The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech

Counter-Directed Energy Weapons

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Executive Summary

As warfare technologies continue to progress, the U.S. Military will soon face a new class of advanced weapons. Directed energy weapons (DEWs) will pose a significant threat to U.S. assets in the relatively near future and therefore demand attention from planners, researchers and the defense acquisition community. A DEW is a system that uses non-kinetic energy as a means to damage or destroy enemy equipment, facilities, and personnel. This class of weapons includes both lasers and radio frequency devices. Although the U.S. Military may not choose to field DEWs, a complete understanding of the capabilities of these weapons is required to defend against them. This study aims to develop a methodology to quantify Directed Energy (DE) threats and suggest the most effective counters or countermeasures for a wartime environment in the arenas of air, land, and sea. The DEW capabilities that were considered are based on a 2020-2025 timeframe, at which point their use is expected to become proliferated. Counters and countermeasures identified during the study included operational actions and technological advances such as evasive maneuvers, metamaterials, and faraday cages. They were then evaluated utilizing detailed models of DE scenarios. Based on modeled results, a parametric environment was developed utilizing advanced design methods to assess combinations of counters and countermeasures in a user-defined scenario. The individual and/or combinations of counters and countermeasures were ranked based on their effectiveness at mitigating laser or radio frequency weapon effects. The resulting environment is able to assist decision makers by suggesting technologies, tactics, and procedures to be used in a DE wartime environment. Based on these parametric trades, conclusions were drawn as to the counter and countermeasure technologies the U.S. Military should pursue in preparation for future directed energy warfare.

Team Members

Beth Clement
Program Manager

Rebecca Douglas
Advisor

Matt Zwack
Chief Engineer

Dr. Santiago Balestrini-Robinson
Advisor

James Board
Laser Modeling

Robert Kempf
Radio Frequency Modeling

Huy Tran
Laser Capabilities

Nick Vass
Counters and Countermeasures

Background

For years, Hollywood has depicted laser warfare and electronic weapons in popular movies such as the Star Wars and James Bond franchises. However, these directed energy weapons are not as fictitious as we think. In fact, there is a growing threat of advanced warfare technologies, and an increasing need to defend against this new class of weapons. Whether or not the U.S. will use directed energy weapons, it must be prepared to face them in battle. It is anticipated that directed energy weapons will pose a radical and unprecedented threat to future military assets by the 2020-2025 timeframe. In order to prepare for this threat, the military must be prepared with a set of effective counters and countermeasures to use against these weapons.

Approach

In order to evaluate and recommend counters and countermeasures against DEWs, the weapons themselves must first be understood. The CDEW team thoroughly researched different types of directed energy weapons, the physics of how they work, and proposed capabilities for the given timeframe. Various scenarios were considered to explore the numerous engagement possibilities. Once the team had a complete understanding of the threats, counters and countermeasures were researched. These included physical devices and material coatings, as well as operational procedures, such as evasive maneuvering. Fully evaluating the effects of counters and countermeasures (CCMs) required consideration of weapon and CCM properties, asset behavior, and the fighting environment. In order to present the results of the analysis, different aspects of the problem needed to be integrated. A parametric environment was desired so that one would be able to see the effects of changing input variables, which would allow for instantaneous comparisons. The environment should also accommodate customizable user input, meaning attributes are subjective depending on user motivation. And lastly, the resulting product should allow for evaluation in a stand-alone platform. To model laser weapons and their effects, the team used HELEEOS, an Air Force laser propagation code. HELEEOS allows for end-to-end calculation of any figures of merit needed in this project regarding lasers. To model radio frequency weapons, an in-house tool was developed to perform direct calculation of beam attenuation from first principles and empirical trends. Surrogate models enabled rapid scenario analysis, as they are simplified models of complex problems. Specifically, artificial neural networks were selected due to their ability to model multivariate, nonlinear problems with both continuous and discrete inputs. Since surrogate models require exploration of the design space, a design of experiments (DoE) was needed to efficiently capture the design space. Once there was sufficient coverage of the design space, the surrogate models were created. These surrogates were then integrated into an Excel-based user interface. This interface would serve as the final analysis environment.

