Обзор методов инерциальной навигации на основе глубокого обучения для навигации АНПА на больших дистанциях
EDN: XMYLOI
Аннотация
Инерциальные методы навигации автономных необитаемых подводных аппаратов (АНПА) позволяют обеспечить выполнение ими сложных задач в автоматическом режиме. Разработки в области традиционной инерциальной навигации ведутся в течение многих лет, и существует потребность в новых технических решениях. С помощью метода глубокого обучения можно автоматически выбирать и извлекать ключевые признаки в обрабатываемых данных, что широко применяется для распознавания изображений, речи, обработки текстов и в других областях. Хорошие результаты достигаются при обработке последовательно поступающих данных, например текста и речи. Очевидно, что выходные данные инерциальной навигации относятся к такому же типу информации. Многочисленные исследования показали, что модели на основе глубоких нейронных сетей можно использовать для снижения уровня шума инерциальных датчиков и дрейфа средств инерциальной навигации, а также комплексирования инерциальных данных с данными других датчиков. Кроме того, эти модели позволяют прогнозировать и уменьшать погрешности инерциальной навигации при длительном подводном плавании. В статье приводится обзор методов инерциальной навигации АНПА на основе глубокого обучения, включая новейшие достижения и тенденции развития.
Об авторах
Цинь Юань Хэ
Национальный институт инновационных оборонных технологий, Ака-
Доктор наук, Национальный институт инновационных оборонных технологий, Академия военных наук
Китай
Китай
Цинь Юань Хэ, доктор наук
Пекин
Хуа Пэн Ю
Национальный институт инновационных оборонных технологий, Академия военных наук
Китай
Китай
Хуа Пэн Ю, доктор наук
Пекин
Ю Чэнь Фан
Университет электронных наук и технологий Китая
Китай
Китай
Ю Чэнь Фан, доктор наук
факультет автоматизированного проектирования
Чэнду
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Рецензия
Для цитирования:
Хэ Ц.Ю., Ю Х.П., Фан Ю.Ч. Обзор методов инерциальной навигации на основе глубокого обучения для навигации АНПА на больших дистанциях. Гироскопия и навигация. 2023;31(3):122-135. EDN: XMYLOI
For citation:
He Q.Yu., Yu H.P., Fang Yu.Ch. Deep Learning-Based Inertial Navigation Technology for Autonomous Underwater Vehicle Long-Distance Navigation – A Review. Gyroscopy and Navigation. 2023;31(3):122-135. (In Russ.) EDN: XMYLOI
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