**5. Conclusions**

In this paper, an improved pedestrian navigation method based on indoor map assistance and particle filter is proposed. Based on the fact that particles cannot "going through the wall", this method limits the pedestrian navigation positioning error to a low range for a long time. In addition, a global search algorithm is proposed to solve the problem of high-precision localization of pedestrians in unfamiliar environments with unknown initial position and heading; An adaptive particle number calculation method in the process of particle resampling is also proposed, which can improve the calculation efficiency and achieve long-term high-precision navigation and positioning for indoor pedestrians.

The method proposed in this paper can be used in indoor environments such as disaster relief and rescue, medical search and rescue. With the building plan and inertial sensors, navigation and positioning accuracy can be maintained for a long time. This method is of great significance to the practical application of pedestrian inertial navigation.

In the future, we will further study the method of multi person cooperative navigation in a complex environment according to the method in this paper to obtain higher navigation and positioning accuracy in a longer period.

**Author Contributions:** Conceptualization, Z.W., L.X. and Z.X.; methodology, Z.W.; validation, Z.W., Y.D., Y.S. and C.S.; formal analysis, Z.W.; software, Z.W.; data curation, Y.D. and Y.S.; supervision, L.X. and Z.X., writing—original draft, Z.W., L.X. and Z.X.; writing—review and editing, Z.W., L.X., Z.X., Y.D., Y.S. and C.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Natural Science Foundation of China, grant number 61873125; The National Natural Science Foundation of China, grant number 62073163; The National Natural Science Foundation of China, grant number 62103285; Support for projects in special zones for national defense science and technology innovation; The advanced research project of the equipment development grant number 30102080101; National Basic Research Program, grant number JCKY2020605C009; The Natural Science Fund of Jiangsu Province, grant number BK20181291; The Aeronautic Science Foundation of China, grant number ASFC-2020Z071052001; The

Aeronautic Science Foundation of China, grant number 202055052003; The Fundamental Research Funds for the Central Universities, grant number NZ2020004; Shanghai Aerospace Science and Technology Innovation Fund, grant number SAST2019-085; Introduction plan of high end experts, grant number G20200010142. Foundation of Key Laboratory of Navigation, Guidance and Health-Management Technologies of Advanced Aerocraft (Nanjing Univ. of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Jiangsu Key Laboratory "Internet of Things and Control Technologies" & the Priority Academic Program Development of Jiangsu Higher Education Institutions, Science and Technology on Avionics Integration Laboratory. Supported by the 111 Project, grant number B20007.

**Data Availability Statement:** The study did not report any data. I choose to exclude this statement.

**Conflicts of Interest:** The authors declare no conflict of interest.
