Methods For Improving Army's Cannon Artillery System

Methods for improving Army’s cannon artillery system

- Maj. Jonathan Erwin

The United States Army’s field artillery community faces a myriad of challenges on the modern battlefield. Areas of operations (AOs) for Army units deployed overseas are trending toward urban, built-up areas that include population centers and large amounts of civilian infrastructure. These AOs are crowded and contain numerous targets that are interspersed amongst large populations of non-combatants. Targets in these environments are often fleeting, presenting commanders with small windows for conducting an engagement. In order to remain relevant in these AOs, cannon artillery units require precision, responsiveness, and effectiveness. Designed as an area fire weapon, a howitzer firing conventional “dumb” rounds has limited precision. In an urban setting, the responsiveness of cannon artillery platforms is constrained by deconfliction procedures and collateral damage requirements. Furthermore, cannon artillery platforms are ineffective when they require multiple adjustments to achieve effects on target.

Big data technology may provide the means to tackle some of the above-mentioned challenges. Big data technology may assist the Army’s cannon artillery units in being more precise, responsive and effective by improving the accuracy of conventional artillery munitions, accelerating the target identification process, rapidly de-conflicting airspace, and speeding up the sensor-to-shooter link. The following sections will address the advent of big data technology and the methods in which big data technology can be applied to the cannon artillery system to improve precision, responsiveness and effectiveness.

Big data