Performance evaluation of measurement based GPS denied 3D drone localization and tracking

Meles, Mehari; Rajasekaran, Akash; Mela, Lauri; Ghazalian, Reza; Ruttik, Kalle; Jäntti, Riku

doi:10.1109/wcnc55385.2023.10118816

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article1

Other1

Relationship

Self Cite1

Independent1

Authors

Journals

Cited by 2 publications

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

RIS-Assisted Three-Dimensional Drone Localization and Tracking Under Hardware Impairments

Meles,

Rajasekaran,

Mela

et al. 2024

IEEE Access

View full text Add to dashboard Cite

RIS-Assisted Three-Dimensional Drone Localization and Tracking Under Hardware Impairments

Meles,

Rajasekaran,

Mela

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Impact of carrier frequency offset and phase noise on the steering vector for 3D drone localization based on angle of arrival (AOA)

Meles,

Rajasekaran,

Mela

et al. 2023

2023 16th International Conference on Signal Processing and Communication System (ICSPCS)

Self Cite

View full text Add to dashboard Cite

Recently, the issue of localizing GPS-denied drones has become a challenge that has attracted attention of researchers. This simulation study focuses on the impact of phase noise (PN) and Carrier Frequency Offset (CFO) on the steering vector of three-dimensional Angle of Arrival (AOA)-based drone localization. The simulation involves a drone that continuously transmits signals, which are then received by multiple base station (BS) receivers equipped with 4 × 4 Uniform Rectangular Array (URA) arranged in a hexagonal cell structure. The base stations possess known locations, and the Inter-site Distance (ISD) between adjacent base stations remains identical. Each base station (BS) receiver receives the signals with different phase noise (PN) and carrier frequency offset (CFO). In this simulation study, we apply Multiple Signal Classification (MUSIC) algorithm to estimate the direction of the drone at each base station receivers. Subsequently, we employ the least squares (LS) method to approximate an unknown point that maintains the minimum distance from the 3D lines connecting the base stations to the drone, after the 3D-AOA estimation. In order to track the movement of the drone, we apply the Extended Kalman filter (EKF). To validate our proposed approach, we conduct numerical and simulation analyses.

show abstract

Performance evaluation of measurement based GPS denied 3D drone localization and tracking

Cited by 2 publications

References 9 publications

RIS-Assisted Three-Dimensional Drone Localization and Tracking Under Hardware Impairments

RIS-Assisted Three-Dimensional Drone Localization and Tracking Under Hardware Impairments

Impact of carrier frequency offset and phase noise on the steering vector for 3D drone localization based on angle of arrival (AOA)

Contact Info

Product

Resources

About