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2004-12

The effective use of multiple unmanned aerial vehicles in surface search and control

Berner, Robert Andrew

Monterey, California. Naval Postgraduate School http://hdl.handle.net/10945/1318

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MONTEREY, CALIFORNIA

THESIS

THE EFFECTIVE USE OF MULTIPLE UNMANNED AERIAL VEHICLES IN SURFACE SEARCH AND CONTROL

by Robert Andrew Berner

December 2004

Thesis Advisor: Thomas W. Lucas Second Reader: Russell Gottfried

Approved for public release; distribution is unlimited.

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1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORT TYPE AND DATES December 2004 COVERED Master’s Thesis 4. TITLE AND SUBTITLE: The Effective Use of Multiple 5. FUNDING NUMBERS Unmanned Aerial Vehicles in Surface Search and Control

6. AUTHOR(S) Berner, Robert A.

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION Naval Postgraduate School REPORT NUMBER

Monterey, CA 93943-5000

9. SPONSORING /MONITORING AGENCY NAME(S) AND 10. SPONSORING/MONITORING ADDRESS (ES) AGENCY REPORT NUMBER

N/A

11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government.

12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release;distribution is unlimited. A

13. ABSTRACT (maximum 200 words)

This study analyzes the effective use of multiple unmanned aerial vehicles (UAVs) for the Navy’s Surface Search and Control mission. In the future, the Navy hopes to leverage the capabilities of a family of UAVs to provide increased situational awareness in the maritime environment. This family of UAVs includes a Broad Area Maritime Surveillance (BAMS) UAV and Vertical Take-Off UAVs (VTUAVs). The concepts of operations for how these UAVs work together have yet to be determined. Questions exist about the best number of UAVs, types of UAVs, and tactics that will provide increased capabilities. Through modeling and agent-based simulation, this study explores the validity of future UAV requirements and provides insights into the effectiveness of different UAV combinations. For the scenarios modeled, the best UAV combination is BAMS plus two or three VTUAVs. However, analysis shows that small numbers of VTUAVs can perform as well without BAMS as they do with BAMS. For combinations with multiple UAVs, BAMS proves to be a valuable asset that not only reduces the number of missed classifications, but greatly improves the amount of coverage on all contacts in the maritime environment. BAMS tactics have less effect than the mere presence of BAMS itself.

14. SUBJECT TERMS Unmanned Aerial Vehicles, UAVs, Agent-based [| 15. NUMBER OF modeling, MANA, Surface Search and Control, Surface Surveillance | PAGES Coordination, SSC, Broad Area Maritime Surveillance, BAMS, Vertical 177

Take-Off Unmanned Aerial Vehicle, VTUAV, Common Operational Picture 16. PRICE CODE

17. SECURITY 18. SECURITY 19. SECURITY 20. LIMITATION CLASSIFICATION OF CLASSIFICATION OF THIS CLASSIFICATION OF OF ABSTRACT REPORT PAGE ABSTRACT

Unclassified Unclassified Unclassified UL

NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. 239-18

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Approved for public release; distribution is unlimited.

THE EFFECTIVE USE OF MULTIPLE UNMANNED AERIAL VEHICLES IN SURFACE SEARCH AND CONTROL

Robert Andrew Berner Lieutenant, United States Navy B.S., United States Naval Academy, 1996

Submitted in partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE IN OPERATIONS RESEARCH from the

NAVAL POSTGRADUATE SCHOOL December, 2004

Author: Robert Andrew Berner

Approved by: Thomas W. Lucas Thesis Advisor

Russell Gottfried Second Reader

James N. Eagle Chairman, Department of Operations Research

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ABSTRACT

This study analyzes the effective use of multiple unmanned aerial vehicles (UAVs) for the Navy’s Surface Search and Control mission. In the future, the Navy hopes to leverage the capabilities of a family of UAVs to provide increased Situational awareness in the maritime environment. This family of UAVs includes a Broad Area Maritime Surveillance (BAMS) UAV and Vertical Take-Off UAVs (VTUAVS) . The concepts of operations for how these UAVs work together have yet to be determined. Questions exist about the best number of UAVs, types of UAVs, and tactics that will provide increased capabilities. Through modeling and agent-based simulation, this study explores’ the validity of future UAV requirements and provides insights into the effectiveness of different UAV combinations. For the scenarios modeled, the best UAV combination is BAMS plus two or three VTUAVs. However, analysis shows that small numbers of VTUAVs can perform as well without BAMS as they do with BAMS. For combinations with multiple UAVs, BAMS proves to be a valuable asset that not only reduces the number of missed classifications, but greatly improves the amount of coverage on all contacts in the maritime environment. BAMS tactics have less effect than the mere

presence of BAMS itself.

