Document Type
Journal Article
Publication Title
Drones
Volume
7
Issue
5
Publisher
MDPI
School
School of Science / Security Research Institute
RAS ID
60259
Funders
National Natural Science Foundation of China (Nos. U22A2002, 61972093 and 62071234) / Hainan Province Science and Technology Special Fund (ZDKJ2021022) / Scientific Research Fund Project of Hainan University under Grant KYQD(ZR)-21008
Abstract
The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. The first method could estimate the source position and angle measurement noise at the same time by seeking the center of an inscribed sphere, called the CIS. Firstly, every sensor measures two angles, the azimuth angle and the elevation angle. Based on that, two planes are constructed. Then, the estimated values of the source position and the angle noise are achieved by seeking the center and radius of the corresponding inscribed sphere. Deleting the estimation of the radius, the second algorithm, called MSD-LS, is born. It is not able to estimate angle noise but has lower computational complexity. Theoretical analysis and simulation results show that proposed methods could approach the Cramér–Rao lower bound (CRLB) and have lower complexity than the MLE.
DOI
10.3390/drones7050318
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Shi, B., Li, Y., Wu, G., Chen, R., Yan, S., & Shu, F. (2023). Low-complexity three-dimensional AOA-cross geometric center localization methods via multi-UAV network. Drones, 7(5), 318. https://doi.org/10.3390/drones7050318