.png){kind=icon}
Return
Detecting targets' longitudinal and angular accelerations based on vortex electromagnetic waves
.png){kind=icon}
PRE
AI
DOI：10.1016/j.measurement.2021.110278.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, the detections of targets' longitudinal and angular accelerations, including uniform and variable accelerations, have been investigated, based on vortex electromagnetic (EM) waves carrying orbital angular momentum (OAM), in which the time-frequency analysis approaches are used to process the echo signal. Compared with other methods, the Choi-Williams distribution (CWD) is more suitable for detecting, which has better energy concentration and less cross term. Meanwhile, the multi-OAM modes method has been proposed to decouple the longitudinal and angular accelerations and detect the concrete acceleration coefficients. And the detection errors have been analyzed by transmitting the OAM waves with different mode combinations of l= 1, 3, 5 at 3 GHz. The results indicate that increasing mode intervals and decreasing topological charges can relatively improve detection accuracy in an appropriate sampling frequency range. In addition, the proposed method is also applicable to the case that the transmission modes are impure in practical application. And the directions of the longitudinal and angular accelerations can be acquired by sending OAM with different amounts of power. This work paves the way of detecting 3-dimensional velocity of complex target.
Keywords:
Vortex EM waves
Rotational Doppler effect
Acceleration detection
Time-frequency analysis
Journal
IF:
5.6
Papers:
2.1W
Citations:
5.4W
Organization
Cited Papers
ShareSave
ShareSaveMutagenesis byN-methyl-N-nitroso-N-nitroguanidine in synchronized cultures ofMycobacterium phlei
PREAI
ShareSaveShareSaveShareSaveMeasurement of the rotational Doppler frequency shift of a spinning object using a radio frequency orbital angular momentum beam.png)
OPTICS LETTERS
OPTICS LETTERSIF3.3
PREAI
ShareSave
View more