When the elevation of target is smaller than a beamwidth, the complex multipath signals will
distort the feature of direct signal reflected from target. The elevation of target can hardly be …

When the elevation of targets is smaller than beamwidth, the coherent multi-path signals will
significantly degrade the direction of arrival (DOA) estimation accuracy of existing methods …

In low-altitude target situation, the multi-path signals cause the amplitude-phase distortion of
direct signal from targets and degrade the performance of existing methods. Hence, in this …

It is a serious problem that the performance loss is suffered by traditional Direction-of-Arrival
(DOA) estimation methods in non-ideal environment, such as mutual coupling of array …

Recently, deep unfolded networks have been widely utilized in direction of arrival (DOA)
estimation due to the reduced computational complexity and improved estimation accuracy …

Direction-of-arrival (DOA) estimation is a vital research topic in array signal processing, with
extensive applications in many fields. In recent years, deep learning has been applied to …

A novel direction of arrival (DOA) estimation method is proposed for very high‐frequency
(VHF) radar by the deep neural network (DNN) under strong multipath effect and complex …

In this letter, we propose two angle separation learning schemes (ASLs) to address the
coherent DOA estimation problem. We first show that the columns of the array covariance …

To achieve fast and accurate two-dimensional (2D) direction of arrival (DOA) estimation, a
novel deep ensemble learning method is presented in this paper. First, a convolutional …

A new high-resolution direction of arrival (DOA) estimation technique using a neural fuzzy
network based on phase difference (PD) is proposed. The conventional DOA estimation …