therefore, the effectiveness of newly generated particles could be guaranteed. The utilization rate of map information could be improved, thus enhancing the accuracy of personnel localization. The walking experiment results showed that, compared with the traditional PDR algorithm, the proposed method had higher localization accuracy and better repeatability of the localization trajectory for multi-turn paths. Under the total travel of 480 meters, the deviation of the starting end point was less than 2 meters, which was about 0.4% of the total travel.

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Real-Time Position and Attitude Estimation for Homing and Docking of an Autonomous Underwater Vehicle Based on Bionic Polarized Optical Guidance

As an important tool for marine exploration, the autonomous underwater vehicle(AUV) must home in and dock at a docking station(DS) to be recharged, repaired, or to exchange information at set intervals. However, the complex and hostile underwater environment makes this process challenging. This study proposes a real-time method based on polarized optical guidance for determining the position and attitude of the AUV relative to its DS. Four polarized artificial underwater landmarks are positioned at the DS, which are recognized by the AUV vision system. Compared with light intensity, the polarization of a light beam is known to be better maintained at greater propagation distances, especially in underwater environments. The proposed method, which is inspired by the ability of marine animals to communicate, calculates the pose parameters in less than 10 ms without any other navigational information. The simulation results reveal that the angle errors are small and the position errors are no more than 0.116 m within 100 m in the coastal ocean. The results of underwater experiments further demonstrate the feasibility of the proposed method, which extends the operating distance of the AUV beyond what is currently possible while maintaining the precision of traditional optical guidance.

Determining Attitude and Position in Deep Space Missions Using X Ray Pulsars

This paper initially reviews types of deep space navigation methods. Then, it studies the use of pulsars as one of sources emitting electromagnetic waves in navigation;hence more details regarding the pulsar physics and the history of navigation using pulsars are presented. The various methods of navigation (including radio method), their advantages and disadvantages—in comparison with navigation using pulsars in spacecraft—are discussed. Then, the equations necessary for calculating position and velocity of a spacecraft (such as the arrival time of pulse from pulsar to the receiver) are introduced, and the methods of calculating position and velocity are dealt with. Finally, two algorithms are presented for positioning, and one for velocity. Attitude determination follows the same simple methods presented in various articles.

Relative Position and Attitude Control for Drag-Free Satellite with Prescribed Performance and Actuator Saturation

An adaptive prescribed performance control scheme is proposed for the drag free satellite in the presence of actuator saturation and external disturbances.The relative translation and rotation dynamics between the test mass and outer satellite are firstly derived.To guarantee prescribed performance bounds on the transient and steady control errors of relative states,a performance constrained control law is formulated with an error transformed function.In addition,the requirements to know the system parameters and the upper bound of the external disturbance in advance have been eliminated by adaptive updating technique.A command filter is concurrently used to overcome the problem of explosion of complexity inherent in the backstepping control design.Subsequently,a novel auxiliary system is constructed to compensate the adverse effects of the actuator saturation constrains.It is proved that all signals in the closed?loop system are ultimately bounded and prescribed performance of relative position and attitude control errors are guaranteed.Finally,numerical simulation results are given to demonstrate the effectiveness of the proposed approach.

5G Ultra-Dense Network Fingerprint Positioning Method Based on Matrix Completion

The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching algorithms.First,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint database.Second,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint databases.Finally,a classification weighted K-nearest neighbor fingerprint matching algorithm is proposed.The estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint database.The simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.

Multi-Modal Scene Matching Location Algorithm Based on M2Det

In recent years,many visual positioning algorithms have been proposed based on computer vision and they have achieved good results.However,these algorithms have a single function,cannot perceive the environment,and have poor versatility,and there is a certain mismatch phenomenon,which affects the positioning accuracy.Therefore,this paper proposes a location algorithm that combines a target recognition algorithm with a depth feature matching algorithm to solve the problem of unmanned aerial vehicle(UAV)environment perception and multi-modal image-matching fusion location.This algorithm was based on the single-shot object detector based on multi-level feature pyramid network(M2Det)algorithm and replaced the original visual geometry group(VGG)feature extraction network with the ResNet-101 network to improve the feature extraction capability of the network model.By introducing a depth feature matching algorithm,the algorithm shares neural network weights and realizes the design of UAV target recognition and a multi-modal image-matching fusion positioning algorithm.When the reference image and the real-time image were mismatched,the dynamic adaptive proportional constraint and the random sample consensus consistency algorithm(DAPC-RANSAC)were used to optimize the matching results to improve the correct matching efficiency of the target.Using the multi-modal registration data set,the proposed algorithm was compared and analyzed to verify its superiority and feasibility.The results show that the algorithm proposed in this paper can effectively deal with the matching between multi-modal images(visible image–infrared image,infrared image–satellite image,visible image–satellite image),and the contrast,scale,brightness,ambiguity deformation,and other changes had good stability and robustness.Finally,the effectiveness and practicability of the algorithm proposed in this paper were verified in an aerial test scene of an S1000 sixrotor UAV.

