Applica'on of Mine Burial Expert System (MBES) to Mine Warfare (MW) Doctrine w/ Unmanned Underwater Vehicle Case Study

Transcription

1 Applica'on of Mine Burial Expert System (MBES) to Mine Warfare (MW) Doctrine w/ Unmanned Underwater Vehicle Case Study LCDR Jason D. Gipson, USN MS Student - Mete Thesis Advisor: Dr. Peter C. Chu, NPS OC Department Second Reader(s): Ronald E Bestch NAVOCEANO MW Program Manager Dr. Peter Fleischer, NAVOCEANO

2 Scheme and Maneuver BLUF Opera'onal Environment MW and Mine Countermeasure (MCM) considera'ons UUV Case Study Players MK18 MOD1 Swordfish and MOD2 Kingfish UUV systems MW Doctrine MBES Conclusion

3 BLUF US Navy has a limited ability to buried mines, mine- like objects or non mine- like objects but has robust capabili'es for find proud, bo*om and moored mines Buried mines pose as tremendous threats to many missions sets: Very Shallow Water (VSW) Mine Countermeasures (MCM) ISO amphibious opera'ons Examples - Force Entry or Air- Sea Ba]le Underwater MCM and Surface MCM Mari'me Homeland Defense (M- HLD) Mine Danger Area clearance Sea Lines of Communica'on POWER PROJECTION Mee'ng the threat requires an understanding of the opera'onal environment and the technology and available resources to exploit and then render safe the threat Exploita:on of the environment can gain momentum through understanding MW and MCM in terms of suppor'ng Navy and Joint Doctrine to meet both military and na'onal strategic and opera'onal needs (requirements) but more importantly gaining knowledge of uncertainty and risk Current MW doctrine, notably in terms of how the Doctrinal Bo]om Type is assessed and assigned is outdated wrt current technology and numerical predic:on methods as well with modern environmental (sea floor composi'on) collec'on stores and robust sediment classifica:on systems America s poten0al enemies have observed the success of its power projec0on opera0ons over the last two decades and have learned that a:emp0ng to counter the U.S. military symmetrically, or head- on, is a recipe for defeat. ~ Center for Strategic and Budgetary Assessments

4 BLUF What was I thinking? Thesis thoughts from opera'onal perspec've: Percent Clearance Probability of Detec'on and Iden'fica'on Applica'ons of Risk and Uncertainty Frac'on of Undetectable Mines Applica'on of METOC Ba]lespace on Demand (BonD) Exploit the environment Numerical Modeling Data Stores Tac'cs Tradi'onal (MEDAL derived) Hydrographic (Coverage) Sensor Performance Approach Meta- analysis of current opera'onal state of MBES Applica'on to 'me vs. DBT (uncertainty) for UUV opera'ons Refine doctrinal binning system Review new model inputs

5 BLUF MBES Interpreta'on and Use Issues to be resolved and Poten'al NPS thesis topics: Communica'ng the Probability Distribu'on Func'ons (PDFs) Need for standardized measures appropriate for planning and tac'cs Sta's'cal measures, burial greater than threshold %, etc. Proper Binning of Burial Categories Doctrinal unequal 5- bin vs. MBES 10% bins What bin sizes are opera'onally meaningful? Impact on MIW Doctrine Adapt MBES measures to exis'ng doctrine Use MBES predic'ons to improve doctrine Informa0onal Inputs by NAVO and NRL- Stennis

6 Figure from Rennie; concept provided by self from EODMU ONE CONOPS brief M- HLD

7 From NWP 3-15

8 UUV Key Players

9 MK18 MOD1 Swordfish UUV Hydroid REMUS 100 Capabilities: 2 man portable Low visibility Ops IPOE (Intelligence Preparation of the Environment) SCM (Search, Classify and Map) RI (Reacquire and Identify) BULS (Bottom Underwater Localization System) M-HLD (Maritime Homeland Defense) Operated from indigenous EODMU ONE 11m RHIB, Combat Rubber Raiding Craft (CRRC), Shore or Ship Chuck Launch, Boat-of-Opportunity Bottom mapping from (VSW Zone) Operational depth up to 100m/328ft Large area coverage (nominal 32 amphibious assault lanes) Utilizing large inventory Proud, bottom and moored mine-like contacts but not buried Navigation methods: Transponders GPS (Inertial Navigation System) Dead reckoning

