Supnithi, Pornchai

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Supnithi, Pornchai
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Supnithi, P.
Supnithi, Pomchai
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pornchai.su@kmitl.ac.th

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    Performances of GAGAN Satellite-Based Augmentation System in Thailand Region
    (2020-07-01)
    Sophan, Somkit
    ;
    Phakphisut, Watid
    ;
    Myint, Lin M.M.
    ;
    Supnithi, Pornchai
    The ASEAN IVO project currently supports the research related to GNSS and ionospheric data products for disaster prevention and aviation in low-latitude regions. Satellite-Based Augmentation System (SBAS) is vital to air navigation in many regions around the world. In Thailand, the L1-frequency SBAS corrections can be received from the GPS Aided Geo Augmented Navigation (GAGAN) system which is intended for use over Indian airspace. In this work, we analyze the performances of the GAGAN system in Thailand on quiet and disturbed days in March 2019 by applying the entire corrections received at King Mongkut's Institute of Technology Ladkrabang station. The 95-percent horizontal and vertical accuracies on quiet days are 1.52 and 3.18 meters, respectively. In contrast, on disturbed days they are 1.97 and 3.41 meters, respectively.
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    Neural Network Prediction of Receiver Bias in Ionospheric Delay Computation
    (2022-01-01)
    Thu, Phyo C.
    ;
    Supnithi, Pornchai
    ;
    Min Myint, Lin Min
    ;
    Saito, Susumu
    ;
    Saekow, Apitep
    An important measure typically used to understand ionosphere properties and disturbances is total electron content (TEC). A typical approach to calculating the ionospheric TEC is by analyzing dual-frequency GPS data. Satellite and receiver biases are the primary discrepancies in TEC computation. In this work, we develop a neural network to predict the instrumental receiver bias based on slant TEC. The minimum standard deviation method is used to calculate the receiver bias. Neural network with two hidden layers is trained with datasets and then used to predict the receiver bias. The predicted receiver bias from the proposed neural network differs from the baseline method by about 10 to 20 percent.
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    Improvement of single point positioning accuracy by using GAGAN satellite-based augmentation system in Thailand Region
    (2021-05-19)
    Sophan, Somkit
    ;
    Phakphisut, Watid
    ;
    Myint, Lin M.M.
    ;
    Supnithi, Pornchai
    Although GAGAN satellite-based augmentation system (SBAS) provides ionospheric correction service to India and surrounding areas, the correction values do not cover the entire region of Thailand and even at provided grids, they may not be sufficiently accurate. Hence, this work, we propose a local ionospheric delay estimation method based on the geo-free ionospheric delay estimation. Then the estimated ionospheric delays are applied together with the fast and long-term corrections of GAGAN SBAS to improve the positioning errors. The results show that the estimated ionospheric delays can improve the user positioning errors in terms of horizontal and vertical errors up to 0.5 and 1 meter, respectively.
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    Performance improvement of the GAGAN satellite-based augmentation system based on local ionospheric delay estimation in Thailand
    (2022-10-01)
    Sophan, Somkit
    ;
    Myint, Lin M.M.
    ;
    Saito, Susumu
    ;
    Supnithi, Pornchai
    Satellite-Based Augmentation System (SBAS) is essential to support aircraft navigation. L1 SBAS operates on the L1 frequency (1575.42 MHz) and is currently still of interest since all GNSS satellites and receivers do not fully support additional frequencies such as L5 (1176.45 MHz). Although the Global Positioning System (GPS) aided Geo Augmented Navigation (GAGAN) SBAS is available, the performances are degraded due to the discrepancies of the ionospheric correction over Thailand and surrounding areas. Hence, in this work, we propose a new method based on the geometry-free ionospheric delay estimation with a single frequency (L1) and a single reference station requirement. The local ionospheric delays are estimated based on the proposed method with the observed GPS and GAGAN data in Thailand. Then the ionospheric corrections are obtained from the estimated local ionospheric delays. The analysis shows that using the estimated corrections, the positioning errors are reduced both on quiet days and locally disturbed days in 2019. More reductions in the positioning errors are found in September and December than other months. In addition, we perform a preliminary availability assessment of two critical phases of flights. The GAGAN performances with the proposed method for the APV-I and LPV-200 categories are improved up to 57% and 53%, respectively, in comparison with the baseline method of the IGP correction.