gyroscopyГироскопия и навигацияGiroskopiya i Navigatsiya0869-70352075-0927AO «Концерн «ЦНИИ «Электроприбор»HUSCUZgyroscopy-21Research ArticleСтатьиКалибровка интегрированной системы «Одометр – Лидар – Гироскоп» в режиме реального времени для определения местоположения с использованием карт в отсутствие сигналов ГНССReal-time Calibration of Odometer in Integration with LiDAR and Gyroscope for Map-aided Positioning During GNSS OutagesЭль-ТохеиМ.El-TokheyM.

Эль-Тохеи Мохамед. Профессор

Каир

Cairo

ЭльхабибиМ.ElhabibyM.

Эльхабиби Мохамед. Профессор

Каир

Cairo

ХассанТ.Tarek HassanT.

Хассан Тарек. Доктор наук, доцент

Каир

Cairo

Инженерный факультет, Университет Аин ШамсЕгипетFaculty of Engineering, Ain Shams UniversityEgyptИженерный факультет, Университет Аин ШамсЕгипетFaculty of Engineering, Ain Shams UniversityEgypt2024160520253224665Copyright © Эль-Тохеи М., Эльхабиби М., Хассан Т., 20252025Эль-Тохеи М., Эльхабиби М., Хассан Т.El-Tokhey M., Elhabiby M., Tarek Hassan T.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.gyroscopy.ru/jour/article/view/21

В последнее время значительное количество исследований сосредоточено на решении проблемы достоверного определения местоположения объектов в режиме реального времени в сложной окружающей обстановке. Решение этой задачи – важнейшее условие для разработки разного рода интеллектуальных транспортных систем (ИТС). С учетом ограничений функционирования глобальных навигационных спутниковых систем (ГНСС) в условиях города и пригородов, где пропадание сигнала – обычное явление, создание независимой системы позиционирования, обеспечивающей непрерывную выработку точных данных о местоположении объектов в отсутствие сигналов ГНСС, становится все более актуальной задачей. Для ее решения были проведены эксперименты в целях изучения комбинации лазерного дальномера (лидара), гироскопов и одометров. В настоящей работе с опорой на данные предыдущих исследований рассматривается коррекция показаний одометров с использованием дорожных карт, а также методика сегментирования дороги в режиме реального времени. Для оценки нового метода моделировалось отсутствие сигнала ГНСС в течение трех пятиминутных интервалов. При этом использовались реальные данные, полученные от движущегося объекта, обработка которых выполнялась в моделируемом режиме реального времени. Результаты экспериментов показали заметное улучшение точности навигации. В частности, применение метода калибровки в реальном времени снизило погрешность позиционирования на 0,9, 1,0 и 0,2 м в каждом из эпизодов пропадания сигнала ГНСС соответственно. Повышение точности во втором и третьем эпизодах было достигнуто за счет получения более точных данных о параметрах дороги. В работе предложен упрощенный алгоритм обработки данных лидара, благодаря которому достигнутые средние значения погрешности позиционирования составили 1,8 и 1,8 м, а ее максимальные значения – 4,0 и 3,8 м соответственно.

In recent research, signicant eorts have focused on achieving dependable real-time positioning in challenging environments, which is a crucial aspect for the development of various Intelligent Transportation Systems (ITS) applications. Given the limitations of Global Navigation Satellite Systems (GNSS) in suburban and urban areas, where signal blockage is common, there is a growing need for an independent positioning system to provide accurate and continuous location data during GNSS disruptions. Previous studies have explored the combination of Light Detection and Ranging (LiDAR), gyroscopes, and odometer sensors for this purpose. This research builds upon that foundation by introducing a real-time calibration process for odometer readings, leveraging road maps and a road segmentation technique. To evaluate this method, real-world data collected from a moving vehicle was used, incorporating three ve-minute simulated GNSS outages. These data were processed in a simulated real-time mode. The results from these tests are promising, showing notable improvements in navigation accuracy. Specically, the application of the real-time calibration method led to an enhancement in positioning accuracy by 0.9m, 1.0m, and 0.2m for each of the GNSS outages, respectively, highlighting the critical role of this calibration process. The performance of the algorithm was improved during the second and third outages with the increased availability of line features. The proposed simpler LiDAR data processing algorithm could achieve mean positional errors of 1.8m and 1.8m, with maximum errors of 4.0m and 3.8m, respectively.

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The authors declare that there are no conflicts of interest present.