Automated Acoustic Monitoring System

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00024-15-P-4560
Agency Tracking Number: N151-030-0038
Amount: $79,924.00
Phase: Phase I
Program: SBIR
Awards Year: 2015
Solicitation Year: 2015
Solicitation Topic Code: N151-030
Solicitation Number: 2015.1
Small Business Information
5860 Trinity Parkway, Suite 200, Centreville, VA, 20120
DUNS: 135121148
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Newell Stacey
 (703) 968-8040
Business Contact
 Meg Stout
Title: Technical Point of Contact
Phone: (202) 781-4233
Research Institution
The SMART (Sensor Monitoring Automated Reporting Technology) system for automated acoustic monitoring will provide advanced information on sensor health, significantly increasing the abilities of operators to manage sensor health while reducing the overall workload associated with sensor management. SMART automatically monitors noise sources in order to assess their effects on sensor performance. Noise sources monitored include self noise, platform noise, and environmental noise. Sensors monitored include the AN/SQS-20 (TB-37U) Multi-Function Towed Array (MFTA) and the AN/SQS-53C Hull Array. PMFL (performance monitoring fault localization) reports are simultaneously monitored and analyzed with noise sources. Based on the sources monitored and the results of the automated analysis, clear information on sensor status and performance is provided to operators, along with clear recommendations for corrective actions. Corrective actions may include recommendations for specific diagnostic procedures, processing option recommendations (such as selecting ABF or CBF), and recommendations to rely on one sensor over another. Condition based maintenance (CBM) prognosticates the future health of sonar sensors using data from those sensors and PMFL data. Data relevant to acoustic monitoring and CBM are saved into a centralized data repository for subsequent analysis to improve acoustic monitoring and CBM algorithms, thus enabling optimum system performance and maintenance.

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

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