Innovative data fusion technology for low-cost multisensor-aided inertial integrated navigation and kinematic positioning

自20世纪90年代末以来，gnss辅助惯性组合导航与定位在直接地理参考（DG）方面取得的显著进展，彻底改变了地理空间数据的参考方式。这种DG技术已经成为航空、海洋和陆地应用中移动测绘的卓越方法。这种现代技术的发展无疑为各种集成架构提供了充分的潜力，并对研究人员进一步研究创新的集成策略和算法提出了挑战。该研究项目旨在为技术进步和经济生产力创造创新的多传感器集成策略和数据融合方法，从而推动应用的明显增长和多样性。这些都是研究人员在DG技术和整个移动地图行业中面临的最新挑战。该计划提出了三个主题：(1)通过图像衍生测量提高多传感器辅助惯性组合导航的求解性能；(2)提高多传感器辅助惯性组合导航性能的先进滤波方法和小波去噪方法；(3)在较差或非gnss环境中开发替代辅助传感器和适当集成低成本惯性传感器的创新集成策略和算法。它的成功将对移动测绘界的学术研究和产业发展产生重大影响，特别是对低成本多传感器辅助惯性组合导航、室内导航以及恶劣或非gnss环境下的移动测绘的商业发展产生重大影响。研究成果将产生新的知识，提高我们对多传感器集成移动地图的理解，并推动相关的科学研究和产业应用。该研究计划将通过出版物、技术转让和商业化传播算法和方法，以显著降低硬件成本，并在允许的导航精度和可靠性下达到工业要求，从而有助于应对这一巨大挑战。

The remarkable progress made in direct georeferencing (DG) through GNSS-aided inertial integrated navigation and positioning has revolutionarily changed the way how to georeference geospatial data since late 1990s. This DG technology has become the preeminent method in mobile mapping for airborne, marine and land applications. This modern technological evolution definitely provides full potential for a great variety of integration architectures and is challenging researchers to further research innovative integration strategies and algorithms accordingly. This research program aims at creating innovative multisensor integration strategies and data fusion methods for technology advancement and economic productivity that can drive obvious application growth and diversity. These belong to the most recent challengeable tasks that researchers confront in the DG technology and the mobile mapping industry at large. This program proposes three main themes: (1) Improvement of solution performance of multisensor-aided inertial integrated navigation through image-derived measurements, (2) Advanced filtering methods and wavelet denoising methods for performance improvement of multisensor-aided inertial integrated navigation and (3) Innovative integration strategies and algorithms for exploitation of alternative aiding sensors in poor or non-GNSS environments and for appropriate integration of low cost inertial sensors. Its success will have a great impact on academic research and industrial development in the mobile mapping community, especially on the commercial development of low-cost multisensor-aided inertial integrated navigation, indoor navigation and mobile mapping in poor or non-GNSS environment. Research results will generate new knowledge and improve our understanding of multisensor integrated mobile mapping, and advance relevant scientific research and industrial applications. The proposed research program will contribute to meeting the great challenge to significantly reduce the hardware cost, and reaching the industrial requirements with the permissible navigation accuracy and reliability via the dissemination of algorithms and methods through publications, technology transfers and commercialization.