Neural Network Constant False Alarm Rate Detection
Abstract
This document presents an approach to augmenting and improving cell averaging constant false alarm detectors with a neural network based approach. The simulated results show that the neural network is able to perform as well as the optimal detector and remove the losses typically associated with estimating the noise power in standard approaches. A feasible implementation of the neural network detector is also presented. Preliminary results demonstrate that the neural network requires the same inputs as the cell averaging constant false alarm rate detector and can work across a range of unknown input signal to noise ratios.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 25, 2023
- Accession Number
- AD1206723
Entities
People
- Huy V. Le
- Kevin Wagner
Organizations
- United States Naval Research Laboratory