Data‐driven target localization using adaptive radar processing and convolutional neural networks

S Venkatasubramanian, S Gogineni… - IET Radar, Sonar & …, 2024 - Wiley Online Library
Leveraging the advanced functionalities of modern radio frequency (RF) modeling and
simulation tools, specifically designed for adaptive radar processing applications, this paper …

Off-grid DOA estimation with mutual coupling via block log-sum minimization and iterative gradient descent

WG Tang, H Jiang, Q Zhang - IEEE Wireless Communications …, 2021 - ieeexplore.ieee.org
Mutual coupling (MC) effect between antennas can deteriorate the direction of arrival (DOA)
estimation performance. Block sparse signal representation (BSSR) is an effective solution …

Cramér–Rao bound for sparse signals fitting the low-rank model with small number of parameters

M Shaghaghi, SA Vorobyov - IEEE Signal Processing Letters, 2015 - ieeexplore.ieee.org
In this letter, we consider signals with a low-rank covariance matrix which reside in a low-
dimensional subspace and can be written in terms of a finite (small) number of parameters …

Modal analysis using co-prime arrays

P Pakrooh, LL Scharf, A Pezeshki - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
We address the problem of estimating mode parameters from noisy observations of a linear
combination of the corresponding modes. This problem arises in line spectrum estimation …

Music for joint frequency estimation: stability with compressive measurements

W Liao - 2014 IEEE Global Conference on Signal and …, 2014 - ieeexplore.ieee.org
This paper studies the application of MUtiple Signal Classification (MUSIC) algorithm on
Multiple Measurement Vector (MMV) problem for the purpose of frequency parameter …

[HTML][HTML] Processor dependent bias of spatial spectral estimates from coprime sensor arrays

R Bautista, JR Buck - The Journal of the Acoustical Society of America, 2018 - pubs.aip.org
Coprime sensor arrays (CSAs) can estimate the directions of arrival of O (MN) narrowband
plane wave sources using only O (M+ N) sensors with the CSA product processor …

Minimax optimal online stochastic learning for sequences of convex functions under sub-gradient observation failures

H Gokcesu, SS Kozat - arxiv preprint arxiv:1904.09369, 2019 - arxiv.org
We study online convex optimization under stochastic sub-gradient observation faults,
where we introduce adaptive algorithms with minimax optimal regret guarantees. We …

Phase estimation in heavy-tailed noise for co-prime arrays

DA Abraham - OCEANS 2018 MTS/IEEE Charleston, 2018 - ieeexplore.ieee.org
A phase estimator appropriate for use in the product-processing of co-prime sub-array pairs
is described and analyzed. The estimator is a unit-circle average (UCA) of the phase …

Modal analysis using sparse and co-prime arrays

P Pakrooh, LL Scharf, A Pezeshki - arxiv preprint arxiv:1504.01258, 2015 - arxiv.org
Let a measurement consist of a linear combination of damped complex exponential modes,
plus noise. The problem is to estimate the parameters of these modes, as in line spectrum …

Hybrid analog/digital MIMO architecture in large antenna array systems

S Park - 2018 - repositories.lib.utexas.edu
Hybrid analog/digital precoding architectures can address the trade-off between achievable
spectral efficiency and power consumption in large-scale multiple-input-multiple-output …