4 papers
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…
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…
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…
Adaptive Beam Broadening for DoA Estimation in Dynamic and Resource-Constrained DFRC Systems
D. R. Raghavendra, V. V. Reddy, A. Mishra
Dual-function radar communication (DFRC) systems incorporate both radar and communication functions by sharing spectrum, hardware and radio frequency (RF) chains. In this work, we…