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，通过全球导航卫星系统辅助的惯性组合导航和定位在直接地理参考（DG）方面取得了显着进展，彻底改变了如何对地理空间数据进行地理参考的方式。该DG技术已成为机载、海洋和陆地应用中移动的测绘的卓越方法。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，并对研究人员提出了挑战，要求他们进一步研究创新的集成策略和算法。该研究计划旨在创建创新的多传感器集成策略和数据融合方法，以促进技术进步和经济生产力，从而推动应用增长和多样性。这些属于研究人员在DG技术和整个移动的测绘行业中面临的最新挑战性任务。该方案提出了三个主要主题：（1）通过图像衍生测量改进多传感器辅助惯性组合导航的解算性能，（2）改进多传感器辅助惯性组合导航性能的滤波方法和小波去噪方法;（3）创新的组合策略和算法，用于在性能较差或不稳定的情况下开发替代的辅助传感器。GNSS环境和低成本惯性传感器的适当集成。它的成功将对移动的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、室内导航和在恶劣或非GNSS环境下的移动的测绘的商业开发。研究成果将产生新的知识，提高我们对多传感器集成移动的测绘的理解，并推动相关的科学研究和工业应用。拟议的研究计划将有助于应对巨大的挑战，以显着降低硬件成本，并通过出版物，技术转让和商业化传播算法和方法，以允许的导航精度和可靠性达到工业要求。

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.