Ground Tracking System Research Articles

Onboard Pointing Error Detection and Estimation of Observation Satellite Data Using Extended Kalman Filter.

The satellite communication is embellished constantly by providing information, ensuring security, and enables the communication among huge at a particular time efficiently. The satellite navigation helps in determining the people's location. Global development, natural disasters, change in climatic conditions, agriculture crop growth, etc., are monitored using satellite observation. Hence, the satellite includes detailed information data, and it must be protected confidentially. The field of the satellite is enhanced at an astonishing pace. Satellite data play an important role in this modern world; hence, the onboard-satellite data must secure through the proper selection of error detection and estimation schema. Lightweight deep learning algorithm based on Extended Kalman Filter (KFK) is proposed to detect and estimate onboard pointing error such as an error in attitude and orbit. The Extended Kalman Filter (EKF) is widely used in the satellite system. EKF is utilized in this proposed model to detect the onboard pointing error such as attitude and orbit determination. An autonomous estimation of orbit position is possible through space-borne gravity. The information obtained through the observation of satellite data is compared with the accurate gravity model in detecting the error. The utilization of EKF reduces the dependence of the ground tracking system in satellite determination. The orbital altitude and orbital position are the most important challenges faced in the satellite determination system. The satellite model using the Extended Kalman Filter is an optimum method in estimating the orbital parameters. The errors in the linearization process are detected, and this can be overcome through the proper selection of linear expansion point with the EKF algorithmic model with the Jacobian matrix calculation. The results show that the EKF implementation helps in attaining better accuracy than other methodologies. Its contribution is enormous to many space missions, autonomous rendezvous and docking for manned and unmanned missions (e.g., ISS operations and beyond, in-orbit servicing, and in-orbit refueling), routine satellite OD operations, orbital debris removal systems, Space Situational Awareness (SSA) operations, and others.

Design of Wind Pendulum Control System Based on Improved Genetic PID Algorithm

Aiming at the attitude disturbance of the airborne ground tracking system and the problem of pointing stability under high-frequency vibration, and effectively utilizing the wind power outside the cabin, a new type of airborne ground tracking simulation platform-wind pendulum control system is designed, designed to TMS320F28335 For the control system of the main control chip, the controller adopts an improved genetic PID algorithm to realize the function of rapid braking and movement according to any desired trajectory. The simulation results show that, compared with the traditional PID algorithm, the improved genetic PID algorithm can better solve the problem of chattering, overshoot and non-fast convergence in a limited time in the system. At the same time, it has strong robustness to external disturbances, and can get the full physical simulation needs of airborne ground tracking systems.

An Interplanetary Network for Spacecraft Autonomous Navigation

An interplanetary autonomous navigation network, named the Internet of Spacecraft (IoS), is proposed in this paper to enable a Solar System-wide autonomous navigation capability for spacecraft. This network consists of two types of spacecraft, namely host and client spacecraft. The former provide the absolute reference for the whole network, and the latter determine their positions by communicating with the host spacecraft or other client spacecraft. To investigate the performance of IoS, a detailed application scheme that supports a flight from Earth to Mars is developed and analysed. IoS is not a simple extension of the navigation constellation. It is independent of the ground tracking system and the configuration of the network is flexible in that any spacecraft-installed identical device can be added to it. Moreover, client spacecraft whose positions have been determined can also be regarded as host spacecraft and provide further navigation information to others. This paper aims to provide technical support for future deep space exploration.

Improving extended Kalman filter algorithm in satellite autonomous navigation

With the goal of reducing dependence on ground tracking systems, satellite autonomous navigation technologies are developed quickly in the recent several decades. However, precise orbit determination at high orbital altitudes is an important and challenging problem. In this paper, the nonlinear real-time orbit determination problem is investigated. Combined with satellite dynamical model, extended Kalman filter is explored to estimate satellite orbit parameters. Further, considering errors occur in linearization processing, two improvements for the extended Kalman filter algorithm, i.e. extended Kalman filter-I and extended Kalman filter-II, are proposed based on Lagrange’s mean value theorem, and respectively focus on choosing better linear expansion point and Jacobian matrix calculation point. Extensive simulations show that extended Kalman filter-I and extended Kalman filter-II significantly enhance orbit accuracy, compared with extended Kalman filter. And the increases in calculation complexity are acceptable. Finally, the robustness of extended Kalman filter-I and extended Kalman filter-II is analyzed by given different initial position errors, and results show that extended Kalman filter-I and extended Kalman filter-II have better robustness than extended Kalman filter.

