Muralidhar Rangaswamy
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View article: Approximate MLE of High-Dimensional STAP Covariance Matrices with Banded & Spiked Structure -- A Convex Relaxation Approach
Approximate MLE of High-Dimensional STAP Covariance Matrices with Banded & Spiked Structure -- A Convex Relaxation Approach Open
Estimating the clutter-plus-noise covariance matrix in high-dimensional STAP is challenging in the presence of Internal Clutter Motion (ICM) and a high noise floor. The problem becomes more difficult in low-sample regimes, where the Sample…
View article: CoFAR Clutter Estimation Using Covariance-Free Bayesian Learning
CoFAR Clutter Estimation Using Covariance-Free Bayesian Learning Open
peer reviewed
View article: CoFAR Clutter Estimation using Covariance-Free Bayesian Learning
CoFAR Clutter Estimation using Covariance-Free Bayesian Learning Open
A cognitive fully adaptive radar (CoFAR) adapts its behavior on its own within a short period of time in response to changes in the target environment. For the CoFAR to function properly, it is critical to understand its operating environm…
View article: Data‐driven target localization using adaptive radar processing and convolutional neural networks
Data‐driven target localization using adaptive radar processing and convolutional neural networks Open
Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper presents a data‐driven approach to improve accuracy in radar…
View article: RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications
RASPNet: A Benchmark Dataset for Radar Adaptive Signal Processing Applications Open
We present a large-scale dataset called RASPNet for radar adaptive signal processing (RASP) applications to support the development of data-driven models within the adaptive radar community. RASPNet exceeds 16 TB in size and comprises 100 …
View article: Fisher Information Approach for Masking the Sensing Plan: Applications in Multifunction Radars
Fisher Information Approach for Masking the Sensing Plan: Applications in Multifunction Radars Open
How to design a Markov Decision Process (MDP) based radar controller that makes small sacrifices in performance to mask its sensing plan from an adversary? The radar controller purposefully minimizes the Fisher information of its emissions…
View article: Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound
Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound Open
In modern radar systems, precise target localization using azimuth and velocity estimation is paramount. Traditional unbiased estimation methods have utilized gradient descent algorithms to reach the theoretical limits of the Cramer Rao Bo…
View article: Corrections to “Semiparametric CRB and Slepian-Bangs Formulas for Complex Elliptically Symmetric Distributions”
Corrections to “Semiparametric CRB and Slepian-Bangs Formulas for Complex Elliptically Symmetric Distributions” Open
Errors in [1] are corrected below. 1. In Eq. (17), $\mathrm{vecs}(\boldsymbol{\Sigma}_{0})$ should be $\mathrm{vec}(\boldsymbol{\Sigma}_{0})$. Specifically, the correct version of Eq. (17) is: \begin{align*} \mathbf{s}_{\boldsymbol{\phi}_{…
View article: Subspace Perturbation Analysis for Data-Driven Radar Target Localization
Subspace Perturbation Analysis for Data-Driven Radar Target Localization Open
Recent works exploring data-driven approaches to classical problems in adaptive radar have demonstrated promising results pertaining to the task of radar target localization. Via the use of space-time adaptive processing (STAP) techniques …
View article: Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach
Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach Open
In this paper, we exploit the spiked covariance structure of the clutter plus noise covariance matrix for radar signal processing. Using state-of-the-art techniques high dimensional statistics, we propose a nonlinear shrinkage-based rotati…
View article: Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks
Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks Open
Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper presents a data-driven approach to improve accuracy in radar…
View article: Toward Data-Driven STAP Radar
Toward Data-Driven STAP Radar Open
Using an amalgamation of techniques from classical radar, computer vision,\nand deep learning, we characterize our ongoing data-driven approach to\nspace-time adaptive processing (STAP) radar. We generate a rich example dataset\nof receive…
View article: High Fidelity RF Clutter Modeling and Simulation
High Fidelity RF Clutter Modeling and Simulation Open
In this paper, we present a tutorial overview of state-of-the-art radio frequency (RF) clutter modeling and simulation (M&S) techniques. Traditional statistical approximation based methods will be reviewed followed by more accurate physics…
View article: Toward Data-Driven STAP Radar
Toward Data-Driven STAP Radar Open
Using an amalgamation of techniques from classical radar, computer vision, and deep learning, we characterize our ongoing data-driven approach to space-time adaptive processing (STAP) radar. We generate a rich example dataset of received r…
View article: Adaptive channel estimation for cognitive fully adaptive radar
Adaptive channel estimation for cognitive fully adaptive radar Open
The paper addresses channel state information estimation for a cognitive radar system. The underlying radar signal model considered in this paper is based on a stochastic Green's function approach. In the radar model, the clutter returns c…
