SENSOR OVERLOAD


GETTING THE BIG PICTURE


Spc. Clayton P. McInnis, a human intelligence analyst with 1st Battalion, 155th Infantry Regiment of the Mississippi Army National Guard, reviews reports in the unit’s tactical operations center in June, at the National Training Center, Fort Irwin, California. The ExPED STO is designed to improve the conversion of large amounts of raw sensor data into usable situational understanding. (Mississippi National Guard photo by Staff Sgt. Shane Hamann, 102nd Public Affairs Detachment)


Tese stovepipes hinder the ability to conduct multi-INT analysis, to hand off targets between sensors (cross-cue) or to share data with other systems. Stove- piped systems also present unscalable and unsustainable costs for the doctrine, organization, training, material, lead- ership and education, personnel and facilities aspects of maintaining the ISR enterprise.


Instead, sensor solutions need to use industry standards, be scalable—capable of handling a growing amount of work— and built on open architectures designed to support rapid integration of new capa- bilities by making it easy to add, upgrade and swap components. Tese architec- tures should adapt to the echelon in which they will operate, provide a frame- work for distributed PED and facilitate integration with other systems.


Data services, an essential architectural component, must provide data man- agement and delivery to the right user; this includes enabling access to joint, interagency, multinational, NATO, allied and national operations. Some currently fielded sensor architectures provide sensor data and status. How- ever, these architectures are not tailored for tactical environments with lim- ited communications, cannot be easily


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reconfigured during missions and are not designed to support multi-INT fusion— the process of comparing and correlating data from multiple sources and disparate types, including human inputs, collected signals, measurements and imagery, and then generating more useful observations.


Te ExPED program is investigating and developing sensor architecture prototypes that will dynamically tie together PED resources (sensors, analytics and analysts) across the tactical space. Tis will pro- vide the ability to reconfigure resources in changing conditions and make better use of constrained tactical bandwidth, thus increasing awareness and discovery of significant events.


REDUCING ANALYST WORKLOADS Te Army continues to add sensors that are capable of collecting greater volumes of data, but we can’t afford to move all of the data around our networks, and we don’t have enough analysts to look at all of it. Analytics provide process automa- tion, smart logic, computation and threat trending that expose nuggets of relevant information to the analysts.


Taskable automated and semiautomated multi-INT analytics and processing— whereby the user (or multiple users


simultaneously) can seek and detect par- ticular features for a particular mission or at a specific time, for example, a red truck or people with white shirts—are needed closer to the sensor to increase the Army’s ability to manage and exploit the breadth and scale of collected data. Distributed data processing—using mul- tiple computers across different locations to divide the processing load—can help reduce the amount of network traffic by filtering and compressing data as it moves through the network, increasing system performance in bandwidth-limited envi- ronments. Tese capabilities will create opportunities to leverage remotely stored data to glean new insights.


ExPED is investing in the development of prediction, fusion, correlation and alerting capabilities that are critical to managing the big data challenge and are necessary to reduce an analyst’s workload. ExPED is working with Army and industry stake- holders to define standards for analytic interoperability so that more sophisticated mission-specific


solutions can be built from existing analytic toolsets.


To validate these standards, the ExPED program is developing multi-INT ana- lytics to merge radar tracks, full-motion video and electronic signals to provide greater confidence in the data and lessen


Army AL&T Magazine


January-March 2018


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