10 MK 18 Mod 2 Kingfish UUV Hydroid REMUS 600 Capabilities: Low visibility Ops to conduct IPOE Over-the-Horizon Environmental Reconnaissance IOT provide DBT classification for contact density and bottom composition SCM RI M-HLD Currently under UOES Ease of deployment and transport Operated from indigenous EODMU ONE 11m RHIB Large area coverage (nominal 32 amphibious assault lanes) Proud, bottom, moored and buried mine-like contacts utilizing SAS Sidescan (i.e. SSAM) Navigation Transponders GPS (Inertial Navigation System) Dead Reckoning (Maritime Homeland Defense)

11 MW Bottom Characteristics Requirements MW Doctrinal Bo*om Analysis Based on NWP 3-15 DBT defines tac'cs u'lized Mine Hunt Sweep MW Doctrine for Burial Processes Impact Burial Scour Subsequent Burial Slide inputs courtesy of NAVOCEANO Dr. Peter Fleischer

12 MW Doctrinal Bo]om Types and Burial Bo*om Types: A- 1,2,3 B- 1,2,3 C- 1,2,3 D- 1,2,3 10% uncertainty probability 0% 10% 55% uncertainty 20% 75% 100% percent burial Doctrinal burial: Only 5 possible states No mechanism for handling INPUT uncertainty Empirical

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14 B A. Sediment type MBES Concept and Scope Sponsor: ONR Mine Burial Research Program MBES Developer: JHU/APL Transi:on coordina:on: NRL- SSC B. Correla'on C. Probability Installed in EPMA Opera:on integra:on: NAVO Environmental informa'on A Mine (tac'cal) informa'on Bayesian inference engine %Burial Burial probability Naval Opera'ons Burial process knowledge (models) MBES provides: - Realis:c predic:ons with various data - Knowledge of the quality of the predic:on - Credible CONFIDENCE and RISK measures

15 MBES - Technical Descrip:on Environmental inputs drive probabilis:c predic:ons Scour Burial Module - example Impact Burial Module - example INPUT Shear strength Water depth Mine type Angle of release Center of mass INPUT Grain size Water depth Tidal current Wave current Elapsed +me OUTPUT Probability Distribu:on Func:on Slide informa0on courtesy of NAVO (Dr. Peter Fleischer) %Burial

16 Mine Burial Expert System MBES Current Status of NAVO/Opera:onal mine burial Predic:on Impact burial predic'on is based on sediment categories No capability for subsequent burial predic'on No models are used No measures of quality or confidence MBES Advantages Physics- based IMPACT and SUBSEQUENT BURIAL models Specific mine shapes Ingests data of varying quality/quan'ty Produces probability distribu'on func'on of burial Payoff Realis:c burial predic'ons regardless of data quality Probabilis'c approach allows credible MIW CONFIDENCE and RISK measures Contributes to improvement of MIW doctrine Courtesy of NRL- Stennis Space Center (Nathanial Plant)

17 Example MBES Burial Predic'ons Impact burial Core analysis NAVO Sediment Databases Subsequent Burial (slides hidden) Simple Sta'c Inputs Time Series

18 Percent Mine- case burial Most Probable Example MBES Impact Burial Predic'on from Sediment Core Analysis Input Parameters Defined Region Mine Type Surface- Dropped Impact Burial (Creep not included) Measured Shear Strength from cores Depths at core loca:ons Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

19 Example MBES Impact Burial Predic'on from Sediment Core Analysis STANDARD Predic:on Doctrinal Burial based on Sediment Provinces from NAVO Sediment Databases MBES- Predicted Doctrinal Burial Category Burial Category (20% - 75%) MBES predic:on leads to a B Bo*om, BUT extent of category makes predic:on misleading HOWEVER - MBES provides a measure of Risk that category is over- or under- es:mated:

20 Example MBES Impact Burial Predic'on from Sediment Core Analysis For MBES- Predicted Doctrinal Burial Category of 20%- 75%: Likelihood that burial is in 75%- 100% Category is 30%- 40% for upper region Probability of burial in excess of 75% Likelihood that burial is in 10%- 20% Category is 0 en:re region Input Parameters Probability of burial under 20% 0 Defined Region Mine Type Surface- Dropped Impact Burial (Creep not included) Measured Shear Strength from cores Depths at core loca:ons Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

