Estimate Problems for Satellite Clusters

Reali, Fabrizio; Palmerini, Giovanni B.

doi:10.1109/aero.2008.4526272

Cited by 12 publications

(7 citation statements)

References 7 publications

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“…The addition of more complete filters, including multiple behavioral models [16] and recursive schemes more complex than EKF, already tested in spacecraft proximity dynamics [17], should work towards this goal.…”

Section: Visual / Infrared Data Fusionmentioning

confidence: 99%

Combining thermal and visual imaging in spacecraft proximity operations

Palmerini

2014

2014 13th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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Advances in multiple spacecraft operations require precise determination of the relative kinematic state of the platforms involved. Such knowledge – above all in case of non-cooperative approaches - can be usefully attained by means of imaging. However, the extremely varying light conditions in the orbital environment do not allow for extended operations in the visible spectrum. The paper investigates the possible coupling of thermal imagery with visible one in order to have a continued relative tracking even during eclipse. The focus is on simple camera devices, suitable for mounting onboard microsatellites, and on the combined (visual and infrared) image processing and data fusion helped by the purposeful modeling of the spacecraft dynamics and bus signature

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Section: Visual / Infrared Data Fusionmentioning

confidence: 99%

Combining thermal and visual imaging in spacecraft proximity operations

Palmerini

2014

2014 13th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

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“…We can see from the calculation process of the UKF filter that the UKF filter does not need to be linearized, which avoids the introduction of linearization errors, thereby improving the estimation accuracy. In addition, the UKF filter simplifies greatly the implementation effort; it is precisely because of this that the UKF filter is widely used in the field of navigation and positioning [28].…”

Section: Introduction To Ukf Algorithm and Its Implementation Stepsmentioning

confidence: 99%

Altimeter + INS/Giant LEO Constellation Dual-Satellite Integrated Navigation and Positioning Algorithm Based on Similar Ellipsoid Model and UKF

Yang

Jing

et al. 2021

Remote Sensing

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To solve the problem of location service interruption that is easily caused by incomplete visual satellite environments such as occlusion, urban blocks and mountains, we propose an altimeter + inertial navigation system (INS) + giant low earth orbit (LEO) dual-satellite (LEO2) switching integrated navigation algorithm based on a similar ellipsoid model and unscented Kalman filter (UKF). In addition to effectively improving the INS error, for the INS + LEO dual-satellite switching algorithm without altimeter assistance, our algorithm can also significantly suppress the problem of excessive navigation and positioning error caused by this algorithm in a long switching time, it does not require frequent switching of LEO satellites, and can ensure navigation and positioning functions without affecting LEO satellite communication services. In addition, the vertical dilution of precision (VDOP) value can be improved through the clock error elimination scheme, so, the vertical accuracy can be improved to a certain extent. For different altimeter deviations, we provide simulation experiments under different altimeter deviations; it can be found that after deducting the fixed height deviation, the algorithm can also achieve good accuracy. Compared with other typical algorithms, our proposed algorithm has higher accuracy, lower cost and stronger real-time performance, and is suitable for navigation and positioning scenarios in harsh environments.

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“…Reali and Palmerini provided a preliminary comparison of different estimation techniques to be used in formation flying navigation [31].…”

Section: Introductionmentioning

confidence: 99%

Research on the Effectiveness of Different Estimation Algorithm on the Autonomous Orbit Determination of Lagrangian Navigation Constellation

Gao

Chen

et al. 2016

International Journal of Aerospace Engineering

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The accuracy of autonomous orbit determination of Lagrangian navigation constellation will affect the navigation accuracy for the deep space probes. Because of the special dynamical characteristics of Lagrangian navigation satellite, the error caused by different estimation algorithm will cause totally different autonomous orbit determination accuracy. We apply the extended Kalman filter and the fading–memory filter to determinate the orbits of Lagrangian navigation satellites. The autonomous orbit determination errors are compared. The accuracy of autonomous orbit determination using fading-memory filter can improve 50% compared to the autonomous orbit determination accuracy using extended Kalman filter. We proposed an integrated Kalman fading filter to smooth the process of autonomous orbit determination and improve the accuracy of autonomous orbit determination. The square root extended Kalman filter is introduced to deal with the case of inaccurate initial error variance matrix. The simulations proved that the estimation method can affect the accuracy of autonomous orbit determination greatly.

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Estimate Problems for Satellite Clusters

Cited by 12 publications

References 7 publications

Combining thermal and visual imaging in spacecraft proximity operations

Combining thermal and visual imaging in spacecraft proximity operations

Altimeter + INS/Giant LEO Constellation Dual-Satellite Integrated Navigation and Positioning Algorithm Based on Similar Ellipsoid Model and UKF

Research on the Effectiveness of Different Estimation Algorithm on the Autonomous Orbit Determination of Lagrangian Navigation Constellation

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