N132-134 TITLE: High Power Radio Frequency (HPRF) Dynamic Surface Engagement Modeling and Simulation Tool

TECHNOLOGY AREAS: Ground/Sea Vehicles, Battlespace, Weapons

ACQUISITION PROGRAM: ONR Code 352: High Power Radio Frequency (HPRF) Basic Research

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OBJECTIVE: Develop a High Power Radio Frequency (HPRF) dynamic surface engagement modeling and simulation (M&S) tool for predicting weapon effectiveness in realistic engagements.

DESCRIPTION: To assess the utility of potential High Power Radio Frequency (HPRF) systems for surface Navy applications, a tool is required to simulate dynamic aspects of vessel versus vessel engagements. The prototype tool should cover a wide range of RF parameters to include narrow-band and wide-band technologies in the range of 0.1 - 10 GHz. The tool should enable graphic visualization of one vs. one and one vs. many engagements across a range of sea states, including a graphical depiction of the beam spot size and target coverage over the course of many tens of seconds of operation. In addition to capturing RF propagation, the tool should enable probability of effect predictions for the engagement using empirical target vulnerability data. Probability of effect predictions should include confidence bounds for extrapolation empirical effects data and/or a functional representation of effectiveness versus RF waveform parameters (frequency, pulse-width, pulse-repetition rate, etc.). This engagement tool should have the flexibility to cover a variety of ranges of interest for this application from 100s of meters to 10s of kilometers.

HPRF weapons are being developed for the US Navy. Deployment of such weapons will require evaluation of their effectiveness and the development of optimum concepts of employment. Such development may be aided by the use of modeling and simulation software capable of modeling the engagement of the HPRF platform and the threat in surface engagement scenarios. The modeling tool should free the analyst of the burdens of software configuration and allow effort to be concentrated on the development of the scenario and the analysis of the outputs expected from the tool. Results should be heavily described by graphical displays of tracked information. Control of the scenario should be through natural language and employ military terminology. The tool should employ a Graphical Unit Interface (GUI) for both scenario development and output analysis. Such utility will enable the operational warfighter to run "what if" scenarios to assess plans and weapon combinations and effectiveness.

The user should be able to specify ranges of parameters of interest or specific scenario parameters that could be varied in repeated runs of the scenario. The tool should provide an indication of the statistical significance for the number of runs required to be executed for a statistically significant result. The tool should also be able to optimize the scenario based on one or more parameters, either for defense or offense. This will free the user from repeated scenario development to obtain optimum performance. The tool should be able to interpolate outcome if parameters are changed, based on previous runs. The code should also be calibrated against real world data.

The HPRF system should be described in terms of source power, antenna gain, pulse repetition rate, pulse width and polarization. The model should have the capability to limit the transmission time possible with the source, so as to mimic a battery operated system with limited energy storage. Propagation of the HPRF beam through the environment of the scenario should be included in the model. Though free space propagation may be trivial, the propagation to a surface target will need to include approximations for the effect of multipath. This may be a complex process for near surface targets such as small boats; ranges of interest for this application are from 100s of meters to 10s of kilometers. The time required to take an HPRF weapon from standby to firing should be included in the model.

The simulation tool should account for environmental conditions. This includes sea state, fog, and rain that could influence the propagation of the HPRF beam as well as mobility and visibility. Such conditions could be significant contributors to the utility of a system.

The HPRF platform types in the simulation tool should initially include large vessels, small vessels and unmanned surface vehicles and with future inclusion of unmanned aerial vehicles. Each should include the ability to account for the effect of the size, weight and power (SWaP) of the platform carrying the HPRF system.

Threats to be included in the scenario should include small vessels and in later stages consideration for UAVs. The modeling should account for one on one, one on many and many on many conditions. HPRF systems may also be employed on a ship, a single small boat, a USV, or defensive swarms that may be prepositioned on a ship or patrolling about a high valued target.

Also of interest, but not required, consideration could be given for an engagement tool for comparison between HPRF systems and conventional weapons. In addition, the enhancement of conventional weapons when HPRF is included in the mix could be investigated. This conventional weapons aspect would be added in stages. Conventional ship weapons (guns, cannon, etc.) would be included in the modeling. The range, magazine size, rate of fire, and effectiveness would be part of the modeling. The capability to include the occulting of weapons by ship structures would be included.

Unless proven otherwise, the modeling should be a combination of user driven and agent based simulation (ABS) control of objects and events. Agents are objects in the simulation that accept input of the evolving scenario through sensors and respond accordingly as specified by the scenario developer. The behavior of the agents is guided by a set of parameters unique to that agent that guides its behavior for each time cycle and the environment around it. Offerors should take advantage of existing Agent based simulation software and not build a system from scaratch.

Agents communicate with other agents, are guided by objectives and have specified capabilities. Based on the input from the evolving scenario an agent may make decisions that affect the action. Vector based location is preferred. Model latency should be specified and smaller than smallest event time duration. The ABS approach executes a scenario from a specified start point through the combined behavior of individual autonomous actors. This results in often unexpected behavior as a scenario progresses through all the possibilities.

