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Homing Missile Guidance and Control at JHU/APL
SAE Aerospace Control & Guidance Systems Committee Meeting #97 March 1-3, 2006 Uday J. Shankar, Ph. D. Air & Missile Defense Department ;
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Abstract This presentation discusses the GNC research at the Guidance, Navigation, and Control Group at the Johns Hopkins University Applied Physics Laboratory. Johns Hopkins University Applied Physics Laboratory (JHU/APL) is one of five institutions at the Johns Hopkins University. APL is a not-for-profit research organization with about 3600 employees (68% scientists and engineers). Our annual revenue is on the order of $670m. The Air and Missile Defense Department is a major department of APL involved with the defense of naval and joint forces from attacking aircraft, cruise missiles, and ballistic missiles. The major thrust of the GNC group is the guidance, navigation, and control of missiles. Our mission is to Integrate sensor data, airframe and propulsion capabilities to meet mission objectives. We are involved with GNC activities in the concept stage (design, requirements analysis, algorithm development), detailed design (hardware, software), and flight test (pre-flight predictions, post-flight analysis, failure investigation). The Advanced Systems section within the GNC group is involved with several projects: boost-phase interception of ballistic missiles, discrimination-coupled guidance for midcourse intercepts, Standard Missile GNC engineering, Kill Vehicle engineering, integrated guidance control, swarm-on-swarm guidance, and rapid prototyping of GNC algorithms and hardware. We discuss two examples. The first is the swarm-on-swarm guidance. This framework can be used to solve guidance problems associated with several missile defense scenarios. The second is the application of dynamic-game guidance solutions. This has applications in terminal guidance of a boost-phase interceptor and the discrimination-coupled guidance of terminal homing of a midcourse interceptor. We discuss in more detail the problem of terminal guidance of a boost-phase interceptor. The problem is formulated and a closed-form solution is offered. UJS-SAE
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Divisions of The Johns Hopkins University
School of Arts & Sciences Whiting School of Engineering School of Professional Studies in Business & Education School of Hygiene & Public Health School of Medicine School of Nursing Applied Physics Laboratory Nitze School of Advanced International Studies Peabody Institute UJS-SAE
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Profile of the Applied Physics Laboratory
Not-for-profit university research & development laboratory Division of the Johns Hopkins University founded in 1942 On-site graduate engineering program in 8 degree fields Staffing: 3,600 employees (68% scientists & engineers) Annual revenue ~ $ 670M UJS-SAE
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Air & Missile Defense Advancing Readiness & Effectiveness of US Military Forces
Key Programs: Cooperative Engagement Capability Ballistic Missile Defense Standard Missile AEGIS Area Air Defense Commander Ship Self Defense Critical Challenge 1: Defend naval & joint forces from opposing aircraft, cruise missiles, and ballistic missiles Critical Challenge 2: Optimally deploy & employ multiple weapons systems to maximize defense of critical assets such as military forces, civilian population centers, airfields & ports in overseas theaters & in the United States UJS-SAE
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GNC Group: Roles Concept Development Detailed Design Flight Testing
Integrate Sensor Data, Airframe and Propulsion Capabilities to Meet Mission Objectives Intercept the Target Maintain Stable Flight Ensure Seeker Acquisition & Track Minimize Noise and Disturbance Sensitivities GPS Other Sensors Target Motion Missile Seeker* Guidance & Navigation Solution Guidance Law Flight Control Airframe/ Propulsion Primary Responsibilities Missile Motion Cooperative Efforts Inertial Sensors Autopilot Loop Homing Loop * Primary responsibility for seeker dynamics and radome effects System concept trade studies GNC requirements analyses Algorithm research Real-time distributed simulation Concept Development Detailed Design Component modeling 6 DOF development & verification GNC algorithm development Stability analysis Flight control hardware testing Evaluation of missile electrical systems System performance analyses Distributed simulation Flight Testing Hardware-in-the-loop Preflight performance prediction Post-flight evaluation Failure Investigation UJS-SAE
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GNC Group: Current Efforts
