Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM Radars

MIMO-OFDM is a key physical-layer architecture for current and next-generation wireless communication. This paper proposes a receive beamforming design scheme for MIMO-OFDM radars configured with partially-connected hybrid linear arrays, in an attempt to improve target parameter (i.e., angle, range, and velocity) estimation. Unlike existing joint estimation methods, our approach first adopts a subspace algorithm to acquire the angle information at the analog beamformer output. Then, maximum signal-to-interference ratio (MSINR) digital beamforming is conducted for target signal alignment to achieve (i) accurate range-velocity estimation thanks to suppressed interference, and (ii) automatic pairing of the identified parameter triple. Moreover, the received signal structure at the analog beamformer output is exploited for obtaining side information of the target range, which can be used to accelerate the search of range and velocity. Simulation results are used to illustrate the effectiveness of the proposed scheme.

Authors

Institutions

Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174850
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM Radars

Jwo-Yuh Wu, Tsang-Yi Wang, Wei-Cheng Kao, Shang-Ho Tsai
Radar Systems and Signal Processing
article

Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM Radars

Jwo-Yuh Wu, Tsang-Yi Wang, Wei-Cheng Kao, Shang-Ho Tsai
article en

Abstract

MIMO-OFDM is a key physical-layer architecture for current and next-generation wireless communication. This paper proposes a receive beamforming design scheme for MIMO-OFDM radars configured with partially-connected hybrid linear arrays, in an attempt to improve target parameter (i.e., angle, range, and velocity) estimation. Unlike existing joint estimation methods, our approach first adopts a subspace algorithm to acquire the angle information at the analog beamformer output. Then, maximum signal-to-interference ratio (MSINR) digital beamforming is conducted for target signal alignment to achieve (i) accurate range-velocity estimation thanks to suppressed interference, and (ii) automatic pairing of the identified parameter triple. Moreover, the received signal structure at the analog beamformer output is exploited for obtaining side information of the target range, which can be used to accelerate the search of range and velocity. Simulation results are used to illustrate the effectiveness of the proposed scheme.

National Sun Yat-sen University (TW), National Yang Ming Chiao Tung University (TW)
Openalex Percentile: Top 65%
Radar Systems and Signal Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Receive MVDR Beamforming Improves Range-Velocity Estimation for Hybrid-Array MIMO-OFDM Radars — Jwo-Yuh Wu, Tsang-Yi Wang, et al. · (2025) | TGRS Research Map | TGRS