Analysis and Results

In order to evaluate and recommend counters and countermeasures against DEWs, the weapons themselves must first be understood. The CDEW team thoroughly researched different types of directed energy weapons, the physics of how they work, and proposed capabilities for the given timeframe. Various scenarios were considered to explore the numerous engagement possibilities. Once the team had a complete understanding of the threats, counters and countermeasures were researched. These included physical devices and material coatings, as well as operational procedures, such as evasive maneuvering. Fully evaluating the effects of counters and countermeasures (CCMs) required consideration of weapon and CCM properties, asset behavior, and the fighting environment. In order to present the results of the analysis, different aspects of the problem needed to be integrated. A parametric environment was desired so that one would be able to see the effects of changing input variables, which would allow for instantaneous comparisons. The environment should also accommodate customizable user input, meaning attributes are subjective depending on user motivation. And lastly, the resulting product should allow for evaluation in a stand-alone platform. To model laser weapons and their effects, the team used HELEEOS, an Air Force laser propagation code. HELEEOS allows for end-to-end calculation of any figures of merit needed in this project regarding lasers. To model radio frequency weapons, an in-house tool was developed to perform direct calculation of beam attenuation from first principles and empirical trends. Surrogate models enabled rapid scenario analysis, as they are simplified models of complex problems. Specifically, artificial neural networks were selected due to their ability to model multivariate, nonlinear problems with both continuous and discrete inputs. Since surrogate models require exploration of the design space, a design of experiments (DoE) was needed to efficiently capture the design space. Once there was sufficient coverage of the design space, the surrogate models were created. These surrogates were then integrated into an Excel-based user interface. This interface would serve as the final analysis environment. Analysis and Results (At least 1000 words) After researching current threats and future capabilities, the team had a better understanding of the physics behind directed energy weapons. Using this knowledge, a set of counters and countermeasures (CCMs) was developed. These counters and countermeasures took advantage of the threat’s limitations or amplified non-ideal conditions that would negatively affect the weapon’s performance. In creating this set of counters and countermeasures, it was assumed that the asset being protected would have the capability of active threat assessment. This meant that it would be able to detect the enemy attack, and classify the threat based on power level or type of weapon. Without this assumed capability, certain counters and countermeasures cannot be employed. For this project, countermeasures were defined as physical devices or technologies that result in the decreased effectiveness of a directed energy weapon. The list of countermeasures was broken down, based on properties, into three sub-groups: materials, hardening, and obscurants. The materials were coatings or layers that could be applied to the surface of an asset that would reflect the harmful electromagnetic waves. This would offer thermal protection by ultimately reducing the amount of power that is absorbed by the asset. Hardening countermeasures mitigate the effect of external electromagnetic fields, by either reducing the number of conductive paths or reducing the probability of electromagnetic coupling. This would allow for uninterrupted communication for assets during radio frequency attacks. Obscurants use water or smoke to create unfavorable atmospheric conditions for laser and radio frequency weapons. The remaining counters were defined as tactical procedures that result in the decreased effectiveness of a directed energy weapon. These counters made use of operating location, operating conditions, and maneuvers to negatively affect the weapon’s performance.

From there, the scope of the project was narrowed based on the engagement scenarios that would be considered. Land, sea, and air arenas were considered, whereas space was not considered due to limited available information and previous discussions with the sponsors. In choosing specific locations, two environments were chosen: maritime and continental. These locations were chosen to explore the ranges of the problem. A maritime environment would provide a “best case scenario” for countermeasures due to the increased humidity. Alternatively, a continental location would serve as a “worst case scenario” for countering weapons, as a temperate locale offers minimal threat degradation. To finish the scenario selection, enemy platforms and assets were identified. For enemy platforms, aircraft, ships, and ground-based weapons were considered. On the asset side, aircraft and ships were considered. These selections were based on projected capabilities for the 2020-2025 timeframe.

