Performance analysis of PPP ambiguity resolution with UPD products estimated from different scales of reference station networks

Integer ambiguity fixing with uncalibrated phase delay (UPD) products can significantly shorten the initialization time and improve the accuracy of precise point positioning (PPP). Since the tracking arcs of satellites and the behavior of atmospheric biases can be very different for the reference networks with different scales, the qualities of corresponding UPD products may be also various. The purpose of this paper is to comparatively investigate the influence of different scales of reference station networks on UPD estimation and user ambiguity resolution. Three reference station networks with global, wide-area and local scales are used to compute the UPD products and analyze their impact on the PPP-AR. The time-to-first-fix, the unfix rate and the incorrect fix rate of PPP-AR are analyzed. Moreover, in order to further shorten the convergence time for obtaining precise positioning, a modified partial ambiguity resolution (PAR) and corresponding validation strategy are presented. In this PAR method, the ambiguity subset is determined by removing the ambiguity one by one in the order of ascending elevations. Besides, for static positioning mode, a coordinate validation strategy is employed to enhance the reliability of the fixed coordinate. The experiment results show that UPD products computed by smaller station network are more accurate and lead to a better coordinate solution; the PAR method used in this paper can shorten the convergence time and the coordinate validation strategy can improve the availability of high precision positioning.     

地基单站GPS探测大气折射环境

基于地基单站双频GPS接收机,提出了实时遥感探测大气折射环境（包括对流层折射率剖面与电离层电子密度剖面）的方法,并经过实验验证可行。在对流层方面,改进精密单点定位技术使得对流层低仰角斜延迟可以实时解算,然后利用相关向量机方法反演得到对流层折射率剖面;在电离层方面,采用Kalman滤波技术消除硬件延迟得到电离层TEC,基于IRI模型,利用遗传算法反演得到电离层电子密度剖面。此研究为大气折射环境的实时、高效、低成本探测提供了一种新手段。     

Trajectory tracking control of a VTOL unmanned aerial vehicle using offset-free tracking MPC

Designing a stable and robust flight control system for an Unmanned Aerial Vehicle (UAV) is an arduous task. This paper addresses the trajectory tracking control problem of a Ducted Fan UAV (DFUAV) using offset-free Model Predictive Control (MPC) technique in the presence of various uncertainties and external disturbances. The designed strategy aims to ensure adequate flight robustness and stability while overcoming the effects of time delays, parametric uncertainties, and disturbances. The six degrees of freedom DFUAV model is divided into three flight modes based on its airspeed, namely the hover, transition, and cruise mode. The Dryden wind turbulence is applied to the DFUAV in the linear and angular velocity component. Moreover, different uncertainties such as parametric, time delays in state and input, are introduced in translational and rotational components. From the previous work, the Linear Quadratic Tracker with Integrator (LQTI) is used for comparison to corroborate the performance of the designed controller. Simulations are computed to investigate the control performance for the aforementioned modes and different flight phases including the autonomous flight to validate the performance of the designed strategy. Finally, discussions are provided to demonstrate the effectiveness of the given methodology.     

带时延和拓扑切换的编队卫星鲁棒协同控制

综合考虑了存在通信时延、拓扑结构切换、参数不确定性和外部扰动等情况下的编队卫星协同控制问题,分别提出了鲁棒位置和姿态协同控制器。采用Lyapunov直接法,通过恰当地选取公共的Lyapunov函数,保证了所设计的位置协同控制器对于通信时延和拓扑切换具有鲁棒性。控制器中设计了一个自适应项,用于在线补偿卫星质量的不确定性。进一步,引入了一个含有时变参数的非线性饱和函数向量项,保证了位置协同控制器对于外部扰动的鲁棒性,并且控制器是连续的。然后,将协同控制器推广到了姿态协同的情况,提出了类似的鲁棒姿态协同控制器。仿真结果表明了本文协同控制方案的有效性。     

Coordinated Multiple Spacecraft Attitude Control with Communication Time Delays and Uncertainties

In this paper, we consider the coordinated attitude control problem of spacecraft formation with communication delays, model and disturbance uncertainties, and propose novel synchronized control schemes. Since the attitude motion is essential in non-Euclidean space, thus, unlike the existing designs which describe the delayed relative attitude via linear algorithm, we treat the attitude error and the local relative attitude on the nonlinear manifold-Lie group, and attempt to obtain coupling attitude information by the natural quaternion multiplication. Our main focus is to address two problems:1) Propose a coordinated attitude controller to achieve the synchronized attitude maneuver, i.e., synchronize multiple spacecraft attitudes and track a time-varying desired attitude; 2) With known model information, we achieve the synchronized attitude maneuver with disturbances under angular velocity constraints. Especially, if the formation does not have any uncertainties, the designer can simply set the controller via an appropriate choice of control gains to avoid system actuator saturation. Our controllers are proposed based on the Lyapunov-Krasovskii method and simulation of a spacecraft formation is conducted to demonstrate the effectiveness of theoretical results.     

