Capstone Concept for Joint Operations (CCJO) Delivering Scalable and

Tailorable Effects Weapons (STEW)

Program Goal – develop, integrate and test capabilities to deliver scalable and tailorable weapon effects to match urban combat targeting objectives, subject to constraints on acceptable collateral casualties

Why is this Darpa hard? Fog-of-war, concealed non-accessible positions, difficult cluttered sensing environment, intermixed combatant/non-combatant (Com/N-Com) populations, fleeting opportunities, compressed battlespace/timelines

Technology Objectives (Thrust Areas) Accurate, precise, real-time discrimination between

Com/N-Com presence in the weapon effects zone Structure-penetrating discrimination systems Controllable release, direction and application of a

mix of weapon effects Autonomous or semi-autonomous weapon

behaviors, decision making

State-of-art (Current practice) How is it done today? ISR/targeting/weapon kill-

chain: Fuse ISR + tactical intelligence + SIGINT/COMINT/HUMINT →C2/FDC nodes → strike platforms, indirect fire support, drones

Current limitations? Inaccurate/unreliable discrimination, long standoff ranges, latency contributing to missed opportunities

New Approach (Key enablers) What is different and why will it be successful? Focus on specific discrimination signatures (not general purpose sensing, imaging, recognition) Apply structure penetration technologies to enhance sensing proximity and discrimination Extend kill chain process to the “last meter” to maximize tactical opportunities, minimize collateral casualties

What are the expected outcomes if program succeeds?

Agile, flexible tactical decisions Effective application of firepower Denial of urban safe havens to enemy

combatants Minimize collateral casualties

What are the risks? Affordable engineering of structure-

penetrating delivery systems Survivability of discrimination sensors Dispersal sub-systems

Technical risks Effective discrimination technologies Achieving scalable and tailorable

weapon effects

Mixed Combatant and Non-Combatant Populations

Inaccurate Discrimination of Combatant/Non-Combatant Presence

Avoidable Collateral Casualties

NGO estimates of collateral casualties Iraq – 133,000 killed Afghanistan – 21,000 killed Pakistan – > 20,000 killed Gaza 2014 conflict – 1,800 killed,

approximately 10,000 wounded

ISR surveillance and ground intelligence assets provide insufficient and stale information

Drones and strike assets lack discrimination capabilities

Tactical time windows are narrow, decision timelines are compressed

Notional Operational Scenario and Timelines

• (Phase 1) Initial assessment of collateral casualties in the weapon effects zone • (Phase 2) Collection of proximity discrimination signatures • (Phase 3) Weapon release and flyout • (Phase 4) Autonomous weapon control • (Phase 5) Follow-up courses-of-action

Phase 1 – Initial ISR + intelligence assessment A multi-story residential building in an urban zone is under surveillance. Enemy presence in the building has been detected and the building has been selected for the candidate target list. Intelligence reports and tactical data indicate high probability of civilian presence including families with children. One possibility is that the civilians are mostly confined to the lower levels and basement while the enemy conducts operations from the rooftop and upper level vantage points. Surveillance indicates temporal patterns to the enemy operations. Collateral casualty modeled estimates are judged acceptable if a strike is launched when enemy forces are concentrated at levels and rooftop.

Phase 2 – Collection of discrimination signatures At T=XXXX hours, airborne video indicates the beginning of enemy movement as the standing watch is relieved. A call for fire is issued and at T+x (seconds), multiple KIP/DSC arrivals penetrate the building walls and upper floors. Clusters of sensors are dispersed through the upper levels but no structural damage is caused. The KIP/DSC sensors collect acoustic and motion detection data and form an ad-hoc network. Simultaneously, a PG/DSC package is launched from the airborne asset to arrive at the target within y seconds of the initial KIP impact. The PG/DSC package deploys over the building rooftop suspended by an altitude-position controlled balloon. The PG/DSC package includes video sensors and a datalink relay to the KIP/DSC sensors.

Phase 3 – Weapon release and flyout A Scalable/Tailorable Effects Weapon (STEW) is launched at T+x+y+z, with time of impact estimated at T+x+y+z+l. The STEW command processor assumes weapon control at T+x+y+z+l-δ

Phase 4 – Autonomous weapon control At T+x+y+z+s (where l-δ < s < l), the uplinked acoustic data reveals signatures correlating to an infant and a woman. The weapon command processor safes the arming circuit and redirects the weapon to a nearby secondary target.

Phase 5 – Follow-up course-of-action The STEW command processor computes the new impact time and checks for any available discrimination information regarding the secondary target. There is insufficient information to achieve a high confidence assessment of collateral casualties. The STEW processor issues a self-destruct command.