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TABLE OF CONTENTS

ENTRODUCIELON: 2) gecte re atig tesa abode le onary oGgrevatetenonas ones abe ca ate Avena elke 1 BPROBLEM/NAVY INTEREST: }a054 Uv wee eG Coe wa we eae oe oa ees 1 A PREV TOUS STUDY: 5 ssc tok el sees Gis Bee eee Gee eGR ete 2 KEY ISSUES AND CONCEPTS ......................0.4. 4

BACKGROUND: & se ee eae Hak bed whe Sok SE Se RS ae Se ee ae Se alae OVERVIEW! 5:52. 3.4. Sw te bade ee Side dee ea eh ed ae SB es a ee See aE UAV CHARACTERISTICS 206 ab we ee eee Re ee 11 1. BAMS oe ea. Soe Sie A eb ite Te Be, Be BE Re ee a we Ss ie 11 2. WUBI Sse. casi Si het Sos tan tet vO sah ae sd taped Seat at ae ale ene a et Ba elle 13 SCENARTOS, 203 boise kd dei w dekh see dtekcdabatekdcak ads 15 As Embargo Scenario .......... 2. eee eee 18

hice MS UMMA Yop ay fa vas, sed os aah Sop apd 2s, whale Sewanee oh canes de 18 b. Scenario Background and Initial CONG TET OG ones 2 areca Sele tls Yeoh GUN at ata wos Se gale als Tak 19 c. Operating Conditions .................66. 20 dy .PFrOCESSES ss5 6b 4 BS Be Eee A ee 20 6s CONSEPALNUS 202-4 baeeedy Bon Ed Bele ae S eee ae 21 f. Measures of Effectiveness .............. 21 Zs Assured Access Scenario ...............000- 23 Bis SUMMA soos, wien So aetna) Sie Bee eee Re Ryle ee to eee 23 b. Scenario Background and Initial CONGL ETON Ss 2.0.5 6ict awe eh ee Sea 24 c. Operating Conditions .................-. 25 Gin <PFOCES SOS esha oye Bide he ands Shia hn BE ea Sade Bila andy Sava bee 26 C4 SCONSELAIRES® ihe we Ge da ea tele hog ea a 26 f. Measures of Effectiveness .............. 27 MODEL SELECTION AND JUSTIFICATION .............. 28

MODEL IMPLEMENTATION AND EXPERIMENTS ................ 33 GENERAL OVERVIEW OF MODEL ...................... 33 CREATIVE. “MODETDING: 2 esd sai & wd ae as ae ee Ba a Sk. oe 35 1. Refueling, “Stealth Mode,” and

COMMUNTCAELTONS 6.0) 6 ied eal a ee eS Sete od A Sle ek 35 2 Weapon and “Shadow Ships” ................. 39 MANA AND SCENARIO DETAILS ...................... 40 al Batt lefielasy 25. eek eda k hoe ara kaos ae SS 40 2 BAM S 25 be enon at Gas “aired Sew ee Se Seles ee aes BES enor bebe Sy ae hares Oe 42 3. BHemy «Shas ossce eo tie eis a Be pan ee ee aie wh 52 4. Neutral). (SHLD S 36 eb gu cele bk Beach eel doh. eee betel Bay 53 5 Fishing: Vessels: .40 seed baws See Aes Bee aes 54 6. CS vend: whos By ek as oe Be ae So hoe Heke ok Sek Seale Se 54 pee VITUAN 85. te cs 8.3) ar eee Be Sa ee BO SS oe Se ae eS 56 EXPERIMENTAL SET-UP, TACTICS, AND WEATHER ...... 61 Ly Experimental Set-up ...............2222000- 61

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a. Red Force Maneuvers ........... cece eens 63 Ds: BLUE FOrCe: TACEL OS ox Sosevca salt Sas Bile BORE 68 IV. EXPERIMENT ANALYSIS AND RESULTS ..................2.04. 75 A. EMBARGO SCENARIO RESULTS ...............2020 2022 e ee 76 1. Timeliness in Establishing the COP........ 76 a. Effects of Tactics on Classification TENE Neo pop Ooo oe aot ell Gee le ecntes 6 BO Die 88 82 b. Classification Location as an Indicator Of “TIME IANE SS fs c0g sts PSS ESN bags ee ae eed 87 2 Completeness in Establishing the COP...... 90 35 Classification Continuity on the COP...... 96 B. ASSURED ACCESS: RESULTS? sos: 645, te Sra wp oh a Sa dhe oS 102 dle Timeliness in Establishing the COP....... 102 a. Effect of Tactics and Maneuvers on Classification Timeliness ................ 107 b. Classification Location as an Indication Of TIm@lINSS S424, he cee 8 we ela Woe Shoe eds BRE 6 hoe 109 2: Completeness of the COP.................. 111 Bi. Classification Continuity on the COP..... 114 Cc ACCOUNTING FOR WEATHER IN ESTABLISHING THE COP 123 V CONCLUSIONS AND RECOMMENDATIONS ..............2.200005 129 A PRIMARY -PINDINGS 3 sce gh Sy 6 Bl S eo SSS So SE RSS ew 129 B ADD TT-LONAT: -PeENDINGS* 3. sos xe Si. siis orange ar Sots wedi a bale edd 132 Cc ASSUMPTIONS AND LIMITATIONS ................... 133 D OPERATIONAL IMPACT OF STUDY AND RECOMMENDATIONS135 E FOLLOW-ON RESEARCH) .oxiccpcex eit wiki as sie eee we Se 136 APPENDIX. GAMBA GS Te yaa a fea area wah at car iw “aria op ebay at iepog bartes arg aces cepa “ard 139 BEB TLOGRA PHY: tose wast suk) ook ashi e! le a5 lao a ohh otis goer obs) aie col le aber Sor wl wae ote Uae or 4) a 145 LEST. OF (REP ERENCES? pce gs. ee He Seale S wh 2s SS SS SS aS wR Se es 149 INITIAL: DESTRIBULION DLS PT 9. 4 sce aeie, we Re eee et Ree eo we ees 153