21 Example MBES Impact Burial Predic'on from Sediment Core Analysis Example Probability Distribu:on Func:ons (PDF) 1 Shear Strength PDF from Core Analysis 0.25 Mine- Case Burial PDF probability Highest Burial Loca:on probability probability Lowest Burial Loca:on probability shear strength, kpa percent burial Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

22 Example MBES Impact Burial Predic'on from Sediment Provinces in NAVO Sediment Databases Percent Mine- case burial Most Probable Not determined (Low or None) Input Parameters Defined Region Mine Type Surface- Dropped Impact Burial (Creep not included) Sediment Provinces Bathymetry Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

23 Example MBES Impact Burial Predic'on from Sediment Provinces in NAVO Sediment Databases STANDARD Predic:on Doctrinal Burial based on Sediment Provinces from NAVO Sediment Databases MBES- Predicted Doctrinal Burial Category (0% - 20%) (20% - 75%) Burial Category AGAIN, MBES predic:on leads to a B Bo*om, BUT extent of category makes predic:on misleading HOWEVER, MBES provides a measure of Risk that category is over- or under- es:mated: Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

24 Example MBES Impact Burial Predic'on from Sediment Provinces in NAVO Sediment Databases For MBES- Predicted Doctrinal Burial Category of 20%- 75%: Probability of burial in excess of predicted Likelihood that burial is in 75%- 100% Category is 30% for most of region Likelihood that burial is in 10%- 20% Category is 0 for most of region Probability of burial below predicted Slide informa0on courtesy of NAVO (Dr. Peter Fleischer) MBES Predicted Doctrinal Burial Category (0% - 20%) (20% - 75%)

25 Example MBES Impact Burial Predic'ons Summary of Example results MBES predic'ons for most probable impact mine- case burial are 50% to 75%, with a significant probability that 75% burial will be exceeded. MBES results, using shear strength profiles from cores, and using MIW sediment provinces, agree well in this example. The cores allow greater discrimina'on: sediment composi'on is fairly constant, but sediment shear strengths will vary regionally. A predic'on within the 20%- 75% doctrinal burial category can be treacherous. This is an issue with the doctrinal burial categories, not with the MBES. The interpreted, sediment database predic'on of 75%- 100% in this example is conserva've, which may be jus'fied by the MBES results. Burial results are for ini'al impact burial. Commonly, further burial by sediment compac'on (creep) will increase the final burial state. Slide informa0on courtesy of NAVO (Dr. Peter Fleischer)

26 MBES and Bo]om Type/Burial Doctrine MBES generates quan'ta've, reproducible predic'ons of impact and subsequent burial from a wide range of inputs. Current Burial doctrine has no measure of uncertainty. With the MBES, uncertainty is quan'fied in a Probability Distribu'on Func'on (PDF). The MBES will work with current doctrine, but much useful informa'on will be ignored. MBES is dummed down when converted into doctrinal categories A significant shortcoming of current Bo]om- Type doctrine is the 20%- 75% burial category. The MBES produces PDFs in 10% increments. PDFs are informa'on- rich and can be exploited for measures and defini'ons of Likely burial (mean, most probable, etc.) Limi'ng burial (exceeding a predefined percent) Risk (percen'le range of burial, i.e., 50, 64, 95) Confidence (e.g., standard devia'on) Other? Informa'on generated by the MBES is complex. Standard, comprehensible doctrinal burial a]ributes need to be defined. A consistent set of opera'onal outputs is essen'al. Input in associa0on with NAVOCEANO (Dr. Peter Fleischer) and NRL- Stennis Space Center (Nathanial Plant)

27 Driving the tac'c U'lity of predic'ng PDFs Evaluate uncertainty Evaluate risk prob(burial>cri'cal burial)=(1- α) Current Doctrine moving to sweep vice hunt opera'ons MBES indicates tac'cal considera'on for Mine Hunt of proud mines TIME (1:1 PMA) burial percentiles 100 (1-α) = 5 th 50 th 95 th most likely burial Slide informa0on courtesy of NAVO (Dr. Peter Fleischer) conservative estimate

28 Ques'ons?