3 papers
eess.SP2026
Von Mises Based Uncertainty Quantification for Closely Spaced Automotive Radar Targets
Vinay Kulkarni, V. V. Reddy
This work investigates uncertainty-aware deep learning approaches for direction of arrival (DOA) estimation in automotive radar, focusing on probabilistic modeling and downstream i…
eess.SP2025
Gamma-Based Statistical Modeling for Extended Target Detection in mmWave Automotive Radar
Vinay Kulkarni, V. V. Reddy
Millimeter-wave (mmWave) radar systems, owing to their large bandwidth, provide fine range resolution that enables the observation of multiple scatterers originating from a single…
eess.SP2025
KAN-powered large-target detection for automotive radar
Vinay Kulkarni, V. V. Reddy, Neha Maheshwari
This paper presents a novel radar signal detection pipeline focused on detecting large targets such as cars and SUVs. Traditional methods, such as Ordered-Statistic Constant False…