Autonomous orbit determination of deep space probe based on the Sun line-of-sight vector

2010 ◽  
Author(s):  
Pingyuan Cui ◽  
Xiaohua Chang ◽  
Hutao Cui
Keyword(s):  
Orbit Determination ◽  
Line Of Sight ◽  
The Sun ◽  
Space Probe ◽  
Deep Space ◽  
Autonomous Orbit Determination

scholarly journals Starspots Magnetic field by transit mapping

2013 ◽  
Vol 9 (S302) ◽  
pp. 220-221
Author(s):  
Adriana Válio ◽  
Eduardo Spagiari
Keyword(s):  
Magnetic Field ◽  
Light Curve ◽  
Field Component ◽  
Solar Magnetic Field ◽  
Line Of Sight ◽  
The Sun ◽  
Using Data ◽  
The Magnetic Field ◽  
Spot Temperature

AbstractSunspots are important signatures of the global solar magnetic field cycle. It is believed that other stars also present these same phenomena. However, today it is not possible to observe directly star spots due to their very small sizes. The method applied here studies star spots by detecting small variations in the stellar light curve during a planetary transit. When the planet passes in front of its host star, there is a chance of it occulting, at least partially, a spot. This allows the determination of the spots physical characteristics, such as size, temperature, and location on the stellar surface. In the case of the Sun, there exists a relation between the magnetic field and the spot temperature. We estimate the magnetic field component along the line-of-sight and the intensity of sunspots using data from the MDI instrument on board of the SOHO satellite. Assuming that the same relation applies to other stars, we estimate spots magnetic fields of CoRoT-2 and Kepler-17 stars.

Autonomous orbit determination and its error analysis for deep space using X-ray pulsar

2014 ◽  
Vol 32 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Dongzhu Feng ◽  
Hehe Guo ◽  
Xin Wang ◽  
Xiaoguang Yuan
Keyword(s):  
Error Analysis ◽  
Orbit Determination ◽  
Deep Space ◽  
X Ray ◽  
Autonomous Orbit Determination

scholarly journals Autonomous Orbit Determination for Lagrangian Navigation Satellite Based on Neural Network Based State Observer

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Youtao Gao ◽  
Tanran Zhao ◽  
Bingyu Jin ◽  
Junkang Chen ◽  
Bo Xu
Keyword(s):  
Neural Network ◽  
Orbit Determination ◽  
Transition Matrix ◽  
State Observer ◽  
Nonlinear Perturbations ◽  
The Neural Network ◽  
Autonomous Orbit Determination ◽  
Simulation Results ◽  
Libration Orbits

In order to improve the accuracy of the dynamical model used in the orbit determination of the Lagrangian navigation satellites, the nonlinear perturbations acting on Lagrangian navigation satellites are estimated by a neural network. A neural network based state observer is applied to autonomously determine the orbits of Lagrangian navigation satellites using only satellite-to-satellite range. This autonomous orbit determination method does not require linearizing the dynamical mode. There is no need to calculate the transition matrix. It is proved that three satellite-to-satellite ranges are needed using this method; therefore, the navigation constellation should include four Lagrangian navigation satellites at least. Four satellites orbiting on the collinear libration orbits are chosen to construct a constellation which is used to demonstrate the utility of this method. Simulation results illustrate that the stable error of autonomous orbit determination is about 10 m. The perturbation can be estimated by the neural network.

A New Algorithm for Onboard Autonomous Orbit Determination of Navigation Satellites

2011 ◽  
Vol 64 (S1) ◽  
pp. S162-S179 ◽  
Author(s):  
Haihong Wang ◽  
Zhonggui Chen ◽  
Jinjun Zheng ◽  
Haibin Chu
Keyword(s):  
Data Processing ◽  
Orbit Determination ◽  
Transition Matrix ◽  
State Transition ◽  
State Transition Matrix ◽  
Processing Unit ◽  
Data Processing Unit ◽  
Autonomous Orbit Determination ◽  
Computing Method

Autonomous orbit determination of a navigation constellation is the process by which the orbit parameters of navigation satellites are autonomously calibrated onboard the satellites without the need for external aids. It commonly uses a satellite onboard data processing unit and a filtering method to process the measurements of inter-satellite ranges. The onboard data processing unit is the main module of autonomous navigation systems. In this paper, the two main factors that affect the accuracy of autonomous orbit determination for a navigation constellation are discussed first, and then a distributed onboard algorithm for autonomous orbit determination of navigation satellites is proposed. This method is based on a long-term ephemeris prediction and is suitable for the satellite hardware capability. The main feature of this method is that both the distributed computing method and an onboard analytical state transition matrix are used to process inter-satellite range measurements. One of the main advantages of this approach is high-speed computing since the amount of calculations needed is significantly less than that of the centralised computing method and those distributed methods that need to use an onboard numerical integrator. Another advantage of this approach is that the use of the onboard analytical state transition matrix algorithm can save a great amount of resources for both ground-to-satellite data transmissions and data storage units in satellites’ hardware. This could result in substantial cost reduction for space missions. Finally, a simulation method used for testing the proposed algorithm is presented. Results of tests over a period of 90 days show that the user range error of autonomous orbit determination derived from the proposed method is less than three metres.

Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

2018 ◽  
Vol 92 (10) ◽  
pp. 1155-1169 ◽  
Author(s):  
Chengpan Tang ◽  
Xiaogong Hu ◽  
Shanshi Zhou ◽  
Li Liu ◽  
Junyang Pan ◽  
...  
Keyword(s):  
Orbit Determination ◽  
Satellite Link ◽  
Autonomous Orbit Determination ◽  
New Generation ◽  
Initial Results

scholarly journals Deep-Space Optical Navigation for M-ARGO Mission

2021 ◽  
Author(s):  
V. Franzese ◽  
F. Topputo ◽  
F. Ankersen ◽  
R. Walker
Keyword(s):  
Optical Sensors ◽  
Orbit Determination ◽  
Autonomous Navigation ◽  
Communication Systems ◽  
Electric Propulsion ◽  
Line Of Sight ◽  
Optical Navigation ◽  
Deep Space ◽  
Space Navigation ◽  
Operational Costs

AbstractThe Miniaturised Asteroid Remote Geophysical Observer (M-ARGO) mission is designed to be ESA’s first stand-alone CubeSat to independently travel in deep space with its own electric propulsion and direct-to-Earth communication systems in order to rendezvous with a near-Earth asteroid. Deep-space Cubesats are appealing owing to the scaled mission costs. However, the operational costs are comparable to those of traditional missions if ground-based orbit determination is employed. Thus, autonomous navigation methods are required to favour an overall scaling of the mission cost for deep-space CubeSats. M-ARGO is assumed to perform an autonomous navigation experiment during the deep-space cruise phase. This paper elaborates on the deep-space navigation experiment exploiting the line-of-sight directions to visible beacons in the Solar System. The aim is to assess the experiment feasibility and to quantify the performances of the method. Results indicate feasibility of the autonomous navigation for M-ARGO with a 3σ accuracy in the order of 1000 km for the position components and 1 m/s for the velocity components in good observation conditions, utilising miniaturized optical sensors.

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