Threat Launch Point Predicted Intercept Point Uncertainty Basket Radar Track Terminal Homing Optimize KV fuel usage Satisfy hit requirements Flyout Guidance Fixed-interval guidance Minimize KV handover errors despite highly uncertain PIP Intercept Point Prediction Uncertain boost profile and temporal events Boost-Phase Intercept Studies and GNC Algorithm Research RV, Booster, ACS, Jammer, Decoys, … Contain Likely RV Objects within FOV Maneuver to Keep Likely Objects Within Divert Capability Discrimination-Coupled Guidance Standard Missile SM-3 Development INS/GPS analysis Flight control improvements 21” Standard Missile SM-6/Future Missile Studies Inflight alignment GNC studies Flight Test 6 DOF replication Failure investigation Hardware fault insertion Engager Swarm Lethal footprint Sensor / detector element Asset Track Designate Swarm-on-Swarm Guidance and Control Research Expected benefit of employing cooperative missile swarms is increased performance robustness and mission flexibility SM-3 Kill Vehicle Flight test performance assessment ACS design options Advanced pintle 6 DOF, G&C design KV G&C Guidance Filter Law Autopilot Target Sensors Airframe / Propulsion Inertial Navigation Motion Missile Integrated Guidance & Control (IGC) via dynamic-game optimization ASCM CG CVN Mitigate Raid Attack Vulnerability via Cooperative Missiles CVBG (Raid) Defense G&C Real-time Implementation Remaining 6-DOF (real-time) Sensor Signals Fin Commands G&C Algorithms Airframe, Sensor & Environment Models Analysis Simulation (not real-time) Rapid Prototype Testbed Processor 1 Processor 2 PC or UNIX processor Rapid GNC Prototyping UJS-SAE
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Example GNC Research at APL
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Cooperative Multi-Interceptor Guidance
Threat Launch Point Threat Trajectory Uncertainty Modified Aegis Platform Multi-KV for BPI Manage Information Uncertainty via Increased Control Space Sea-Surface Asymmetric Adversaries (S2A2) Mini-Missiles Speedboat Attacker Swarm Short time to ID & negate threat Effect A Volume Kill Via Increased Control Space ASCM CG MaRV CVN Overhead Asset Mitigate Raid Attack Vulnerability via Cooperative Missiles CVBG (Raid) Defense Swarm-Guidance: Expected Benefits Eased centralized control requirements - Remove “chokepoints, delays, etc. Reactive flexibility / adaptation to threats Scalability (response insensitive to #s) Near-simultaneous swarm negation Minimize chaotic threat response to being engaged Rapid battle-damage assessment and 2nd-salvo response Swarm-guidance: Guide multiple cooperative missile interceptors to negate one or more incoming threats (“Swarm-on-swarm”) UJS-SAE
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Ballistic Missile Defense Challenges
Threat Launch Point Predicted Intercept Point Uncertainty Basket Radar Track Terminal Homing Optimize KV fuel usage Satisfy hit requirements Flyout Guidance Fixed-interval guidance Minimize KV handover errors despite highly uncertain PIP Intercept Point Prediction Uncertain boost profile and temporal events Notional Sea-Based Boost-Phase Intercept Scenario Boost-Phase Intercept Challenges Compressed timelines Uncertain threat trajectory, acceleration, staging events and burn-out times Interceptor TVC has fixed maneuvering time ending before intercept occurs Kill vehicle fuel and g limitations Predicted Intercept Point Uncertainty Basket Terminal Guidance Contain likely objects within FOV Volume / object commit Maximize containment Flyout Guidance Cluster / volume commit PIP refinement / IFTU Energy / pulse management Engageability / launch solution Predicted intercept point (PIP) Terminal Guidance - End Game Aimpoint Selection Satisfy Hit Requirements Midcourse-Phase Intercept Challenges Complex threat cluster(s) act to postpone identification of the lethal object Discrimination quality improves with time Divert capability decreases with time Guidance must generate acceleration commands prior to localization of lethal object Notional Midcourse-Phase Intercept Scenario Information uncertainty coupled with time and kinematic limitations pose substantial challenges to ballistic missile defense UJS-SAE
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Boost-Phase BMD: Terminal Homing
Improve guidance law zero-effort-miss estimation accuracy This improves KV V and g-efficiency Assume that the threat acceleration increases linearly Improve on the APN concept versus a boosting threat Solve a dynamic-game (DG) optimization formulation DG framework provides robustness to threat acceleration uncertainty Couples the control components of the guidance problem to estimation and prediction quality Control is less sensitive to threat acceleration uncertainties Accommodating threat burnout Employ a burnout detection cue (from the seeker) Use in estimation and guidance algorithms Derive closed-form solutions Prefer closed-form solutions to numerical solutions UJS-SAE
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BPI Terminal Guidance Solution
Terminal Miss Control Uncertainties Terminal Miss Performance Weight Estimation Uncertainty Control Riccati Equation Solution General structure of the control solution Dynamic Game Filter Guidance Law Relative Position Relative Velocity Threat Acceleration Threat Jerk UJS-SAE
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Thank You! UJS-SAE
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