Using the Kalman filter to integrate GPS and IMU data in noisy environments
The article deals with the problem of improving the accuracy and reliability of navigation systems that use the integration of GPS and IMU data in a noisy environment. The main task is to reduce errors arising from the periodic absence of GPS and noise in IMU measurements. To solve this problem, we...
| 出版年: | Технічна інженерія |
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| 主要な著者: | , , , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
Zhytomyr Polytechnic State University
2024-12-01
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| 主題: | |
| オンライン･アクセス: | http://ten.ztu.edu.ua/article/view/319109 |
| 要約: | The article deals with the problem of improving the accuracy and reliability of navigation systems that use the integration of GPS and IMU data in a noisy environment. The main task is to reduce errors arising from the periodic absence of GPS and noise in IMU measurements. To solve this problem, we consider the use of the Kalman filter to predict and correct the system state based on available measurements, even in the case of partial or complete loss of the GPS signal. The research methods include a series of experiments aimed at modelling different scenarios: ideal conditions (no noise) and noise on both sensors (GPS and IMU). During the experiments, data on the real position and speed were collected and processed, which allowed us to evaluate the accuracy of the Kalman filter in different conditions and showed a significant reduction in the position error. |
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| ISSN: | 2706-5847 2707-9619 |