On Learning Spatial Structure from Pre-Beamforming Per-Antenna Range-Doppler Radar Measurements

arXiv:2604.01921 · cs.CV, cs.LG, cs.RO · Submitted 2026-04-02 · Read on arXiv

cs.CV, cs.LG, cs.RO

Submitted: 2026-04-02

Updated: 2026-10-01

Comments: Accepted for publication in IEEE Robotics and Automation Letters (RA-L), 2026

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Aperture — 13× in this paper · explained in 1 episode
Ablation — 9× in this paper · explained in 1 episode
Point Clouds — 6× in this paper · explained in 2 episodes
Hallucination — 5× in this paper · explained in 3 episodes
Transformer — 4× in this paper · explained in 2 episodes
Benchmark — 2× in this paper · explained in 2 episodes
Ablation Studies — 1× in this paper · explained in 1 episode
Accuracy — 1× in this paper · explained in 1 episode
AdamW Optimizer — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Computer Vision and Pattern Recognition — 1× in this paper
Consistency — 1× in this paper · explained in 3 episodes
Data Fusion — 1× in this paper · explained in 3 episodes
Distillation — 1× in this paper · explained in 2 episodes
F1 Score — 1× in this paper · explained in 3 episodes
IEEE Intelligent Vehicles Symposium — 1× in this paper
Point Cloud Data — 1× in this paper · explained in 2 episodes
Regularization — 1× in this paper · explained in 3 episodes
Sparsity — 1× in this paper · explained in 4 episodes
Transformer Models — 1× in this paper · explained in 2 episodes
alpha — 1× in this paper · explained in 1 episode

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