UAV Sensing Data Optimisation: Comparison and Application of Key Filtering Algorithms

DOI

10.2991/978-94-6463-821-9_19How to use a DOI?

Keywords

UAVs; Filtering Algorithms; Kalman Filtering; Nonlinear Systems; Data Fusion

Abstract

With the wide application of UAV technology in several fields, the accuracy and reliability of the sensed data become critical. Therefore, this paper aims to explore the current status of the application of key filtering algorithms in the field of UAVs. This paper firstly introduces the development history of filtering algorithms, and then analyses in detail the basic principles, and mathematical models, as well as the advantages and disadvantages of various filtering algorithms. It is found that despite the theoretical advantages of Kalman filtering and its derivative algorithms, they still face many challenges in practical applications, such as nonlinear processing and computational complexity problems. Although particle filtering is able to deal with a wider range of nonlinear and non-Gaussian problems, its particle degradation and resampling problems are still difficult to study. The significance of this paper is to sort out these algorithms, as well as their advantages and disadvantages, and determine their applicability in application scenarios such as UAV navigation, localisation and target tracking, in order to enhance the performance and robustness of UAVs, reduce the impact of sensor noise and external interference, promote technological innovation, and facilitate the advancement of UAV technology.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Junhao Cai
PY  - 2025
DA  - 2025/08/31
TI  - UAV Sensing Data Optimisation: Comparison and Application of Key Filtering Algorithms
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 162
EP  - 170
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_19
DO  - 10.2991/978-94-6463-821-9_19
ID  - Cai2025
ER  -