DOA estimation for low angle targets using time reversal in frequency domain model

Xiaolu Zeng, Baixiao Chen, Minglei Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Multipath distortion has been a challenge problem for low angle target localization problem using very high frequency (VHF) radar. In particular, under complex terrain, part of the multipath lies in the same beamwidth of the direct path signal, which makes it difficult to be distinguished in the spatial, temporal and Doppler domains. This paper uses time reversal (TR) technique to adjust the transmitting signal waveform by exploring the channel information contained in multipath clutters. According to TR principle, this specially designed signal can refocus at the original target position, which not only mitigates the multipath distortion but also equally increases the signal-to-noise ratio (SNR) of the TR receiving signal. Next, we analyzes the independence between the noise subspace and the sampling frequency bin in our TR wideband signal model. A novel direction of arrival (DOA) estimation method is then investigated in frequency domain. Compared with conventional methods, its superiority in DOA estimation accuracy for low angle targets is validated by numerical simulations.

Original languageEnglish
Title of host publication2018 IEEE Radar Conference, RadarConf 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1323-1327
Number of pages5
ISBN (Electronic)9781538641675
DOIs
Publication statusPublished - 8 Jun 2018
Externally publishedYes
Event2018 IEEE Radar Conference, RadarConf 2018 - Oklahoma City, United States
Duration: 23 Apr 201827 Apr 2018

Publication series

Name2018 IEEE Radar Conference, RadarConf 2018

Conference

Conference2018 IEEE Radar Conference, RadarConf 2018
Country/TerritoryUnited States
CityOklahoma City
Period23/04/1827/04/18

Fingerprint

Dive into the research topics of 'DOA estimation for low angle targets using time reversal in frequency domain model'. Together they form a unique fingerprint.

Cite this