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LIST OF FIGURES

Figure 1: Global Hawk Maritime Demonstration ............. 1:2 Bagure 2 RO oe: Pine SCOul VTUAY: vere 5.8 aN weeny deere ang alte Giwe wile 14 Pigure: 33 Embargo Scenario ws «.esihee Peete Pee See eS ESS 18 Figure 4: Assured Access Scenario (best viewed in color) . 24

Figure 5: Red force “Direct” tactic for Embargo scenario (best: viewed “an color) .2s dhe eel eee haw e hee Re oe b eos ERS 63

Figure 6: Red force “Coastal” tactic for Embargo scenario (DSS. Viewed 2m tee diOe plough gob Giulia gee tle SUAS ple ulate Die ack ge 64

Figure 7: Red force “Combo” tactic for Embargo scenario (DESE Viewed In GOLor) asf s0% aodud ond Bae eee deed lee 65

Figure 8: Red force “All Small” tactic for Assured Access sceriario:. (best viewed in Color) ..cs.cabweeewun ee ees 65

Figure 9: Red “All Big” tactic for Assured Access scenario (DeSb Vie weGsi COLOR)! 6 vic. dies BE oy ot hie's wt Dag ew ig weer de 66

Figure 10: Red “Combo” tactic for Assured Access scenario (Best Viewed), 2h COLOR) es 9 oe ao aw ceo ae Sites a oahe ea 67

Figure 11: Red “All Six” tactic for Assured Access scenario (beste VLewed “2 vO LOE )io 25 6 aie iatel ang Sine bee 8 ed eRe ee BUCA, Ee Be ae 67

Figure 12: Blue force “Barrier” tactic for Embargo scenario

(best viewed san.) COLOG) 6 sb 28 le tee kes ete bed ols a We ek hed es ee 70 Figure 13: Blue “Barrier” tactic for Assured Access scenario. (best“viewed’ in. Color) iii. dee soe jee ee Sl iowa os 71

Figure 14: Average Time to First Classification on the COP for Embargo scenario with Blue force using "TSP" tactic and Red force using "Combo" maneuver (best viewed in COLO) soc bte Sate e Sia ee Bieta eR 8 te Beaee tens, 6 Agere tae eee Sueoe te Bee. ek eae 77

Figure 15: Box and Whisker plot of Average Time to First Enemy Classification on the COP for Embargo scenario with Blue "TSP" tactic versus Red "Combo" maneuver (best WleWweR At: -COLOU) & wna: own curse ae 5 ete ag sa hate phe ee ees 79

Figure 16: Average Time to First Enemy Classification on COP for the Embargo scenario with Blue "TSP" tactic (DES>: Viewed: An COLOE)¢ 2 sd ae oe Seles uk MEER eS PES Re 82

Figure 17: Average Time to First Enemy Classification on the COP for Embargo scenario with Blue "Barrier" tactic (best. viewed in CoOlOYr) ..cssees a0 ad ee eR we we ew ow 84

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Figure 18: Average Time to First Enemy Classification by any UAV for Embargo scenario with Blue "TSP" tactic (DES Viewed (1m COLOr) a. a 65 = wet ala oe Rohan Se suka ee eRe 85

Figure 19: Average Time to First Enemy Classification by any UAV for Embargo scenario and Blue "Barrier" tactic (Desi “Viewed: all COLOG): Sacc spdieis ate she ae 3 ohne Pe wae eee dees 87

Figure 20: Average Locations of Enemy Classifications by any UAV for Embargo scenario with Blue "TSP" tactic (Desc viewed An COLOE) o2oi6 oo te eGed e Gk Eee S RS ESE SS 88

Figure 21: Average Locations of Enemy Classifications by any UAV for Embargo scenario with Blue "Barrier" tactic IDES VVewed) -1n COL G2 one 5 sa en a a a te tera by dS eave lea wa aw oe 89

Figure 22: Average Time to Second Enemy Classification by any UAV for Embargo scenario with Blue "TSP" tactic (Dee EV ewes aa G6 LOO) aires caja ie pd de pve aw I Soe ae penis ow we 911.