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Assumptions Discrimination information is geo-referenced with common time

base Discrimination information is low dimensional, e.g. based on

presence or absence of pre-specified signatures, features or patterns

Discrimination information can be applied to confirm, refine or downgrade existing high probability hypotheses, generated from other information sources

Useful discrimination information requires near proximity to sources

Discrimination information value decays rapidly over time Use Cases

Refine presence of non-combatants Presence of high risk populations, e.g. children, women

Downgrade presence of combatants Absence of combatant activities, uniforms. gear, weapons

Confirm separation of combatants from non-combatants in target zone Localization of non-combatants outside target zone, absence of non-

combatant activities in target zone, presence of combatant activities/weapons/uniforms/gear in target zone

Key Assumptions and Use Cases

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A Survey of Human Sensing Methods (Texeira, Dublon, Savvides; ACM Computing Surveys)

Discrimination Modalities and Signatures

Arm and hand gestures from WiTrack data (Fadel Adib, Zachary Kabelac, Dina Katabi, Robert C. Miller; MIT)

Activity signatures

Key-frame poselet activity recognition (Michalis Raptis, Leonid Sigal; Disney Research, Pittsburgh)

Disrimination Modality Signature(s) Confidence Proximity Sensing

Count Biophysical, thermal, chemical High 3 - 5 metersInfrared, bolometric, CO2, humidity

Localization Motion, range/depth Moderate 3 - 5 meters RFActivities Motion, gesture,

acoustic, vibration featuresModerate 3 - 5 meters RF, Acoustic/VLF

Age Voice/speech features Moderate 3 - 5 meters AcousticGender Voice/speech features Moderate 3 - 5 meters AcousticNon-combatant objects Image/spectral features,

range/depthModerate

5 - 8 meters Optical, RF

Combatant objects Image/spectral features range/depth

Moderate5 - 8 meters Optical, RF

Non-combatant presence Image/spectral features Low 5 - 8 meters OpticalCombatant presence Image/spectral features Low 5 - 8 meters Optical

Biometrics Very Low < 1 meter MMW, ultrasound

Feature signatures

Multispectral measurements of camouflage uniforms (Institute of Optoelectronics)

Time-frequency plot of baby crying (Erik Gustafsson, Florence Levréro,David Reby & Nicolas Mathevon, Nature Communications)

N. T. N. Tho, S. Zhao, and D. L. Jones, “Robust DOA estimation of multiple speech sources,” (ICASSP 2014),

Sensor System Common Requirements Survivability, acceleration/shock hardening, vibration

compensation Internal power source Self-locating and self-orienting services Communication and networking services Autonomous processing core

Front end : signal conditioning/signal processing Feature extraction, pattern recognition Discriminant analytics Sensor control and management

Examples Panoramic (4π sr) camera ball Miniaturized microphone arrays Metal-oxide olfactory sensor module

Discrimination Sensor Packages

Kinetic impact penetrators Metal (tungsten) alloy Liquid metal

Explosively formed penetrators – heavy masonry, multi-floor penetration

Precision guided single package – entry through windows, ingress/egress apertures, light structural barriers

Multi-stage penetrator with multiple dispersal packages

Examples of Structure Penetrators

Common STEW System Requirements Subsystems: Dual-mode seeker, Navigation (NAV), Guidance and

Control (G&C) , Command Link (CL) Autonomous Weapon Behaviors

Dynamic course-of-action (COA) decision making Terminal tracking, final impact adjustments Battle damage assessment (BDA) Selection of follow actions (e.g. 2 weapon leader/follower attacks) Weapon controller commands

Weapon Effects Controller Arming/safing, fuzing, self-destruct/self-inert Selection of effects (lethal, non-lethal) Control of release (timing, spacing, direction)

Controllable Lethal effects Multi-phase explosives, shaping, timing Tunable energy release (Dense Inert Metal Explosives) DARPA Controlled timed explosive jets (MAHEM) DARPA Reactive Material Structures (RMS) Anti-personnel – controlled fragmentation dispersal patterns

Non-lethal effects Neuro-muscular paralytics Incapacitating agents

Scalable and Tailorable Effects Weapon (STEW) Systems

CFD Simulation of directional jet formation from charge shaping and timing

Focused blast fragmentation warhead

Proposed Brimstone 2 Design – MBDA Inc.

Phase 1 – Demonstration Program Objectives

Define CONOPS Define system concepts and requirements Design / Integrate / Test prototype technologies

Discrimination Technologies Structure Penetration Delivery Systems Scalable and Tailorable Effects Weapon (STEW)

Demonstration of Prototypes Outcomes

Assess measures of effectiveness (MOEs) Down-select/prioritize technologies for further development Finalize CONOPS and SoS architecture Build DoD partnering relationships

Phase 2 – Advanced Concept Development Objectives

Complete (2) or more system concepts Operational testing of system concepts at DoD facility Finalize DoD MOU/MOA for further development and operational testing

Outcomes Validate operational effectiveness and suitability of system concepts Transition system concepts and technologies to DoD partners

Notional Program Roadmap