Underwater Terrain Positioning Method Based on Least Squares Estimation for AUV

To achieve accurate positioning of autonomous underwater vehicles, an appropriate underwater terrain database storage format for underwater terrain-matching positioning is established using multi-beam data as underwater terrainmatching data. An underwater terrain interpolation error compensation method based on fractional Brownian motion is proposed for defects of normal terrain interpolation, and an underwater terrain-matching positioning method based on least squares estimation（LSE） is proposed for correlation analysis of topographic features. The Fisher method is introduced as a secondary criterion for pseudo localization appearing in a topographic features flat area, effectively reducing the impact of pseudo positioning points on matching accuracy and improving the positioning accuracy of terrain flat areas. Simulation experiments based on electronic chart and multi-beam sea trial data show that drift errors of an inertial navigation system can be corrected effectively using the proposed method. The positioning accuracy and practicality are high, satisfying the requirement of underwater accurate positioning.

Design of trotting controller for the position-controlled quadruped robot

This work presents a controller designed for position-controlled quadrupedal dynamic locomotion,aiming at simple and robust trotting control. The controller takes the torso attitude angles and velocities into planning foot trajectories. Firstly design of the servo motor actuated quadruped robot is introduced and the kinematic equations are deduced. Then a scheme is presented for controlling the robot torso attitude based on the virtual leg model. Furthermore,it demonstrates the design of the controller which enables the robot to have a wide range of trotting gaits and omni-directional motions. Finally,results of robust trotting in various speeds,path tracking and push recovery in simulation are reported,and results of trotting on real quadruped robots will be studied.

Binocular Vision Positioning Method for Safety Monitoring of Solitary Elderly

In nowadays society,the safety of the elderly population is becoming a pressing concern,especially for those who live alone.There might be daily risks such as accidental falling or treatment attack on them.Aiming at these problems,indoor positioning could be a critical way to monitor their states.With the rapidly development of the imaging techniques,wearable and portable cameras are very popular,which could be set on human individual.And in view of the advantages of the visual positioning,the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor.In this paper,the imaging model has been established with the corrected image data from the binocular camera;then feature extraction has been completed to provide reference to adjacent image matching based on the binary robust independent elementary feature(BRIEF)descriptor,finally the camera movement and the states of the elderly have been estimated to distinguish their falling risk.In the experiments,the real-sense D435i sensors were adopted as the binocular cameras to obtain indoor images,and three experimental scenarios have been carried out to test the proposed method.The results show that the proposed algorithm can effectively locate the elderly indoor and improve the real-time monitoring capability.

Estimation of Quaternion Motion for GPS-Based Attitude Determination Using the Extended Kalman Filter

In this paper,the Global Positioning System(GPS)interferometer provides the preliminarily computed quaternions,which are then employed as the measurement of the extended Kalman filter(EKF)for the attitude determination system.The estimated quaternion elements from the EKF output with noticeably improved precision can be converted to the Euler angles for navigation applications.The aim of the study is twofold.Firstly,the GPS-based computed quaternion vector is utilized to avoid the singularity problem.Secondly,the quaternion estimator based on the EKF is adopted to improve the estimation accuracy.Determination of the unknown baseline vector between the antennas sits at the heart of GPS-based attitude determination.Although utilization of the carrier phase observables enables the relative positioning to achieve centimeter level accuracy,however,the quaternion elements derived from the GPS interferometer are inherently noisy.This is due to the fact that the baseline vectors estimated by the least-squares method are based on the raw double-differenced measurements.Construction of the transformation matrix is accessible according to the estimate of baseline vectors and thereafter the computed quaternion elements can be derived.Using the Euler angle method,the process becomes meaningless when the angles are at 90where the singularity problem occurs.A good alternative is the quaternion approach,which possesses advantages over the equivalent Euler angle based transformation since they apply to all attitudes.Simulation results on the attitude estimation performance based on the proposed method will be presented and compared to the conventional method.The results presented in this paper elucidate the superiority of proposed algorithm.

Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination

The Global Positioning System(GPS)offers the interferometer for attitude determination by processing the carrier phase observables.By using carrier phase observables,the relative positioning is obtained in centimeter level.GPS interferometry has been firstly used in precise static relative positioning,and thereafter in kinematic positioning.The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector,defined as the vector between the antenna designated master and one of the slave antennas,connected to a rigid body.Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination.The conventional solution of the baseline vectors based on least-squares approach is inherently noisy,which results in the noisy attitude solutions.In this article,the complementary Kalman filter(CKF)is employed for solving the baseline vector in the attitude determination mechanism to improve the performance,where the receiver-satellite double differenced observable was utilized as the measurement.By using the carrier phase observables,the relative positioning is obtained in centimeter level.Employing the CKF provides several advantages,such as accuracy improvement,reliability enhancement,and real-time assurance.Simulation results based on the conventional method where the least-squares approach is involved,and the proposed method where the CKF is involved are compared and discussed.