Figure 23: Average Time to Second Enemy Classification by any UAV for Embargo Scenario with Blue "Barrier" tactic

(DESc vrewed. 10 COLOE) 4 ose bees sects kGe} eed ee ees ewe 92 Figure 24: Average Proportion of Missed Enemy Classification for Embargo scenario with Blue "TSP" tactic (best. viewed in. CoOlOY) 1 iv ceiw ao iw ue dw eee weeks 93 Figure 25: Average Proportion of Missed Enemy Classifications for Embargo scenario with the Blue "Barrier tactic: (best viewed: 1n- COLO) eo. eu eee Sek wx 95

Figure 26: Average Proportion of Time Enemy is Positively Identified for Embargo scenario with Blue "TSP" and Red "Combo" maneuver scheme (best viewed in color)........ 97

Figure 27: Average Proportion of Time Enemy is Positively Identified for Embargo scenario with Blue "Barrier" and

Red "Combo" maneuver scheme (best viewed in color)... 98 Figure 28: Average Proportion of Time Neutrals are Positively Identified in Embargo scenario with Blue "TSP" and Red "Combo" maneuver scheme (best viewed in CON OT hs. to nsg 50 ee a Stee 5 on Sr Sa at tas Se et Ea At Batt en er GA ae ot, toe 99 Figure 29: Average Proportion of Time Neutrals are Positively Identified in Embargo scenario with Blue "Barrier" and Red "Combo" maneuver scheme (best viewed META EO MOTE) geet chess be ah Seed che Sw baes coe sat Stet ede Rb nGes She ask tle dena Seca de en thee deh abetiede nn Sal eee 99

Figure 30: Average Proportion of Time Fishing Vessels are Positively Identified in Embargo scenario with Blue

"TSP" and “Barrier” tactics versus Red "Combo" maneuver scheme (best viewed in color) ......... 0.0.0... ce ee eee 100

Figure 31: Average Time to First Enemy Classification on the COP in Assured Access scenario with Blue "TSP" and Red "All Small" maneuver scheme (best viewed in color) Sig hak Busse ly Sense ds alee Saige wah ae Pat eS SOE ae oe end 1s SBh eee Pat Se went ean So Me senes See aus 102

Figure 32: Box and Whisker plot of average time to first enemy classification on the COP in Assured Access scenario for Blue "TSP" tactic and Red "All Small" maneuver scheme (best viewed in color) .............. 104

Figure 33: Average Time to First Enemy Classification on the COP for Assured Access scenario with Blue “TSP” tactic versus all types of Red maneuver schemes (best ViLewed. 22 COlOr) 2 obey. be os ete me he ee PER Ee eb we eee 107

Figure 34: Average Time to First Enemy Classification on the COP in Assured Access scenario with Blue "Barrier" tactic versus all types of Red maneuver schemes (best Viewed.<in GCOLOL): og eee hee ee bg CS eee de wees 108

Figure 35: Average Locations of Enemy Classifications for Assured Access scenario with Blue “TSP” tactic (best nF a 5111 UE aC ot © pl Ef cgp ae ae ne ene 109

Figure 36: Average Locations of Enemy Classifications with

Blue "Barrier" tactic (best viewed in color)......... 110 Figure 37: Average Proportion of Missed Enemy Classifications for Assured Access scenario with Blue "TSP" tactic (best viewed in color)...............0.. 112 Figure 38% Average Proportion of Missed Enemy Classifications for Assured Access scenario with Blue "Barrier" tactic (best viewed in color)............. 113

Figure 39: Average Proportion of Time Enemy is Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Small" maneuver scheme (best viewed EA MHOOLOT )h tate cle sue Oeste wae Gul le al wie Mu ae GN ae Nahe eal ae eels 115

Figure 40: Average Proportion of Time Enemy is Positively Identified in Assured Access scenario with Blue "Barrier" tactic and Red "All Small" maneuver scheme (best. viewed: tn COLOL) eaten clad d fa Ok ol ANd ed BA eas 116

Figure 41: Average Proportion of Time Enemy is Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Big" maneuver scheme (best viewed in COLOL): ais ste tae es wi aes ee aM DG nda fa ion hig en sd Sale Be ah inane eo ae Sy ads 117

Figure 42: Average proportion of time Enemy is Positively Identified in Assured Access scenario with Blue "Barrier" tactic and Red "All Big" maneuver scheme (best WiLEWEC “Ail, WOLOR) 5 <-1.c-a0e Tah eae ed a eae Re Te Meee ds ee es 118

Figure 43: Average Proportion of Time Enemy is Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Six" maneuver scheme (best viewed in COLO) saith Go iON ils Cesc neice he cal Aen gee aca Muah teal ain naa ge dg 119

Figure 44: Average Proportion of Time Enemy is Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Six" maneuver scheme (best viewed in COMO) +s. 6 De ois bah AR AR A He AEE Ce AR bod 120

Figure 45: Average Proportion of Time Fishing Vessels are Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Small,” “All Big,” and “All Six” maneuver schemes (best viewed in color) ...121

Figure 46: Average Proportion of Time Fishing Vessels are Positively Identified in Assured Access scenario with Blue "TSP" tactic and Red "All Small,” “All Big,” and “All Six” maneuver schemes (best viewed in color) ...122

Figure 47 Average Time to First Enemy Classification as BAMS Cumulative P(Classification) Increases for the Embargo scenario with Blue "TSP" tactic and Red "Combo" maneuver scheme for the BAMS alone UAV combination (DESE: Viewed: aT VNCOLOR) Wars s cial ae thar sed eh Oe Me be oe ide eee 124

