Analisis Fusi Sensor Gnss Low-Cost Dan Imu Menggunakan Kalman Filter Untuk Meningkatkan Akurasi Navigasi Kendaraan Selama Gnss Signal Outage.

Erfianti, Risa (2022) Analisis Fusi Sensor Gnss Low-Cost Dan Imu Menggunakan Kalman Filter Untuk Meningkatkan Akurasi Navigasi Kendaraan Selama Gnss Signal Outage. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sistem navigasi pada kendaraan di darat umumnya memanfaatkan sensor Global Navigation Satellite System (GNSS) dan Inertial Measurement Unit (IMU) untuk memberikan informasi posisi, kecepatan, dan orientasi. GNSS memiliki kelebihan dalam memberikan informasi posisi yang akurat ketika dapat membentuk Line of Sight (LOS) dengan minimal empat satelit. Namun, akurasi tersebut dapat menurun ketika berada di wilayah perkotaan yang padat dengan gedung-gedung tinggi karena jumlah satelit yang terlihat kurang dari empat (GNSS signal outage). Sedangkan, IMU melakukan pengukuran orientasi wahana dengan frekuensi pembaruan yang tinggi dan tidak dipengaruhi oleh kondisi lingkungan, namun terdapat efek drift yang menyebabkan kesalahan pengukuran akan terakumulasi. Salah satu teknik fusi sensor berbasis low-cost yaitu dengan meningkatkan algoritma integrasi tanpa sensor tambahan. Peningkatan algoritma integrasi GNSS/IMU pada penelitian ini akan dilakukan dengan menggunakan model pergerakan mobil pada 3 Degree of Freedom (DOF), menggunakan algoritma Unscented Kalman Filter (UKF), dan memanfaatkan least square pengamatan GNSS dalam penentuan error covariance. Hasil fusi tersebut dianalisis terhadap referensi yaitu fusi yang dilakukan oleh Modul U-Blox F9R. Pada kondisi free outage, hasil fusi Differential GNSS (DGNSS) dan IMU terfilter mampu meningkatkan akurasi posisi easting dan northing hingga 93,02% dan 93,03% dibanding penggunaan stand-alone GNSS. Namun, pada kondisi outage akurasi yang dihasilkan fusi masih tergolong rendah yaitu sebesar 13.378 m pada easting dan 17.551 m pada northing. Hal ini terjadi karena peningkatan algoritma yang diajukan pada penelitian ini belum cukup untuk mengompensasi drift pengukuran sensor IMU tanpa adanya sensor tambahan selama kondisi outage.
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Ground vehicle navigation systems commonly utilize the Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to provide information such as position, velocity, and orientation. GNSS can provide accurate positioning when establishing a Line of Sight (LOS) with a minimum of four satellites. However, this accuracy may decrease significantly in specific environments, such as in dense urban areas with tall buildings, because the number of visible satellites is less than four (GNSS signal outage). In contrast, the IMU measures the vehicle's orientation with a high-frequency update that is not influenced by environmental conditions. However, a drift effect causes the measurement errors to accumulate. One of the GNSS/IMU sensor fusion techniques, especially for a low-cost navigation system, is improving the integration algorithm without additional sensors. In this study, the GNSS/IMU integration algorithm will be improved by defining a car movement model at 3 Degree of Freedom (DOF), using the Unscented Kalman Filter (UKF) algorithm, and utilizing the least square of GNSS observations to determine error covariance. The fusion results were analyzed against the reference, namely the fusion performed by the U-Blox F9R Module. During the free outage condition, the fusion of Differential GNSS (DGNSS) and filtered IMU was proven to increase the accuracy of easting and northing position up to 93.02% and 93.03% compared to the use of stand-alone GNSS. However, in outage conditions, the fusion accuracy is still relatively low, namely 13,378 m and 17,551 m in the east and north direction, respectively. It happens because the algorithm improvement proposed in this study is insufficient to compensate for IMU sensor measurement drift without the additional sensors during outage conditions.

Item Type:	Thesis (Masters)
Additional Information:	RTG 526.6 Erf a-1 2022
Uncontrolled Keywords:	GNSS Signal Outage, Fusi Sensor GNSS/IMU, Land Vehicle, Unscented Kalman Filter, 3 DOF. GNSS Signal Outage, GNSS/IMU Sensor Fusion, Land Vehicle, Unscented Kalman Filter, 3 DOF.
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL798.N3 Global Positioning System.
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	13 May 2026 08:09
Last Modified:	13 May 2026 08:09
URI:	http://repository.its.ac.id/id/eprint/133196

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