Novel closed-loop approaches for precise relative navigation of widely separated GPS receivers in LEO

This paper deals with the relative navigation of a formation of two spacecrafts separated by hundreds of kilometers based on processing dual-frequency differential carrier-phase GPS measurements. Specific requirements of the considered application are high relative positioning accuracy and real-time on board implementation. These can be conflicting requirements. Indeed, if on one hand high accuracy can be achieved by exploiting the integer nature of double-difference carrier-phase ambiguities, on the other hand the presence of large ephemeris errors and differential ionospheric delays makes the integer ambiguities determination challenging. Closed-loop schemes, which update the relative position estimates of a dynamic filter with feedback from integer ambiguities fixing algorithms, are customarily employed in these cases. This paper further elaborates such approaches, proposing novel closed loop techniques aimed at overcoming some of the limitations of traditional algorithms. They extend techniques developed for spaceborne long baseline relative positioning by making use of an on-the-fly ambiguity resolution technique especially developed for the applications of interest. Such techniques blend together ionospheric delay compensation techniques, nonlinear models of relative spacecraft dynamics, and partial integer validation techniques. The approaches are validated using flight data from the Gravity Recovery and Climate Experiment (GRACE) mission. Performance is compared to that of the traditional closed-loop scheme analyzing the capability of each scheme to maximize the percentage of correctly fixed integer ambiguities as well as the relative positioning accuracy. Results show that the proposed approach substantially improves performance of the traditional approaches. More specifically, centimeter-level root-mean square relative positioning is feasible for spacecraft separations of more than 260 km, and an integer ambiguity fixing performance as high as 98% is achieved in a 1-day long dataset. Results also show that approaches exploiting ionospheric delay models are more robust and precise of approaches relying on ionospheric-delay removal techniques.     

Robust attitude coordinated control for spacecraft formation with communication delays

In this paper,attitude coordinated tracking control algorithms for multiple spacecraft formation are investigated with consideration of parametric uncertainties,external disturbances,communication delays and actuator saturation.Initially,a sliding mode delay-dependent attitude coordinated controller is proposed under bounded external disturbances.However,neither inertia uncertainty nor actuator constraint has been taken into account.Then,a robust saturated delay dependent attitude coordinated control law is further derived,where uncertainties and external disturbances are handled by Chebyshev neural networks (CNN).In addition,command filter technique is introduced to facilitate the backstepping design procedure,through which actuator saturation problem is solved.Thus the spacecraft in the formation are able to track the reference attitude trajectory even in the presence of time-varying communication delays.Rigorous analysis is presented by using Lyapunov-Krasovskii approach to demonstrate the stability of the closed-loop system under both control algorithms.Finally,the numerical examples are carried out to illustrate the efficiency of the theoretical results.     

Temporal and spatial stochastic behaviour of high-frequency slant tropospheric delays from simulations and real GPS data

In this paper, a turbulence theory-based simulation procedure for slant tropospheric delay variations is presented. Based on this procedure tropospheric delay variations are simulated for three different geometric scenarios. The stochastic behaviour of the generated time series is assessed in terms of temporal structure functions. It is shown that the temporal structure functions – in general – follow a 5/3 to 2/3 power-law behaviour. Deviations from this behaviour due to the complex interaction between varying observation geometry and atmospheric/turbulent conditions are discussed.     

Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines

GPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zero-difference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters.     

Attenuation prediction for fade mitigation using neural network with in situ learning algorithm

Increasing demand of bandwidth in communication satellites has forced satellite links to be designed in Ku bands and above. But at these frequencies, rain and other tropospheric elements result in large attenuation. To mitigate the tropospheric attenuation of microwave satellite signals above 10 GHz using any standard Fade Mitigation Technique (FMT), it is essential to have a priori knowledge about the level of attenuation. Hence, short-term rain attenuation prediction models play a key role in maintaining the link in which necessary compensation can be applied depending on the early information of attenuation. This paper presents a method of attenuation prediction using Adaptive Artificial Neural Network. Here In situ Learning Algorithm (ILA) has been used to enable the system to track the non-stationary nature of the attenuation. To validate this, Ku Band data, collected at three different sites in India have been used for the purpose of prediction. The performance of the algorithm is determined through the estimation of prediction accuracy by comparing the predicted values with the measured data. Results obtained using the mentioned technique shows considerably good accuracy even up to 20 s of prediction interval with acceptable ratio between the under and over predictions. The prediction performance is evaluated for different prediction intervals. Furthermore the present model is also compared with the persistence model and the relative performance is quantified.