To model the laser weapons, the Air Force laser propagation model HELEEOS was utilized. This code allowed inputs of weapon and asset properties, scenario definition, and atmospheric conditions. The relevant outputs from the model were irradiance on target, probability of kill, and power in bucket. While HELEEOS was capable of end-to-end calculations for figures of merit needed in the project, it was not suitable for the modeling goals. The high dimensionality and discrete inputs caused it to run too slowly for desired functionality. Therefore, surrogate models were used to enable rapid laser scenario analysis. Artificial neural networks were selected due to their ability to handle complex, non-linear problems. Multiple neural networks were used to model the peak irradiance. In total, 64 neural networks were created to fully capture the modeling of every scenario possibility. This segmentation allowed for higher fidelity models. Multiple DoEs were created to capture the entire design space. A central composite design, a Latin hypercube design, and a full factorial design were used. A screening test was then performed to narrow the number of variables considered. The neural networks were then validated using a full factorial design that included 75% of the design space. To model the effects of radio frequency weapons, several options existed but had restricted access. Therefore the team developed an in-house model to perform direct calculation of beam attenuation from first principles and empirical trends. As there was no direct way to incorporate most of the counters and countermeasures into the modeling software, the effects of each were applied as modifiers to certain parameters with the codes. These values were based on researched effectiveness of the CCM. Weapon, asset, and environment parameters were all subject to variation. For this project, the CCMs were additive, and could be packaged together. An assumption was made that all counters and countermeasures were compatible with one another. To model the effect of a CCM, the effects were first applied to the model parameters. The model was then run under the new conditions. The new inputs resulted in new outputs, specifically probability of kill. In order to accommodate for the trades that must be made when making a selection, each counter and countermeasure had secondary attributes that were considered. These included freedom of operations, asset weight, ease of implementation, technology readiness level (TRL), and cost.

Ultimately, an Excel-based user interface was created and named Integrated Multi-Attribute Trade-off Tool, or IMATT. IMATT ran the weapon models from a single interface, integrated the use of counter and countermeasure k-factors, allowed the user to parametrically evaluate scenario inputs, and make direct comparisons between different scenarios and counters/countermeasures. To use IMATT, first a scenario is defined by the user. This includes location settings, asset and weapon inputs, a user-defined CCM package, and CCM and asset attribute weightings. Next, the scenario is run through the weapon models with no CCMs applied. The threat level is determined based on the probability of kill, which is a function of peak irradiance and material properties. The baseline is then re-calculated with CCMs applied. These packages are limited by the attribute weightings. Finally, the CCMs are ranked by probability of kill. The top 10 packages, along with the user-selected package, are then displayed, as well as several plots of effectiveness.

To recommend a set of counters and countermeasures, IMATT was utilized to investigate scenarios. The focus was on determining high-threat scenarios and effective CCMs. The IMATT outputs aided in this investigation by allowing real-time comparisons of different counters and countermeasures against given threats. Radargrams were used to allow for tradeoffs between CCM effectiveness and secondary considerations, such as TRL and freedom of operations. IMATT also allowed the team to develop REDE, or Response and Evaluation for Directed Energy. This threat architecture was created by repeating scenarios, varying inputs, and recording the top-performing CCMs. After multiple iterations of this process REDE was created. With REDE in place, a recommended set of counters and countermeasures is automatically generated once the user defines the scenario. This serves to recommend a package of CCMs based on the scenario, asset, and weapon identification.

Conclusions

In summary, the team thoroughly investigated counters and countermeasures that could be used against laser and radio frequency directed energy weapons. This scope was then narrowed to consider scenarios relevant to the 2020-2025 timeframe. A modeling and simulation environment was created based on HELEEOS and an in-house radio frequency propagation model. This environment allowed for evaluation of directed energy threats, ranking of counter and countermeasure packages for given scenarios, and direct comparisons of counters and countermeasures in real time. With IMATT, the team established a set a of recommended counter and countermeasure packages for specific studies to drive future investigative studies. While the project goal was reached, the team has identified future work to expand the scope of the project. The list of counters and countermeasures could be extended. Another improvement would be to include subject matter expert into the CCM effects and secondary attributes. Additional scenarios should be considered, such as air vs. air. Within HELEEOS, clouds and wavelength could be included as variables to enhance the fidelity of the model. Another step would be to account for supersonic applications, and therefore high-speed platforms such as missiles in the scenario definition.