Figure 48: Average time to first enemy classification as BAMS cumulative P(Classification) increase for the Embargo scenario with Blue "TSP" and Red "Combo" tactic for BAMS plus additional VTUAVs (best viewed in color) bcoatiw td Bis vee, Sow ley davies Ie esl ol de BUR ee ee SSDS Bee aly Ae eed rn My dE fo aepe aece 125

Figure 49: Average Proportion of Time Enemy 1 is Positively Identified as BAMS Cumulative P(Classification) Increases in Embargo scenario with Blue “TSP” tactic and Red “Combo” maneuver scheme (best viewed in color) .. 126

Figure 50: Difference in Average Proportion of Time that Enemy 1 and Enemy 2 are Positively Identified as BAMS

Cumulative P(Classification) Increases in Embargo scenario with Blue “TSP” tactic and Red “Combo” maneuver scheme (best viewed in color) .......... 0.0... 0.0002 eee 127

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LIST OF TABLES

Table 1: GHMD Characteristics (NAVAIR 5.1.1, 2004) ....... 13 Table 2: VTUAV Characteristics (Klingbeil, 2004) ......... 15 Table 3: Some of the variables involved in UAV MOE analysis

ai ae eS Sl ees Pe eee Pe eee ee Re a ee ch dead 29 Table 4: Some of the variables involved with UAV flight PLOEDTSS: 5.0, crim a. eis ee aaah OS he eG Sere ag Ba, & ree a eee 29 Table 5: Experimental Set-up ......... eee eee 62 Table 6: Probabilities of Classification for BAMS UAV.... 73

Table 7: t-test Results for BAMS plus one VTUAV versus BAMS plus: ‘two: VIVAV Siocon eB eae Ee Be ie Be a ec ae 80

Table 8: t-test between BAMS plus two VTUAVs and BAMS plus ENLES. VIUAVS ie suite sie SR Suerte ay ew eels Bie Se See ote a Se Huet! Se uaa 81

Table 9: Diminishing returns with the addition of more VIUAVs with regard to the time Fishing vessels are positively identified ........ ee ee ees 101

Table 10: t-test between BAMS plus three VTUAVs and three VTUAVs alone in Assured Access scenario with Blue "TSP" tactic and Red "All Small" maneuver scheme............. 105

Table 11: t-test between BAMS plus two VTUAVs and BAMS plus three VTUAVs for the Assured Access scenario with Blue "TSP" tactic and Red "All Small" maneuver schemes...... 106

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LIST OF ABBREVIATIONS, ACRONYMS, AND SYMBOLS

BAMS BDA C2 CCOL CFEC COL CONOPS COP CSG EO EO/IR ESG FNF GHMD HALE

Broad Area Maritime Surveillance Battle Damage Assessment

Command and Control

Critical Contact of Interest Combined Fleet Forces Command Contact of Interest

Concept of Operations

Common Operational Picture

Carrier Strike Group Electro-optical Electro-optical/Infrared Expeditionary Strike Group

Fire and Forget

Global Hawk Maritime Demonstration High Altitude, Long Endurance Indications & Warning

Infrared

Irreducible Semi-Autonomous Adaptive Combat

Inverse Synthetic Aperture Radar

Intelligence Surveillance and Reconnaissance Joint Requirements Oversight Council

Joint Task Force

Littoral Combat Ship

Line of Sight

Launch and Recovery Element

Map Aware Non-uniform, Automata

Mission Control Element

Maritime Interdiction Operations

Maritime Moving Target Indicator

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MNS Mission Needs Statement

MOE Measure of Effectiveness

MPRF Maritime Patrol and Reconnaissance Force MS Maritime Surveillance

MTA Maritime Targeting Acquisition NAVAIR Naval Air Systems Command OPAREA Operational Area

O&S Operations and Support

OR Operations Research

SA Situational Awareness

SAG Surface Action Group

SAR Synthetic Aperture Radar

SEA-5 Systems Engineering Group SLOCs Sea Lines of Communication

Surface Search and Control

a (Surface Surveillance Coordination) Suw Surface Warfare

TACMEMO Tactical Memorandum

TACON Tactical Command

TACSITS Tactical Situations

TCS Tactical Control Station (for VTUAV) TDSI Temasek Defense Systems Institute TSC Tactical Support Center (for GHMD) TSP Travelling Salesman Problem

TTP Tactics, Techniques and Procedures UAVs Unmanned Aerial Vehicles

USAF United States Air Force

VTUAV Vertical Take-off Unmanned Aerial Vehicles

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EXECUTIVE SUMMARY

This research analyzes the effective use of multiple unmanned aerial vehicles (UAVs) for the Navy’s Surface Search and Control (SSC) mission. In the future, the Navy hopes to leverage the capabilities of a family of UAVs to provide increased situational awareness in the maritime environment. This family of UAVs includes a Broad Area Maritime Surveillance (BAMS) UAV and Vertical Take-Off UAVs (VTUAVs). However, the exact concepts of operations (CONOPS) that these assets will employ have yet to be determined. Questions exist about the best number of UAVs, types of UAVs, and tactics that will provide increased capabilities. This study presents some answers to these questions through analysis of results obtained with an agent-based model.

