The Army needed transformation to a network-enabled force that sees first, decides first and acts decisively, integrating information from tactical engagements into a common operational picture.

DARPA and PEO STRI conducted a series of battle experiments to ensure that future command and control systems enable battle command to conduct small unit operations with soldiers better equipped to see, decide, and fight in ways that produce decisive operational results.

ARA participated in the post-experiment analysis with a focus on the decision-making environment, using Cognitive Task Analysis techniques to support process tracing.

• Measure and understand decision-making

• Review EEA-focused analysis

A prime example of an ARA real-time analysis tool is the Data Analysis Real Time System (DARTS). DARTS provides real-time summation and trend information to analysts in a series of quad charts. The display cycles through five topic areas with four charts displayed for each topic. The five topics areas are: key event indicators, movement, attrition, fires, and detections.

ARA provides unique and sophisticated post-run products as well, ranging from ones that provide data minutes after the run to ones that operate throughout the post-experiment analytic period, producing in-depth reports and ad hoc query support. One post-experiment product, the Sensor Coverage Tool, provides a visual display of both the extent and quality of the commander’s use of intelligence sensors. The primary focus is on the use of various Unmanned Aerial Vehicles (UAV) with differing sensor packages and the resulting aggregate picture generated from the sensed data. The sensor coverage analysis accounts for the types of sensors covering the area, distance from the sensor to the target, number of times the area has been covered, and the time since the sensed information was collected (i.e. information decay).

 ARA has also devised a valuable method for analyzing aspects of situational awareness (SA).  Produced within minutes after a run, the pictures the SA Tool provides show the difference between ground truth and the commander’s effectiveness in gaining knowledge of the enemy. The SA curves calculate this by scoring the objective information contained in the commander’s graphical user interface and comparing it to ground-truth data from the simulation. These curves are presented for each echelon as well as overall BLUFOR vs. OPFOR.