발사체 추적자료 후처리를 통한 비행궤적 생성

나로우주센터의 발사통제시스템은 우주발사체의 비행궤적과 상태정보를 감시하기 위하여 지상추적시스템(추적레이더 2대, 원격자료수신장비 4대, 광학추적장비 1대)으로부터 정보를 받아 처리한다. 각 추적장치는 주로 다중경로나 클러터, 전파굴절에 의해 자체 오차를 나타내고 있어 전송된 정보들 중 하나만을 이용해서는 우주발사체의 실제 궤적을 판별할 수 없다. 본 논문에서는 취득된 추적자료의 후처리를 통해 우주발사체 비행궤적을 생성해내는 방법을 제시한다. 본 후처리 알고리즘은 크게 대기의 전파굴절에 따른 오차를 보정하는 부분과 다중센서 정보를 융합하는 부분으로 나뉘며, 효과적인 센서 융합을 위해 등가속 운동모델에 기반한 분산식 칼만필터를 구성하였다. 실측 자료의 후처리 적용 결과, 어떤 단일 센서에 의한 것 보다 오차가 최소화된 발사궤적을 얻을 수 있었다. For monitoring the flight trajectory and the status of a launch vehicle, the mission control system in NARO space center process data acquired from the ground tracking system, which consists of two tracking radars, four telemetry stations, and one electro-optical tracking system. Each tracking unit exhibits its own tracking error mainly due to multi-path, clutter and radio refraction, and by utilizing only one among transmitted informations, it is not possible to determine the actual vehicle trajectory. This paper presents a way of generating flight trajectory via post-processing the data received from the ground tracking system. The post-processing algorithm is divided into two parts: compensation for atmosphere radio refraction and multi-sensor fusion, for which a decentralized Kalman filter was adopted and implemented based on constant acceleration model. Applications of the present scheme to real data resulted in the flight trajectory where the tracking errors were minimized than done by any one sensor.

Orbit determination for Chang’E-2 lunar probe and evaluation of lunar gravity models

The Unified S-Band (USB) ranging/Doppler system and the Very Long Baseline Interferometry (VLBI) system as the ground tracking system jointly supported the lunar orbit capture of both Chang’E-2 (CE-2) and Chang’E-1 (CE-1) missions. The tracking system is also responsible for providing precise orbits for scientific data processing. New VLBI equipment and data processing strategies have been proposed based on CE-1 experiences and implemented for CE-2. In this work the role VLBI tracking data played was reassessed through precision orbit determination (POD) experiments for CE-2. Significant improvement in terms of both VLBI delay and delay rate data accuracy was achieved with the noise level of X-band band-width synthesis delay data reaching 0.2–0.3 ns. Short-arc orbit determination experiments showed that the combination of only 15 min’s range and VLBI data was able to improve the accuracy of 3 h’s orbit using range data only by a 1–1.5 order of magnitude, confirming a similar conclusion for CE-1. Moreover, because of the accuracy improvement, VLBI data was able to contribute to CE-2’s long-arc POD especially in the along-track and orbital normal directions. Orbital accuracy was assessed through the orbital overlapping analysis (2 h arc overlapping for 18 h POD arc). Compared with about 100 m position error of CE-1’s 200 km200 km lunar orbit, for CE-2’s 100 km100 km lunar orbit, the position errors were better than 31 and 6 m in the radial direction, and for CE-2’s 15 km100 km orbit, the position errors were better than 45 and 12 m in the radial direction. In addition, in trying to analyze the Delta Differential One-Way Ranging (DOR) experiments data we concluded that the accuracy of DOR delay was dramatically improved with the noise level better than 0.1 ns and systematic errors better calibrated, and the Short-arc POD tests with DOR data showed excellent results. Although unable to support the development of an independent lunar gravity model, the tracking data of CE-2 provided evaluations of different lunar gravity models through POD. It is found that for the 100 km100 km lunar orbit, with a degree and order expansion up to 165, JPL’s gravity model LP165P did not show noticeable improvement over Japan’s SGM series models (100×100), but for the 15 km×100 km lunar orbit, a higher degree-order model can significantly improve the orbit accuracy. Chang’E-2, VLBI, orbit determination, lunar gravity field

Diagnostic expert system for scientific satellite

We have successfully developed a diagnostic expert system for scientific satellites, and applied it to the geomagnetic tail observation satellite named GEOTAIL, which was launched in July 1992. In recent years satellite operators are required to have an increasingly wide variety of experts' knowledge both on the spacecraft and on the ground tracking systems in order to check the satellite's conditions exactly. The GEOTAIL operation will extend over a long period of time, so it is not practical to post such high level operators in the control room all the time because of economic problems and limited personnel resources. This diagnostic expert system enables an operator who doesn't have special knowledge to diagnose the whole status of the satellite easily and with a high level of expertise. Most of the necessary information for trouble diagnosis is automatically set using an on-line data feed system.