A software program called MANA (Map Aware Non-uniform, Automata) serves as the conduit for this study's agent-based simulation. The simulation models BAMS as a high altitude, long endurance UAV with a long radar detection range. VTUAVs are modeled as “pouncers” that can birddog enemy vessels once they are classified.

Two different scenarios are modeled based upon four of the Naval Air Systems Command (NAVAIR) approved tactical Situations (TACSITS) for the Navy’s precursor to BAMS

called Global Hawk Maritime Demonstration (GHMD ) (See Appendix). The first scenario is called “Embargo” and it simulates a Maritime Interdiction Operations (MIO) mission in which an enemy force is smuggling goods. The

second scenario is called “Assured Access” and it simulates

a friendly force entering a gulf-like region through a

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strait. Both scenarios model over 10,000 square nautical miles of coastal environment with dense shipping traffic and sparse enemy contacts.

Data are collected on almost 20,000 runs of the simulation in both scenarios, with different combinations of UAVs, friendly force tactics, and enemy force maneuvers. Friendly tactics involve a change in BAMS’ movement algorithm from a traveling salesman problem (TSP) solution to a “Barrier” search along specific waypoints. Red force maneuvers involve different routing. Data from the runs allows for analysis on when, where, and how long the friendly force classifies enemy ships.

There are four primary findings in this study. Of course, each finding is in the context of the scenarios modeled.

The first two findings pertain to the most effective numbers of UAVs. For the scenarios chosen, the best combination of UAVs is the Broad Area Maritime Surveillance (BAMS) UAV and two to three Vertical Take-Off UAVs (VIUAVs) . However, small numbers of VTUAVs can do just as well, if not better, when they operate without BAMS versus when they operate with BAMS. Both of these results are in terms of the lowest amount of time until first enemy classification.

The third finding deals with the most effective type of UAVs. Combinations of multiple UAVs that include BAMS tend to have advantages over those combinations without BAMS. These advantages include less average numbers of missed classifications and an increase in the proportion of

time that all types of contacts are positively identified.

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The fourth finding deals with the best UAV tactics to employ. The study shows that the tactics that BAMS employs do not usually make that much of a difference. This is, in large part, due to its long detection range—i.e., no matter what its search pattern is, BAMS detects all surface contacts in the operational area.

These findings lend themselves to operational recommendations about the numbers of UAVs, types of UAVs, and UAV tactics to employ in the maritime SSC environment.

In terms of numbers, investments in more UAVs are warranted, but should not be overblown. More UAVs certainly seem to provide more operational capability, but there is a point of diminishing returns at the two or three VTUAV point. A strong recommendation is to equip naval forces in scenarios similar to those modeled with enough capability that at least two VTUAVS can be operated at all times.

In terms of future UAV types, this study may or may not validate the operational requirement for a BAMS UAV. Poorer performance of combinations with BAMS and less VTUAVs diminishes the importance of BAMS as a force multiplier. However, the effectiveness of BAMS with higher numbers of VTUAVs advocates the use of BAMS. In addition, BAMS’ benefits in terms of reducing the number of leakers, and providing overall coverage, may outweigh all other results. A valid recommendation is to pursue the procurement of BAMS, but to augment it with at least two other cooperative VTUAVs.

Finally, in terms of tactics, this study suggests that with respect to BAMS, tactics are less important than the presence of BAMS itself. For the most part, results with

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changes in both enemy and friendly tactics seem to provide Similar results. A valid recommendation is to emphasize Studies with other scenarios to see if this is always

the case.

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ACKNOWLEDGEMENT

Professor Lucas, thanks your steadfast advice, academic guidance, and complete patience with me in this endeavor.

LCDR Gottfried, thanks for your operational expertise, unswerving confidence, and critical evaluations. The Navy is losing one of its most valuable leaders with your retirement.

Special appreciation goes to Lloyd Brown, Steve Upton, and the Project Albert Team for their inordinate amounts of time and energy dedicated to this project.

Thanks also to my colleagues in the Temasek Defense Systems Institute (TDSI) program. T’1ll always cherish our time together in Singapore and Monterey. I consider you to be among my best of friends.

Finally, thanks to my family for their constant support, and to my wife for her complete acceptance of me. Lee, your devoted support and understanding gives me willpower every day. Thanks for being the best thing to

ever happen to me.