ATTITUDE RATE ESTIMATION BY GPS DOPPLER SIGNAL PROCESSING

A method is presented for near-Earth spacecraft or aviation vehicle's attitude rate estimation by using relative Doppler frequency shift; of the Global Positioning System (GPS) carrier. It comprises two GPS receiving antennas, a signal processing circuit and an algorithm. The whole system is relatively simple, the cost and weight, as well as power consumption, are very low.

Coordinate correction algorithm for WLAN indoor positioning

In the fingerprint matching-based wireless local area network(WLAN) indoor positioning system,Kalman filter(KF) is usually applied after fingerprint matching algorithms to make positioning results more accurate and consecutive.But this method,like most methods in WLAN indoor positioning field,fails to consider and make use of users' moving speed information.In order to make the positioning results more accurate through using the users' moving speed information,a coordinate correction algorithm(CCA) is proposed in this paper.It predicts a reasonable range for positioning coordinates by using the moving speed information.If the real positioning coordinates are not in the predicted range,it means that the positioning coordinates are not reasonable to a moving user in indoor environment,so the proposed CCA is used to correct this kind of positioning coordinates.The simulation results prove that the positioning results by the CCA are more accurate than those calculated by the KF and the CCA is effective to improve the positioning performance.

Design on a Multi-Sensor Integrated Attitude Determination System for Small UAVs

This paper discusses the design and implementation of a low cost multi-sensor integrated attitude determination system for small unmanned aerial vehicles( UAVs),which uses strapdown inertial navigation system( SINS) based on micro electromechanical system( MEMS) inertial sensors,commercial GPS receiver,and 3-axis magnetometer.MEMS-SINS initial attitude determination cannot be well performed for the reason that the MEMS inertial sensors biases are time-varying and poor repeatability,therefore in this paper the magnetometer and inclinometer are used to assist the MEMS-SINS initial attitude determination and MEMS inertial sensors field calibration.Furthermore,the attitude determination algorithms are presented to estimate the full attitude during GPS signal outage and non-accelerating situation.Additionally,the attitude information estimation results are compared with the reference of the non-magnetic marble platform and 3-axis turntable.Then the attitude estimation precision satisfies the requirement of attitude measurement for small UAVs during GPS signal outage and availability.Finally,the small UAV autonomous flight test results show that the low cost and real-time attitude determination system can yield continuous,reliable and effective attitude information for small UAVs.

Attention-based LSTM predictive model for the attitude and position of shield machine in tunneling

Shield machine may deviate from its design axis during excavation due to the uncertainty of geological environment and the complexity of operation.This study therefore introduced a framework to predict the attitude and position of shield machine by combining long short-term memory(LSTM)model with attention mechanism.The data obtained from the Wuhan Rail Transit Line 6 project were utilized to verify the feasibility of the proposed method.By adding the attention mechanism into the LSTM model,the proposed model can focus more on parameters with higher weights.Sensitivity analysis based on Pearson correlation coefficient was conducted to improve the prediction efficiency and reduce the irrelevant input parameters.Compared with LSTM model,LSTM-attention model has higher accuracy.The mean value of coefficient of determination(R^(2))increases from 0.625 to 0.736,and the mean value of root mean square error(RMSE)decreases from 3.31 to 2.24.The proposed LSTM-attention model can provide an effective prediction for attitude and position of shield machine in practical tunneling engineering.

Some Results on Position Restriction Scheduling Problems

In this paper, we first consider the position restriction scheduling problems on a single machine. The problems have been solved in certain special cases, especially for those obtained by restricting the processing time pj = 1. We introduce the bipartite matching algorithm to provide some polynomial-time algorithms to solve them. Then we further consider a problem on unrelated processors.

A Cross-Sectional Survey of Knowledge Attitude and Prevention Practice towards Malaria among Basic Schools Pupils Prior to Health Education Campaign

Background: Malaria has historically been a major public health concern in Yemen, noted to be the country with the highest prevalence in the Eastern Mediterranean Region. As more and more children attend school, governments are increasingly recognizing the importance of child health for educational achievement. Aim: The aim is to assess the baseline knowledge, attitude and practice of pupil towards malaria before the health education activities. Methods: We conducted a cross-sectional study, in four randomly selected districts (rural and urban) of Taiz governorate. The study population was 1598 pupils in primary schools. Data was collected using questioner. Results: The pupils who recognized mosquito bite as a route of malaria transmission was 769 (48.1%), while the pupils who recognized fever as the main symptom were 786 (49.2%), 281 (17.58%) of pupils recognized convulsion as a complication of malaria. Regarding protective method 881 (55.31%) were mentioned the cover of the tanks as a protective method, about the BN 293 (18.3%) of pupils known about the BN and 280 (17.5%) mentioned children & pregnancy were the vulnerable groups to malaria. Conclusions and Recommendation: the percentage of knowledge of malaria knowledge and methods of prevention was low (24.5%). Also, the positive attitude and practice toward malaria was 45%. The rate of having bed-nets was very low (10.1%). There were misconceptions of malaria cause and transmission (48.1%). We recommend conducting health education activities that will focus on increasing the knowledge, attitude and practice levels of malaria among school pupils.