SBIR-STTR Award

This proposal describes the development of an analog-to-information (A2I) system capable of detecting and classifying non-periodic radio frequency (RF) signals such as noise radars, ultra wide band (UWB) radars, and low probability of detection/intercept (LPD/LPI) waveforms. The proposed system leverages advanced algorithms for non-periodic signal classification that were originally developed for marine mammal classification, and improves performance through the use of deep neural networks (DNNs). Phase-I is structured into three sub-phases: the Baseline Phase, the Mark-1 Phase, and the Mark-2 Phase . Preliminary results obtained by applying a developmental algorithm to a real-world data set containing non-periodic signals suggests that the proposed approach is capable of achieving state-of-the-art performance as measured by validation accuracy.

Benefit:
A real-time system capable of consistently and accurately detecting and classifying non-periodic signals-of-interest has immediate applications in signals intelligence (SIGINT), electronic intelligence (ELINT), radar warning receivers (RWRs), missile warning receivers, and a number of other defense technologies. Such a system would also have immediate application to a number of biological and environmental monitoring problems like marine mammal population impact studies and seismic monitoring.

Keywords:
ELINT, ELINT, Wavelets, SIGINT, deep neural networks, low probability of intercept (LPI), analog-to-information (A2I)

The objective of this Phase II effort is to develop and demonstrate wavelet-based digital communication signals for low probability of detection (LPD) applications. Novel wavelet-based signaling schemes will be compared to conventional digital communication waveforms in terms of bit error rate (BER) and probability of detection (Pd) as a function of signal-to-noise ratio (SNR) for fixed system parameters (e.g., bandwidth). The communication performance (BER) and LPD performance (Pd) will be predicted theoretically, and the theoretical predictions will be verified via Monte Carlo simulations. High-fidelity signal-level simulations of the physical layer of the corresponding digital communication systems will be performed for scenarios involving air-to-ground communication in maritime environments. The signal-level modeling & simulation (M&S) results will be used to develop digital transmitter and digital receiver software for use in real-world tests. Air-to-ground testing will involve a software-defined transmitter carried by a commercial aircraft equipped with an antenna pointing system capable of continuously pointing the transmit antenna at the ground-based receiver during flight. The ground-based software-defined receiver will be equipped with an Automatic Dependent Surveillance - Broadcast (ADS-B) tracking system capable of pointing the receive antenna at the aircraft during flight. Novel wavelet-based waveforms and conventional waveforms will be transmitted and received over a variety of conditions. The communication and LPD performance of all waveforms will be evaluated in post processing and compared to demonstrate the benefits of wavelet-based communication signals.