6 papers
Approximate MLE of High-Dimensional STAP Covariance Matrices with Banded & Spiked Structure -- A Convex Relaxation Approach
Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy +3
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 bec…
CoFAR Clutter Estimation using Covariance-Free Bayesian Learning
Kunwar Pritiraj Rajput, Bhavani Shankar M. R., Kumar Vijay Mishra +2
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 pr…
Fisher Information Approach for Masking the Sensing Plan: Applications in Multifunction Radars
Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy +2
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 pur…
Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound
Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang +1
In modern radar systems, precise target localization using azimuth and velocity estimation is paramount. Traditional unbiased estimation methods have utilized gradient descent algo…
Subspace Perturbation Analysis for Data-Driven Radar Target Localization
Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang +3
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 t…
Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach
Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy +2
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 dimensiona…