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I. INTRODUCTION

A. PROBLEM/NAVY INTEREST

The Navy plans to take advantage of Unmanned Aerial Vehicles (UAVs) to perform many of the tasks that its manned assets perform today. As the Expanded Concept of Operations for the Navy’s High Altitude Long Endurance Aircraft (HALE) states:

The evolution of the hostile surface-to-air and

air-to-air threat and their collective effectiveness against manned aircraft and Satellites can generate unacceptably high

attrition rates. Current systems cannot perform

these missions in a timely, responsive manner in

an integrated hostile air defense environment

without high risk to personnel and costly

systems. There is a need for a capability, which

can be employed in areas where enemy air defenses

have not been adequately suppressed, in heavily

defended areas, in open ocean environments, and

in contaminated environments. (Navy High

Altitude Long Endurance (HALE) Unmanned Aerial

Vehicle Expanded Concept of Operations, Draft 4,

2004, hereafter referred to as HALE CONOPS, 2004)

Although the complete replacement of manned systems with unmanned systems is an unreasonable expectation for the near future (SEA-5, 2004), the augmentation of unmanned systems into the Fleet is forthcoming. This is evidenced by the fact that future configurations for the Littoral Combat Ship (LCS) may substitute helicopters with Vertical Take-off UAVs (VTUAVs) (Burgess, 2004). The Navy has also shown interest in the development of a Broad Area Maritime Surveillance (BAMS) UAV in order to replace aging

land-based maritime search platforms. Within the broader

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context of the Surface Search and Control (SSC) mission, initial Navy doctrine also recommends roles for these capabilities in focused search and cooperative identification tasking (TM 3-22-5-SW, 2004).

The Fleet is the stakeholder for this research, and it has many questions about UAV implementation. There are questions about what “speed, altitudes, sensor package and line of sight” are most effective. As well as “what kind of footprint can we expect and are we talking solo, section (two), or division (four) ops?” (Olivarez, 2004) The U.S. Navy’s THIRD Fleet has asked, “Can we get a sampling of the Concepts of Operation (CONOPS) that describe how we'll employ UAVS in a maritime environment?” (Olivarez, 2004).

Thorough exploration of these issues can answer questions about UAV supportability for the Navy’s vision of the future (Clark, 2004). It is one question to ask about the proper mix of UAVs in order to be effective. It is another to see what tactics will ensure that effectiveness.

Currently, such tactics do not exist.

B. A PREVIOUS STUDY

To date, study into the tactics for multiple UAV

operations has been limited. In a focused study on tactics and optimized search patterns for UAVs, the Operations Research (OR) Team of the Temasek Defense Systems Institute (TDST) collaborated with the

Systems Engineering and Analysis Team 5 (SEA-5) in an attempt to analyze tactics for multiple UAVs. Using high-level UAV definitions and sensor capabilities, the

study compares sensor capabilities, tactics, and numbers of 2

UAVs in a given scenario. Specifically, it focuses on the detection and identification missions. The study points

out that:

The search and identification problem is easier if it is assumed that the picture of the search area (provided by the P-3 or other high altitude orbiting asset) is always available. If such an asset exists, then the UAV flight path problem essentially resolves itself into a “traveling salesman problem” . . . In this problem, the salesman is given a finite number of cities along with the cost of travel between each pair of them. The challenge is for the salesman to find the cheapest way to visit all cities and return to his or her starting point. This type of problem can be solved with optimization techniques such as linear programming. (Temasek Defense Systems Institute, 2004)

As a result, the study explores the case with no high altitude orbiting asset available. The study concludes that UAV tactics do matter. That is, the number of UAVs and the patterns that UAVs fly have a direct effect on the coverage area and probability of detection of contacts of interest (Temasek Defense Systems Institute, 2004).

This thesis examines multiple UAV operations as well, but it differs from the TDSI study in that it also examines the case where information is passed from a high altitude asset to smaller UAVs, which act more as “pouncers.” Although the “traveling salesman problem” mentioned above does apply to this situation, it is of limited use. It takes time for the high orbiting asset to detect all targets and to determine which targets are of critical interest. “Pouncer” UAVs must also spend a certain amount

of time at each contact of interest before they can move on

to other contacts. This thesis also reviews the case in 3

which there is a lack of “pouncers” and only the

high altitude asset is available.

Cc. KEY ISSUES AND CONCEPTS

It is possible to decompose the surface search UAV problem into two separate areas: detection and identification. The distinction between detection and identification is important because these tasks inherently involve many different aspects of surface search. Although both missions are related, each presents its own difficulties because they compete for resources, consume time, and require different assets (Temasek Defense Systems Institute, 2004). Also, an asset may not commence the identification mission until detection has been accomplished organically or by some other asset.

Traditionally, the Navy handles the missions of detection and identification with multiple assets under a broad mission called Surface Search and Control (SSC). At sea, surface detections are often made by long-range, land-based, maritime search aircraft such as the P-3C Orion. These aircraft extend the Fleet’s surface picture and provide an extended aerial view of all surface contacts. Shipboard watch-standers use the information from these assets to maintain the Recognized Maritime Picture (RMP).

The RMP is ‘about maintaining an unambiguous’) and timely database of the position and identification of all tracks, both warship and merchant, and being able to distinguish good or cleared ships from the adversary, unchallenged, suspect, or blockade running ships”

(Germain, 1997). The RMP helps to provide commanders with 4

a Common Operational Picture (COP). The COP allows “decision makers [to] have a more effective means of evaluating tactical situations through this common display of forces. This enhances the Joint Task Force (JTF) Commander’s ability to effectively exercise command and control of his battle-space and enables synchronized execution of forces” (SPAWAR, 1995).

