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A POSSIBLE STOCHASTIC APPROACH to THREAT ASSESSMENT

UNCLASSIFIED. 1 st Annual Israel Multinational BMD Conference & Exhibition. A POSSIBLE STOCHASTIC APPROACH to THREAT ASSESSMENT. Presented By : BG(R) R. Eyal WALES, Ltd., Israel. A Stochastic Approach to Threat Assessment - 1 /15. UNCLASSIFIED. WALES, Ltd. MAY 2010. INTRODUCTION.

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A POSSIBLE STOCHASTIC APPROACH to THREAT ASSESSMENT

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  1. UNCLASSIFIED 1st Annual Israel Multinational BMD Conference & Exhibition A POSSIBLE STOCHASTIC APPROACH to THREAT ASSESSMENT Presented By: BG(R) R. Eyal WALES, Ltd., Israel A Stochastic Approach to Threat Assessment - 1/15 UNCLASSIFIED WALES, Ltd. • MAY2010

  2. INTRODUCTION • Threat Assessment is an essential input for ballistic missile defense architecture formulation and evaluation • Without underestimating the importance of data on ballistic missiles` technical attributes, Reference Scenarios are extremely important for determining architecture design points and estimating the existing performance safety margins • Among the many reasons that compel addressing scenarios the following may be pointed out: • They are a must for evaluating “many-on-many” events • Scenarios are flexible, can be easily changed and therefore a wide variety of them must be checked • They can reveal weaknesses in system and architecture robustness • This presentation is devoted to a Stochastic Approach to Reference Scenario Generation, within the Threat Assessment context

  3. OBJECTIVES • To propose a tool for generation of stochastic scenarios intended to serve Ballistic Missile Defense (BMD) developers and enable: • Use of computerized war games and simulations • Evaluation of BMD systems and architectures • Estimation of their robustness • Evaluation of different sets of Rules Of Engagement (ROEs) and their impact on attainable defense levels • The basic concept is illustrated in later slides and is supported by results produced by a high number (hundreds or thousands) of runs

  4. LIMITATIONS / DEFICIENCIES OF THE TRADITIONAL METHOD • The alternative approach offers a number of deterministic reference scenarios • This number is always finite and most often very small- enough to represent only a limited set of possible Courses Of Action (COA) • Deterministic scenarios have a low probability of representing real future events • Intelligence Officers find themselves in uncomfortable situations whenever they must commit to a few limited possible COAs, with no tools to convey information gaps, uncertainties, dilemmas, inherent risks or suggest assessment safety margins • The suggested stochastic method overcomes these difficulties

  5. SIMULATION`S OUTPUT Typical Assessed Intensity Range Better than specified performance Defense Performance (MOE) Required nominal performance range Required typical performance Missile Attack Intensity Poor performance

  6. SIMULATION`S OUTPUT Typical Assessed Intensity Range Exceptional performance Defense Performance (MOE) Required nominal performance range Architecture's weakness Missile Attack Intensity Collapse of the architecture

  7. CORE PARAMETERS ESSENTIAL FOR SCENARIO DEFINITION • The core parameters essential for simulation of any scenario are: • Launch site’s location • TBM types • Trajectory characteristics • Launch time • Target location • All these for any single TBM • Additional parameters can be used for refinement of the model, but due to time constraints are not mentioned here

  8. CONCEPTUAL (SIMPLIFIED) FLOWCHART FOR REFERENCE SCENARIO GENERATION Basic Script Target / Cluster Allocation per TBM Unit Targets Target Allocation per TBM T= 0 Start Participating Adversaries Engagement Time Probability per Target Trajectory Attrition ORBAT Factor Engaged Target Unit`s Launch TBM Launch Participating Timing Time ORBAT No Continue? End Yes Participating TBM Launchers` Locations Time Off/Launcher

  9. CONCEPTUAL FLOWCHART FOR REFERENCE SCENARIO GENERATION * Basic Script Target / Cluster Allocation per TBM Unit Target Allocation per TBM Targets T= 0 Start Participating Adversaries Engagement Time Probability per Target * Trajectory Attrition ORBAT Factor Engaged Target Unit`s Launch TBM Launch Participating Timing Time ORBAT No End Continue? Participating TBM Launchers` Locations Yes LEGEND * Drawn for single random scenario or manually selected and frozen for simulation of a complete war Time Off/Launcher * Range limit will determine legitimate combination of launch sites, TBM types, targets and trajectories Stochastic variable

  10. A similar table can be produced according to TBM types, if needed The logic should be influenced, for example, by: missile range, RV type, impact accuracy, relative estimated target value Legend: SRBM = Short Range Ballistic Missile MRBM = Medium Range Bal` Missile LRBM = Long Range Ballistic Missile MATCHING BETWEEN TARGETS AND MISSILE TYPES Upper limit (% of total) launched to any single target Prob` of target to be attacked by (%) SRBM MRBM LRBM TAR` # A B C D E F G H I J - - L M N P - - - - X 0 Y Z - - S T R 0 - - 1 2 3 4 5 6 7 8 9 10 - - Total (%) 100 100 100 >100

  11. CONCEIVABLE DISTRIBUTION PATTERNS AROUND NOMINAL VALUES • Different distribution graphs characterize the various parameters that are taken into account • Technical as well as operational logic influences the selection of distribution that matches this logic • The Normal Distribution on the right, under certain conditions, could, for example, describe a complete scenario run in a specific game Number of TBMs launched as a function of time N Time

  12. EXAMPLES OF CONCEIVABLE DISTRIBUTION PATTERNS Trajectory type Prob. EOB γ Number of TBMs launched against a 3-rd priority target Intermission between consecutive launches from same launcher Prob. Prob. Time N

  13. DETERMINATION OF PARAMETER VALUE LIMITS • Examples of approaches helpful in determination of values and patterns: • Observation and/or available data • Constrained by performance known from the past (min) and state of the art (max) • Limited by pessimistic (worst case) and optimistic (permissive) experts` approach and estimates • Widest conceivable limits • Wild guess

  14. DETERMINISTIC vs. STOCHASTIC APPROACH • The two should be considered complementary to each other and not substitutes • Extreme cases (worst case analysis, for example) can be best examined by the deterministic approach • Macro analysis conducted by stochastic methods can support estimation of calculated risks with a clear vision of where the risk lies and how the calculation was performed • Extreme cases revealed by the stochastic method should trigger closer individual analysis and careful “zoom in”

  15. WALES, Ltd’s EXPERIENCE WITH STOCHASTIC SCENARIOS • Stochastic Threat Assessment and Stochastic Presentation of the Threat is one of several tools developed by WALES, Ltd. for evaluation of Missile Defense Performance and Architecture Robustness • Its unique contribution and effectiveness have been proven in studies and simulations conducted for more than ten years • The model undergoes continuous modifications and enhancements in order to adjust it to new challenges, including description of scenarios that are typical to Short Range Missiles and Artillery Rockets launched in masses • Stochastic Threat Assessment outputs are fed to suitable Architecture Models and Simulation developed in parallel for extensive exploitation of the existing potential. They were not shown since they are out of scope of the presented topic

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