JOURNAL OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
Online ISSN : 2432-3691
Print ISSN : 1344-6460
ISSN-L : 1344-6460
Volume 71, Issue 5
Displaying 1-3 of 3 articles from this issue
Paper
  • Takeyasu Sakai, Mitsunori Kitamura, Atsushi Kezuka
    2023 Volume 71 Issue 5 Pages 203-208
    Published: 2023
    Released on J-STAGE: October 05, 2023
    JOURNAL RESTRICTED ACCESS

    The SBAS is the standard augmentation systems which ensure the integrity of navigation by providing augmentation information via satellite broadcast. Due to GNSS vulnerabilities, the signal authentication is being discussed to be added to the augmentation system including SBAS as a countermeasure against spoofing attacks. Here the authors propose a method to reduce Fast Correction messages of SBAS to secure the bandwidth for authentication information, because the current SBAS implementation does not have such vacant bandwidth. The method is compatible with the current system in terms that no performance degradation is expected.

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  • Shotaro Hamato, Seiji Tsutsumi, Hirotaka Yamashita, Tatsuro Shiohara, ...
    2023 Volume 71 Issue 5 Pages 209-217
    Published: 2023
    Released on J-STAGE: October 05, 2023
    JOURNAL RESTRICTED ACCESS

    Uncertainty quantification (UQ) of a numerical model of JAXA 6.5m × 5.5m Low-speed Wind Tunnel (LWT1) is conducted to realize model-based anomaly detection. The uncertainty evaluated by UQ is used to estimate the normal space of LWT1, and anomaly detection can be achieved by comparing the measurements and the estimated normal space. In the operating condition with the wind velocity in the test section of 9.7m/s, the 95% confidence interval of the predicted wind velocity is ranging from 5.50 to 9.80m/s, which is too large to realize anomaly detection with sufficient accuracy. Uncertainty management (UM) is conducted for reducing the uncertainty of the numerical model. Sobol's method is employed to find explanatory variables sensitive to the objective variable, and then, an additional experiment is conducted to reduce the uncertainty originating in those variables. The 95% confidence interval of the predicted wind velocity can be reduced to the range of 7.61 to 9.80m/s. Successful reduction of uncertainty is achieved through UM.

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The study Note
  • Takuma Katagiri, Yukihito Aoyama, Masaru Naruoka, Tetsujiro Ninomiya, ...
    2023 Volume 71 Issue 5 Pages 218-221
    Published: 2023
    Released on J-STAGE: October 05, 2023
    JOURNAL RESTRICTED ACCESS

    The usage of an accurate mathematical model of a turbofan engine installed into an airplane is essential for flight simulation and controller design. However, the acquisition of the model is difficult because it consists of proprietary information. Thus, we proposed that the model was estimated by applying system identification techniques to arbitrarily accessible flight data. As a practical example, the relationship between the thrust lever angle and the rotation speed of the low-pressure axis of an airplane turbofan engine was estimated. The estimated model, whose structure was postulated to be linear, successfully simulated the actual data in at least 82.96% fitness.

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