SBIR-STTR Award

Acoustic sensors, such as the Ground Counter Fire Sensor (GCFS), are used by the USMC to identify the point-of-origin (POO) and point-of-impact (POI), as well as provide source identification. This effort will develop a proof-of-feasibility set of signal processing algorithms for the GCFSs Command Post (CP). These algorithms will permit a network consisting of a mixture of up to 12 fixed listening posts (LPs) and relocatable LPs (RLPs). The CP will de-conflict simultaneous events and identify POO / POI as well as the firing platform with the accuracy stated in the solicitation as an optimal goal. Hyperion will develop a robust event location estimation algorithm. A stochastic data fusion method will be developed for handling simultaneous events. Acoustic ray-tracing and wave propagation estimators, using meteorology and terrain data, will be used to achieve highly accurate calculations of event time and location and support improved event type identification. As a benefit of this work, the USMC can implement an improved sensor network, lessening the logistical burden on the Warfighter in regards to emplacement, operation and maintenance.

Benefit:
Derivative applications include the improvement of a number of acoustic processing systems. For example, on a different range scale (100s and 1000s of km) geo-location and event identification methods are utilized by the International Monitoring System (IMS) Infrasound Network which supports the Comprehensive Test Ban Treaty Organization (CTBTO). For Homeland Security, these technologies could play a key role in detecting, geo-locating (3-D) and tracking low-flying unmanned aerial vehicles trying to cross-borders or enter a restricted airspace.

Keywords:
data fusion, data fusion, Point of Origion, GCFS, Sensors, Acoustic Signal Processing, maneuverable assets, law enforcement, acoustic sensor, Meteorology, Homeland Security, Terrain, Point of Impact

This proposal addresses the development of a Command Post and Acoustic Listening Posts for performing detection and automatic geo-location and classification of transient acoustic sounds associated with the firing of weapons, especially rockets, mortars, and artillery and the corresponding munitions impacts. Key components of the system are rugged low-noise infrasound sensors, state-of-the-art acoustic propagation algorithms, and Bayesian statistical detection, estimation, and classification algorithms.

Benefit:
If successful this Phase II SBIR project will produce a GCFS system that is at TRL 7 in that the system will have been demonstrated in an operational environment at a location such as Camp Shelby, Miss. where weapon systems of interest (RPGs, mortars, heavy artillery, IEDs, tanks) will have been used. Additionally, the GCFS system will have been deployed with minimal difficulty, remained functional throughout demonstration, located acoustic events with an acceptable level of accuracy, classified the events adequately, and generated very few false alarms. Clearly, if successful, the primary post-research application of this GCFS system is a system capable of performing the mission. Additionally, the system can perform the same functions (and more) as the ARL-developed system, UTAMS. Technology ideas from the program could easily be transitioned into applications suitable for (terror) shooter detection and forensic data collection. Consider the recent Phoenix, Arizona, events, the Columbus, Ohio, and DC-area events from several years ago. Modification of the system might also be useful in detection of low-flying airborne threats, but the sources would be moving, airborne, and generators of continuous wave acoustic energy.

Keywords:
Battlefield Acoustics, geo-location, Ground Counter-Fire Sensor