View article: Multi‐task tracking and classification with an adaptive radar
Multi‐task tracking and classification with an adaptive radar Open
This study investigates the use of adaptive radar waveforms in performing a multi‐task operation involving the tracking and classification of a single target. The work applies a previously reported hierarchical fully adaptive radar framewo…
View article: Foreword to the Special Section on Meta-Level and Adversarial Tracking
Foreword to the Special Section on Meta-Level and Adversarial Tracking Open
The nine papers in this special section focus on meta-level and adversarial tracking. A plethora of well-established tracking algorithms aim to estimate, over time, the latent kinematic state (e.g., position, velocity, higher order kinemat…
View article: Adversarial Radar Inference: Inverse Tracking, Identifying Cognition and Designing Smart Interference
Adversarial Radar Inference: Inverse Tracking, Identifying Cognition and Designing Smart Interference Open
This paper considers three inter-related adversarial inference problems involving cognitive radars. We first discuss inverse tracking of the radar to estimate the adversary's estimate of us based on the radar's actions and calibrate the ra…
View article: An Information Elasticity Framework for the Adaptive Matched Filter
An Information Elasticity Framework for the Adaptive Matched Filter Open
The adaptive matched filter (AMF) uses a number of training samples observed by the radar to estimate the unknown disturbance covariance matrix of a cell under test. In general, as the number of homogeneous training samples increases, the …
View article: How to Calibrate Your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems
How to Calibrate Your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems Open
We consider an adversarial Bayesian signal processing problem involving "us"\nand an "adversary". The adversary observes our state in noise; updates its\nposterior distribution of the state and then chooses an action based on this\nposteri…
View article: Semiparametric CRB and Slepian-Bangs Formulas for Complex Elliptically Symmetric Distributions
Semiparametric CRB and Slepian-Bangs Formulas for Complex Elliptically Symmetric Distributions Open
The main aim of this paper is to extend the semiparametric inference\nmethodology, recently investigated for Real Elliptically Symmetric (RES)\ndistributions, to Complex Elliptically Symmetric (CES) distributions. The\ngeneralization to th…
View article: Transmit MIMO Radar Beampattern Design via Optimization on the Complex Circle Manifold
Transmit MIMO Radar Beampattern Design via Optimization on the Complex Circle Manifold Open
The ability of Multiple-Input Multiple-Output (MIMO) radar systems to adapt\nwaveforms across antennas allows flexibility in the transmit beampattern\ndesign. In cognitive radar, a popular cost function is to minimize the\ndeviation agains…
View article: Fusion of Deep Neural Networks for Activity Recognition: A Regular Vine Copula Based Approach
Fusion of Deep Neural Networks for Activity Recognition: A Regular Vine Copula Based Approach Open
In this paper, we propose regular vine copula based fusion of multiple deep neural network classifiers for the problem of multi-sensor based human activity recognition. We take the cross-modal dependence into account by employing regular v…
View article: Spatio-Spectral Radar Beampattern Design for Co-existence with Wireless Communication Systems
Spatio-Spectral Radar Beampattern Design for Co-existence with Wireless Communication Systems Open
We address the problem of designing a transmit beampattern for multiple-input multiple-output (MIMO) radar considering co-existence with wireless communication systems. The designed beampattern is able to manage the transmit energy in spat…
View article: Semiparametric Inference and Lower Bounds for Real Elliptically Symmetric Distributions
Semiparametric Inference and Lower Bounds for Real Elliptically Symmetric Distributions Open
This paper has a twofold goal. The first aim is to provide a deeper\nunderstanding of the family of the Real Elliptically Symmetric (RES)\ndistributions by investigating their intrinsic semiparametric nature. The\nsecond aim is to derive a…
View article: Hierarchical fully adaptive radar
Hierarchical fully adaptive radar Open
By emulating the cognitive perception–action cycle believed to be at the core of animal cognition, cognitive radars promise to improve radar performance over standard systems. The fully adaptive radar (FAR) framework provides a generalised…
View article: Cost function design for the fully adaptive radar framework
Cost function design for the fully adaptive radar framework Open
By emulating the neuropsychological processes underpinning animal cognition, the field of cognitive radar seeks to improve performance compared to non‐adaptive systems. The fully adaptive radar (FAR) framework is an application agnostic me…
View article: A Fresh Look at the Semiparametric Cramér-Rao Bound
A Fresh Look at the Semiparametric Cramér-Rao Bound Open
This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at the Semiparametric Cramér-Rao Bound (SCRB). Semiparametric models are characterized by a finite-dimensional parameter vector of interest a…
View article: Flawed Waveform Design of Augusto Aubry, Antonio DeMaio et al
Flawed Waveform Design of Augusto Aubry, Antonio DeMaio et al Open
arXiv admin note: This submission has been withdrawn by arXiv administrators due to unprofessional personal attack.