Sparse arrays are known to achieve an increased number of degrees-of-freedom (DOFs) for
direction-of-arrival (DOA) estimation, where an augmented virtual uniform array calculated …

Augmented coarrays can be derived from spatially undersampled signals of sparse arrays
for underdetermined direction-of-arrival (DOA) estimation. With the extended dimension of …

Coprime arrays can achieve an increased number of degrees of freedom by deriving the
equivalent signals of a virtual array. However, most existing methods fail to utilize all …

We propose a high-resolution imaging radar system to enable high-fidelity four-dimensional
(4D) sensing for autonomous driving, ie, range, Doppler, azimuth, and elevation, through a …

Lower bounds on the mean square error (MSE) play an important role in evaluating the
direction-of-arrival (DOA) estimation performance. Among numerous bounds for DOA …

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme
noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network …

Recently, nested and coprime arrays have attracted considerable interest due to their
capability of providing increased array aperture, enhanced degrees of freedom (DOFs), and …

The signal processing community is currently witnessing the emergence of sensor array
processing and direction-of-arrival (DoA) estimation in various modern applications, such as …

Sparse linear arrays (SLAs) can be designed in a systematic way, with the ability for
underdetermined DOA estimation where a greater number of sources can be detected than …

Joint communication and radar (JCR) waveforms with fully digital baseband generation and
processing can now be realized at the millimeter-wave (mmWave) band. Prior work has …