Home / Technology / AI & IT / USAF’s Multi-Domain Command and Control (MDC2) requires Artificial Intelligence technologies for Information Analysis and Targeting

USAF’s Multi-Domain Command and Control (MDC2) requires Artificial Intelligence technologies for Information Analysis and Targeting

Advanced Integrated Air Defense Systems, Anti-satellite, and computer network attack weapons can hold capabilities in air, space and cyber at risk and create Anti-Access and Area Denial (A2AD) quandaries. The goal of Multi-Domain Operations is to ensure the ability to integrate operations in multiple domains and create complex dilemmas for potential adversaries; success is dependent on the ability to harness information and conduct advanced command and control in all domains, simultaneously. Including advanced command and control (C2) capabilities to meet evolving threats, as the Air Force continues to leverage air, space and cyberspace operations, progressing from enhanced operational effects to truly synergistic effects.


The need for Multi-Domain Command and Control (MDC2) stems from the notion that conflict in the Digital Age will be characterized as multi-domain, multi-region, multi-component, and multi-nation. These characteristics will create operational seams for our forces that must be overcome in an operationally agile way. MDC2 represents the Air Force’s concept for how to mitigate the negative effects of these seams with operational agility and high velocity decision making.


Development of MDC2 is requires optimized C2 processes, assured communications networks to enable C2 in contested environments, C2 interoperability with joint, coalition and interagency forces and advanced technology (Artificial Intelligence, Machine Learning, etc.) to enhance and accelerate C2 functions.


U.S. Air Force researchers are asking industry for new enabling technologies in fast attack planning on valuable and enemy moving targets that offer only a fleeting time window to carry out successful missions.


Dynamic Targeting

Dynamic targeting prosecutes targets of opportunity that are identified too late, or not selected for action in time to be included in deliberate targeting but, when detected or located, meet criteria specific to achieving objectives. When plans change and planned targets must be adjusted, dynamic targeting can also manage those changes.


Dynamic targeting is divided into five steps: Find. During this step, possible targets are detected and classified for further prosecution; Fix. The fix step of dynamic targeting includes actions to determine the location (fix) of the potential target; Track. During this step, the target is observed, and its activity and movement are monitored; Target. During this step the decision is made to engage the target in some manner to create desired effects and the means to do so are selected and coordinated and Engage. In this step, action is taken against the target.


The steps of dynamic targeting may be accomplished iteratively and in parallel. While the find, fix, and track steps tend to be ISR-intensive, the target and engage steps are typically labor-force, and decision-making intensive.


During execution, as armed conflict is a dynamic event, some targets will be identified as emerging targets or not selected for execution in time to be included in the normal targeting process. These targets must be prosecuted on a compressed timeline than those that are prosecuted using deliberate targeting. Consequently, automating and expediting the flow of information, from nomination, through development and execution, and then back to the targeteers, becomes even more critical in these instances.


Automating weaponeering solutions for Dynamic targetting

Weaponeering may be defined as the process of determining the quantity of a particular type of weapon required to achieve a specific level of target damage by considering the effects of target vulnerability, warhead damage mechanism, delivery errors, damage criterion and weapon reliability. Effective use of Weaponeering methodologies will produce the most efficient way to inflict the prescribed amount of damage to the intended target thereby reducing exposure of war fighters to enemy threats and minimizing collateral damage to non-combatant personnel and infrastructure (www.weaponeering.com).

The objective in weaponeering knowledge, is to understand the difficulties Air Force Targeteers encounter when dealing with little to no data, and still needing to compute a probability of effect for a given target. There is a plethora of information regarding target vulnerability and damage mechanisms in the kinetic effects domain mostly hosted in the Joint Munitions Effectiveness Manual, JMEM Weaponeering System (JWS).


The idea is to significantly reduce the dynamic targeting process by automating weaponeering solutions.  Possible Machine Learning applications could be used to “teach” a machine to quickly determine a weaponeering solution and provide rapid options to targeteers dealing in the real time realm. In this realm there is not time to fully compute a weaponeering solution.  That is left for the deliberate targeting process. The objective is to develop such capability to ingest into an optimization algorithm that will present decision makers with options.


Airforce BAA

The Air Force Research Laboratory – Information Directorate (AFRL/RI) is soliciting white papers under this BAA in the area of multi-domain operations, information, and dynamic targeting solutions for targeting recommendations through optimization algorithms, sensitivity analysis, and analysis of alternatives.


The BAA objective is to conceive, develop and demonstrate innovative and affordable technologies that provide accurate and timely planning and execution against full-spectrum dynamic, time-sensitive or pre-planned targets.


The intent is to provide research, development, integration, test and evaluation of technologies/techniques for the Air Operations Center (AOC) and Combatant Command targeting needs.


With dynamic targeting occurring in a compressed timeline on targets outside of the Air Tasking Order (ATO), this fast-paced activity allows for little time to conduct analysis on the target or assign the optimal asset to use for targeting.  Conduct research to develop and demonstrate innovative and affordable technologies that provide a more lethal, disruptive, and resilient Air Force (AF) targeting production capability through the application of algorithmic warfare, artificial intelligence, and automation.


Technical Areas

This announcement is divided into four (4) technical areas (TAs)

Technical Area 1. Optimization of Targeting process

The goal of Multi-objective Optimization is to analyze the targeting process, identify processes which can be improved via optimization, and develop a multi-objective framework for performing optimization across these processes.


