Recent advancements in Deep Learning (DL) for Direction of Arrival (DOA) estimation have
highlighted its superiority over traditional methods, offering faster inference, enhanced super …

Automotive radar systems require high resolution in four dimensions: range, Doppler,
elevation and azimuth. The angular resolution of an automotive radar are determined by the …

In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using
frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low …

This article introduces a novel microstrip slot antenna array (SAA) configuration for radar
applications. The proposed antenna is specifically designed for operation in the K-band …

In this paper, we develop a scheme to partition a one-or multi-dimensional consecutive
integer number set into multiple identical, possibly rotated, subsets. The proposed technique …

Automotive radar emerges as a crucial sensor for autonomous vehicle perception. As more
cars are equipped radars, radar interference is an unavoidable challenge. Unlike …

Single-snapshot signal processing in sparse linear arrays has become increasingly vital,
particularly in dynamic environments like automotive radar systems, where only limited …

For time division multiplexing multiple input multiple output (TDM MIMO) millimeter wave
radar, the measurement of target range, velocity and other parameters depends on the …

In this study, we develop a holistic framework for space-time adaptive processing (STAP) in
connected and automated vehicle (CAV) radar systems. We investigate a CAV system …

Automotive radar with sparse arrays are highly desired, as a sparse array has a smaller
number of elements compared to a uniform linear array (ULA) of the same physical aperture …