If more information is needed on a certain contact in order to update the RMP and the COP, then the P-3C investigates that contact further, or perhaps another locally deployed asset is tasked to obtain more information. These deployed assets may include helicopters, such as the SH-60B, other jet aircraft, or surface ships.

In effect, commanders employ one long-endurance asset as the detection agent and other assets as “pouncers” in order to accomplish identifications. With limited assets, contacts, or compressed timelines, a single asset often performs both of these roles. In other words, the SH-60B that detects three surface contacts is the same one that investigates and identifies each of these three contacts in order to properly identify them. Whatever the case may be, all SSC assets work together to accomplish both the detection and identification tasking.

The Navy sees the BAMS UAV as an eventual replacement LOr the long-range P-3C eareratt in the SSG

mission since...

The land-based, manned airborne platforms that perform the broad area maritime and littoral Intelligence, Surveillance, and Reconnaissance (ISR) functions today are reaching the end of their service life and are facing possible

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reduced flight operations and subsequent near-term retirement. Airframe life issues, declining availability rates, high Operations and Support (O&S) costs and limited system growth capacity plague legacy MPRF [Maritime Patrol and

Reconnaissance Force] aircraft (P-3C). (Operational Requirements Document for Broad Area Maritime Surveillance (BAMS ) Unmanned Aerial

Vehicle, Draft version 3.0, DEC 03.

In addition, the Chairman of the Joint Requirements Oversight Council (JROC) signed a validated Mission Needs Statement (MNS) for a “Close Range and Long Endurance Reconnaissance, Surveillance, and Target Acquisition Capability” (JROC MNS 003-90, 1990).

To augment the JROC MNS, the Navy has decided to increase its emphasis on UAVs with “both a short-term plan to capitalize on existing systems and a longer-term plan to develop a family of unmanned vehicles” (HALE CONOPS, 2004). The short-term plan is called Global Hawk Maritime Demonstration (GHMD) and it is currently supervised by the Naval Air Systems Command GHMD Test and Experimentation Design Division, Integrated Systems Evaluation, Experimentation and Test Department. This program office

describes the Navy’s UAV plan as a two-phased process.

Phase I will be procurement of an Air Force production line Global Hawk system which will have modifications to the existing sensor package to make it more compatible with a maritime environment. A system will consist of two air vehicles with payloads, a launch and recovery element and mission control element. The system will be used primarily for experimentation and CONOPS development leading to Phase II. Phase II (now called BAMS UAV) will leverage from the

Broad Area Maritime and Littoral Armed Intelligence, Surveillance, and Reconnaissance Mission Needs Statement and Analysis of

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Alternatives to competitively acquire high altitude long endurance vehicles with robust and fully capable maritime sensor payloads. The thrust of BAMS UAV will be towards developing sensor/payload capability or identifying existing sensor/payloads capable of performing BAMS missions. (HALE CONOPS, 2004)

GHMD will be a system that “leverages United States Air Force (USAF) contracts to expeditiously procure a

robust UAV system” (NAVAIR 5.1.1, 2004). It will:

e Provide Navy Concept of Operations (CONOPS), Tactics Technigues and Procedures (TTP), and Experimentation for 24/7 ISR System

e Rapidly insert Persistent Intelligence Surveillance and Reconnaissance (ISR) UAV capability to the Navy

e Be an Enduring Test Bed e Develop/Gain Fleet user community advocacy e Address Naval transformational Roadmap initiatives

(e.g., Sea Trial) (NAVAIR 5.1.1, 2004)

In pursuit of the aforementioned longer-term plan to develop a family of unmanned vehicles, the Navy expects to equip the new Littoral Combat Ship (LCS) with VTUAVs, an example of which is the Fire Scout. The RQ-8A Fire Scout will augment the Fleet in order to facilitate the following

missions:

e Surface Search and Control (SSC)

e Birddog/tattletale operations

e Maritime Interdiction Operations (MIO) e Targeting

e Battle Damage Assessment (BDA)

(Klingbeil, July 2004)

In other words, stakeholders desire a VTUAV to act as the “pouncer” aircraft that can identify and closely monitor surface contacts of higher interest.

Together, the two types of UAVs—-BAMS and VTUAVs—are expected to work together to help accomplish the detection and identification missions for the Navy of tomorrow. However, the exact CONOPS and specific tactics that these assets will employ have yet to be determined. Questions about these CONOPS specifically include the number of UAVs required to complete the identification mission, tactical dependencies on BAMS and VTUAV availability, and tactics selection. This thesis addresses these issues. ie analyzes the performance characteristics of both the BAMS and VTUAVs to gain insight into whether and how they should work together in the SSC role, in a variety of scenarios.

The number of UAVS needed to complete the identification mission is dependent upon the size of the search area and the sweep-width of UAV sensors (Washburn, 2002). However, operations with increased numbers of UAVs may be more complicated with an increased requirement for airspace separation and coordination. There may also be some point of “diminishing returns” when the marginal benefits of adding another UAV, in terms of the time from detection to identification or the proportion of time in which all contacts are positively identified, are outweighed by the cost