You are here

Ultra Wideband Receiver (UWR) – Sample Clock Modulation

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8571-19-P-A030
Agency Tracking Number: F18C-003-0045
Amount: $150,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF18C-T003
Solicitation Number: 18.C
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-04-15
Award End Date (Contract End Date): 2020-04-15
Small Business Information
Oceanit Center 828 Fort Street Mall, Suite 600
Honolulu, HI 96813
United States
DUNS: 144540283
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Matthew Williams
 Senior Scientist
 (808) 531-3017
Business Contact
 James Andrews
Phone: (808) 531-3017
Research Institution
 Professor Ethan Yuanxun Wang Professor Ethan Yuanxun Wang
10889 Wilshire Blvd, Suite 700 Box 951406
Los Angeles, CA 90095
United States

 (310) 206-5670
 Nonprofit College or University

Modern electronic warfare (EW) employs agile, dynamic, convert waveforms. It has become challenging for legacy electronic intelligence (ELINT) receivers to intercept such waveforms. To cover a wide frequency band, many frequencies must be scanned rapidly. Therefore, the probability of intercepting by the super heterodyne receiver is limited by the intermediate frequency (IF) bandwidth and tuning speed. The Ultra Wideband Receiver (UWR) enables the reception of a wide spectrum without the need of frequency scanning. Persistently monitoring wide spectrums allows rapid detection of multiple signals across different bands. The most brute-force approach to achieve such receiver is to use a high-speed analog-to-digital converter (ADC) with a broadband antenna and frontend. Even with the state-of-the-art ADC, it is not possible to cover the entire band of interest while satisfying Nyquist rate. Oceanit shall develop an UWR based on sample clock modulation, consisting of two subsystems: a non-uniform sampling module, using clock modulation to extract non-uniform samples from a time domain signal; and a frequency identification system based on compressive sensing (CS) and random sample consensus (RANSAC)module, identifying carrier frequency. By first creating (via RANSAC) and exploiting (via CS) sparsity in the frequency domain, we make accurate predictions despite relative lack of data.

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government