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http://dx.doi.org/10.9723/jksiis.2017.22.5.039

Tracking Performance Enhancement of Space Launch Vehicle Based on Adaptive Kalman Filter  

Han, Yoo Soo (한국항공우주연구원 나로우주센터)
Song, Ha Ryong (한국항공우주연구원 나로우주센터)
Lee, In Soo (경북대학교 IT대학 전자공학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.22, no.5, 2017 , pp. 39-49 More about this Journal
Abstract
A Space Launch Vehicle (SLV) for Launching Satellites Consists of Multi-stage Rockets for the Purpose of Efficient Flight and Accomplishes the Launch Mission through Flight Events such as Stage Separation, Engine Start and Stop. In this Process, the SLV is Supposed to Undergo the Processes of the Powered Flight Section in which the Engine Generates Thrust and the Ballistic Flight Section in which there is no Thrust Repeatedly. Because it is Difficult to Express these Flight Characteristics of the SLV as a Single Dynamics Model, much Research on Tracking Algorithms using Multiple Models has been Undertaken. In case of using the Multiple Model Tracking Algorithm, it is Expected to Improve the Tracking Performance of the SLV. However, it is Difficult to Select Proper Dynamics Models to be used and the Calculation Amount Increases due to the use of Multiple Models. In this Paper, we Propose a Method to Track the SLV with Diverse Flight Characteristics Efficiently by only Two Kalman Filters using Constant Acceleration Model and Adaptive Singer Model.
Keywords
Kalman Filter; Adaptive Singer Model; Space Launch Vehicle;
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  • Reference
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