4 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…
A Digital Engineering Approach to Testing Modern AI and Complex Systems
Joseph R. Guerci, Sandeep Gogineni, Robert W. Schutz +5
Modern AI (i.e., Deep Learning and its variants) is here to stay. However, its enigmatic black box nature presents a fundamental challenge to the traditional methods of test and va…
Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks
Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang +3
Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper p…
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…