These processes will include, but are not limited to, identifying available resources, performing weaponeering, selecting ideal available weapon effects, and selecting most appropriate platform for effect delivery. The result of the optimization is to be a ranked list of suggested courses of action.


Optimization will be performed with the goal of reducing mission planning time, decreasing overall mission cost, and increasing mission success rates, with reduced human overhead. These objectives are to be weighted to reflect commander’s intent, though other objectives may also be used to supplement.


Targeting sub-processes may be modeled as analogues to classical Mixed-Integer Linear Programing (MILP) problems, or through the creation of custom objective functions and tailored solvers. In either case, clear mathematical representations for each objective must be provided, with detailed reasoning behind formulation decisions. This will support future alterations and additions as targeting evolves.


The optimization framework must be capable of ingesting the diverse data formats that are critical to the targeting process. It should also estimate the time required to solve each objective function for each problem, as this will identify bottlenecks and determine infeasible solutions as the window of opportunity decreases. While the initial effort should focus on applying kinetic effects, the framework must be constructed with the intent of domain-agnosticism, to support future development into non-kinetic effects.


Technical Area 2. Modeling and Simulation of Multi-Domain Command and Control (MDC2) operations

The purpose of Technical Area 2 is to create models that simulate Multi-Domain Command and Control (MDC2) operations, and utilizing dynamic targeting scenarios. These scenarios should have the ability to add or inject MDC2 technologies to determine how new technologies can shape the battlespace. The model design may create scenarios that create quandaries to force application due to insufficient battle space awareness due to the “fog-of-war”. Comprehensive battlespace awareness provides the basis for planning and execution efforts. It provides predictive and actionable intelligence, ISR operations, and targeting in a manner that supports air tasking, execution, and assessment. From a multi-domain perspective, the development of comprehensive battlespace awareness is challenged by the need to integrate information from multiple sources of varying quality across command chains, over multiple networks and classification levels to understand the nature of developing events and their consequences from a geographic or global perspective.


The MDC2 objective for battlespace awareness activities, ostensibly, is to develop and maintain a shared understanding of the operational environment that spans geographic, functional, domain, classification, and organizational boundaries. The scope of such awareness includes information on friendly forces, ongoing operations, adversary forces, indications and warnings, possible targets, as well as military, political, environmental, and other events.


It entails understanding not only what events are taking place throughout the battlespace irrespective of domain, but also establishing how they may impact each other, cross geographic areas of responsibility, affect campaign plans, and hamper (or even enhance) the commander’s ability to project force and create effects.

Modeling and Simulation may be mathematical, physical or computer based and may include, but are not limited to:

  1. Real-time visualization and playback (i.e. VESPA)
  2. User-interrupted simulation design (i.e. WARLOCK)
  1. Discrete or continuous event simulations
  2. Linear or non-linear programming
  3. Wargaming


Technical Area 3. Workflow Analysis of Dynamic targeting

The purpose of Workflow Analysis is to elicit established dynamic targeting workflows. The idea is to use workflow methodologies to understand work processes and output, grounded in a social and technical framework. It should take into account the overall functionality and purpose of the entire organization (with boundary conditions set as appropriate) as well as the specific goals of the teams associated with key processes of interest.  Minimally consider the work domain, tasks, strategies as well as the social/cultural aspects of the organization as well as the required skillsets of those involved in the work processes.


Technical Area 4. Virtual and Augmented Reality

Virtual Reality (VR) is a technology that takes place within a simulated environment which uses computational data to immerse the user within a realistic construct. This gives the illusion of your presence in an environment similar to the real world. VR technology is used across all branches of the military, within the Intelligence Community and within the Department of Homeland Security for flight and battlefield simulation.


Augmented Reality (AR) takes VR and overlays other information from various sources and creates a multi-dimensional “info-sphere” where the user can better determine the effects of various factors upon their current/future position. This fused view can enhance mission effectiveness and enable better decisions.


The purpose of Virtual and Augmented reality is to create a representation of a Region of Interest (ROI) with information pulled from multiple sources, in real-time, or near real-time, to build an immersive environment of a single location, which enables ease of interaction, for an analyst or a team of analysts, in different locations.


Additionally, create a user friendly info-sphere with the capability to display a multitude of information to foster potential multi-domain data fusion. This capability includes the real-time/near real-time ability to dynamically regenerate a new ROI or incorporate changes in an existing ROI. The system will also be capable of point mensuration; a process that will allow for measurement of a feature or location on the earth to determine an absolute latitude, longitude, and elevation.  It should also allow for the introduction of photogrammetry which models geometric information about a target to support precise evaluation of physical effects.


The vision is to make the VR Info-sphere’s COP viable, and as new data is captured and technologies advance, they will become auto-integrated into dynamic display for targeteers.  This 3D model of the ROI would be exportable/shareable between future ground forces Augmented Reality (AR) headsets/display units (e.g. mission adaptive ballistic goggles/helmets, etc).



About Rajesh Uppal

Check Also

From Jeopardy Champion to AI Powerhouse: Evolution of IBM Watson 1.0 to WatsonX

Introduction: In the rapidly evolving landscape of artificial intelligence and cognitive computing, IBM Watson has …

error: Content is protected !!