Sparse Aperture Multistatic Radar Imaging Techniques
Abstract
We give a summary of FY20 research activity for the NRL 6.1 Base Program project Sparse Aperture Multistatic Radar Imaging Techniques. This project focuses on the development of techniques for multistatic radar imaging from a spatially sparse set of sensors. The algorithmic framework for the project is the Linear Sampling Method (LSM), which allows for multistatic imaging without the use of simplified scattering assumptions common to radar signal processing that may not be valid in many sensing scenarios. The work completed in FY20 comprises three main topics. The first is an extension of an LSM formulation we generated in FY19 which stabilizes the sparse-aperture LSM solution by incorporating a priori phase-delay information. The second is a new LSM formulation that achieves better sparse-aperture performance by taking into account the targets electric field boundary conditions. The third is a new technique for classifying targets according to their electrical properties by applying machine learning to the phase of the LSM solution.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 29, 2021
- Accession Number
- AD1154435
Entities
People
- Hatim F. Alqadah
- Matthew J. Burfeindt
Organizations
- United States Naval Research Laboratory