Computer hardware that will be used run the tool should be commercially available hardware and the software should be easily ported. The developer should scope out the hardware required for the full employment of the requirements identified here. This should include run time assessment and graphics needed.

To aid in the degree of realism and the rapid conveying of engagements, realistic objects need to be included in the simulation. A library of 3-Dimensional objects to be used in the simulation should be included. This includes boats, ships, ports, UAVs, and USVs. Software for the conversion of 3D models to the type used in the simulation tool should be included in the software suite so that available models from other libraries may be imported into the simulation tool. In addition, software enabling the inclusion of topology from freely available sources such as Google maps or other sources should be part of the software suite. The tool should also have the ability to modify this topology.

Innovative research and development is needed in ABS methodology to develop the capability to accurately explore the statistical space for the user. This is crucial for proper examination of a scenario. The ABS, given a starting scenario should be able to optimize the scenario based on selected parameters. For example, given an attack by multiple small boats on a large vessel protected by USVs, a potential optimization parameter could be the positioning of the USVs in a picket formation. The attackers could have multiple options for attack so the model should be able to run the simulation and develop the optimum locations PHASE I: The basic ABS system involving a ship and small boat attackers shall be developed using existing ABS software. The HPRF system shall be implemented and shall include the RF multipath effect. The tool shall permit the installation of HPRF systems on the ship or on USV defenders. This requires setting of the HPRF weapon agent�s effective range and effect. The weapon should be paired with a sensor agent on the ship that controls the detection of threats. The key part in Phase I is describing the proposed optimization algorithms that will be developed in the next Phases. The methodology should be described and demonstrated sufficiently to be able to estimate the computer resources that will be required for full implementation. This phase should also include the development of user friendly GUIs that employ natural language and military terminology for scenario development. It is not expected that the natural language function be completely implemented, but that the capability is demonstrated sufficiently so that estimates may be made of the computer resources required for full implementation. Scenarios to be tested include (1) attack by a single exploding boat, posing as a noncombatant, and (2) a swarm of 5 attacking boats. Displays should be able to show planar view of developing movements at selected timescale. Views from selected agents are also useful. Simplified agent models may be employed but capability of expansion to full capability modeling needs to be demonstrated. The optimization algorithm will be demonstrated. Recommended hardware to host the development package shall be described. Estimates of computer resources for the full model shall be conducted. Successfully demonstrating feasibility in this restricted model will be the criteria for Phase II selections.

PHASE II: The performer will scale up the concept developed during Phase I to include small boat attackers and USVs numbering up to 50 agents each. The simulation tool should include environmental conditions. The optimization capability shall be fully developed in the model. Ship movement shall be included. Full development of the scenario development controls will be added. Full analysis capability will be included. The optimization model will be exercised and tested by users to ensure its ease of usability to extract topological data from sources such as Google maps shall be included. Conversions software for importing 3D models of other types will be added to the software. Estimates of computer resources for the full model shall be conducted. Documentation shall be provided for the hardware and software systems. Conventional weapons for comparison purposes could be included where possible.

PHASE III: The performer will apply the knowledge gained during Phase II to build a complete model that provides all required functionality. The library will be populated with functional models of Naval vessels, USVs, and UAVs. The optimization capability should be fully enabled with the ability for optimization up to key parameters. Documentation shall be completed for the full model.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: RF propagation modeling and simulation for over water and land environments is of use in a variety of communications and sensor bases systems where electromagnetic interference needs to be considered and planned for shielding and proper operation.

REFERENCES:
1. Robust Defense Against Small Boat Attacks, Ka-Yoon Wong, Masters Thesis Naval Post Graduate School, December 2010

2. Small Boat And Swarm Defense: A Gap Study, Andre N. Tiwari, Masters Thesis Naval Post Graduate School, September 2008.

3. Modeling Force Response To Small Boat Attack Against High Value Commercial Ships, David J. Walton, Proceedings of the 2005 Winter Simulation Conference, M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds., p 988.

4. Military Applications Of Agent-Based Simulations, Thomas M. Cioppa et al, Proceedings of the 2004 Winter Simulation Conference, R .G. Ingalls, M. D. Rossetti, J. S. Smith, and B. A. Peters, eds., p 180.

5. Analyzing Anti-Terrorist Tactical Effectiveness Of Picket Boats For Force Protection Of Navy Ships Using X3d Graphics And Agent-Based Simulation, James W. Harney, Masters Thesis, Naval Postgraduate School, March 2003.

6. Exploring The World Of Agent-Based Simulations:Simple Models, Complex Analyses, Susan M. Sanchez, Thomas W. Lucas, Proceedings of the 2002 Winter Simulation Conference, E. Yücesan, C.-H. Chen, J. L. Snowdon, and J. M. Charnes, eds., p 118.

7. Modeling Robot Swarms Using Agent-Based Simulation; Alistair Dickie, Masters Thesis, Naval Post Graduate School, June 2002.

8. Recent Developments in the agent based model MANNA, Gregory MacIntosh, et al., The Scyth, Issue 1, p 38

KEYWORDS: Agent-Based Simulation; HPRF; Small Boat Attack; Swarm; HPM; Engagement

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