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.


    Access

    Download


    Export, share and cite



    Title :

    Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV Network


    Contributors:
    Baihua Shi (author) / Yifan Li (author) / Guilu Wu (author) / Riqing Chen (author) / Shihao Yan (author) / Feng Shu (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Three‐Dimensional Localization

    Castrejon‐Lozano, Juan Gerardo / Dzul, Alejandro | Wiley | 2013


    Methods and Systems for Three Dimensional Object Detection and Localization

    CHEN XU / ZHAO HANG / YU RUICHI | European Patent Office | 2023

    Free access

    Methods for Localization Using Geotagged Photographs and Three-Dimensional Visualization

    TROY JAMES J / KARAKUSEVIC VLADIMIR / ESPOSITO CHRISTOPHER D | European Patent Office | 2017

    Free access

    Methods and systems for three dimensional object detection and localization

    CHEN XU / ZHAO HANG / YU RUICHI | European Patent Office | 2023

    Free access

    Methods and Systems for Three Dimensional Object Detection and Localization

    CHEN XU / ZHAO HANG / YU RUICHI | European Patent Office | 2023

    Free access