Description:
OBJECTIVE: This Topic seeks research and development of innovative planning algorithms toward improving sensor coordination of a hybrid Aegis BMD System. The result of this effort should be adaptable planning algorithms that recommend options for optimizing Ship Operating Area (SOA) toward defending a given area against a missile raid (multiple targets). Research should include, but not be limited to, exploring concepts of advanced learning, sensor coordination and adaptive applications (i.e., Bioinspired algorithm for managing the sensor resources, Information-Based Decision Making and others) DESCRIPTION: Existing planners use sensor kinematic models together with selected geographic constraints that provide support in determining the placement/SOA for Sea-based assets. As more assets become available, and particularly in the case where some are Earth fixed and others are mobile, existing approaches need to become real-time adaptable and optimal. This becomes increasingly critical when these assets are planning for a coordinated raid of threats launched in close proximity and closely in time. As a result, the Missile Defense Agency (MDA) is seeking the development of novel, highly effective planning algorithms and associated models to provide optimal positioning solutions for a hybrid Aegis BMD system comprised of both land-based and sea-based assets. These algorithms must take into account operational constraints of each sensor asset type, and produce optimal yet adaptable Sea-based positioning solutions in real time. The focus should be on developing an adaptable planning algorithm that would optimize SOA when incorporating land based and mobile sensor sources to handle a raid environment (multiple targets). These new planning algorithms must be able to recommend sensor assets that minimize the number of required sensors for a given coverage, maximize the effectiveness of each sensor given its performance and resource constraints, and optimize the probability of successful engagements (Pes) for each Aegis BMD firing asset (whether land-based or sea-based). Generic Aegis BMD Data will be provided that will assist the small business in this effort. When a single sensor is tasked with collecting measurements on a single target, the management of the sensor's available resources does not pose any challenge. However, in situations where multiple sensors are directed to collect measurements on multiple targets, the decision process that determines which sensors to collect measurements on within a given area to cover can be difficult. The sensor coordination/management problem becomes more difficult as the number of targets relative to the number of sensors increases. The problem is further exacerbated when targets and sensors are not arranged in a favorable geometric position [1]. Innovative concepts and models should be explored and proposed that would optimize planning for engagement success. Things to consider toward developing these models are minimizing required sensor resources in a threat raid environment, minimizing the probability of target leakage and maximizing target raid annihilation. These models should potentially be applicable to other BMDS (Ballistic Missile Denfense System) weapon systems such as THAAD (Terminal High Altitude Area Defense), GMD (Ground-Based Midcourse Defense) and PATRIOT (Phased Array Tracking Radar to Intercept on Target). PHASE I: Develop noval planning algorithms for positioning sea-based assets, that includes adding land based sensor assets along with other mobile sensor assets, which is geared toward defending a given area against a missile raid (multiple targets). These algorithms should determine the optimal positioning of land-based and sea-based BMD assets such as generic S-band and X-band radars, interceptors of various capabilities, notional IR sensors and any required communication relays to cover a given defended area. Develop a proof of concept design; identify designs and test capabilities and conduct feasibility assessment for the proposed algorithms. Phase I work should clearly validate the viability of the proposed solution. Phase I should also result in a clear concept of operations document. PHASE II: Based on the results and findings of Phase I, utilize Aegis BMD assets as an intial testbed to develop the planning models that can provide calculated and graphical output of optimal placement for Aegis BMD assets. After development of the planning algorithms, exercise the models using real world data, including actual Aegis BMD asset characteristics. Planning algorithms should be scalable to other BMDS platforms such as GMD and THAAD. The Phase II objective will be to validate a new technology solution that MDA users and prime contractors can transition in Phase III. Validate the feasibility of the Phase I concept by development and demonstrations that will be tested to ensure performance objectives are met. Validation would include, but not be limited to, system simulations, operation in test-beds, or operation in a demonstration subsystem. The goal of the Phase II effort is to demonstrate technology solution viability. PHASE III: In this phase, the contractor will apply the innovations demonstrated in the first two phases to one or more MDA systems, subsystems, or components. The objective of Phase III is to demonstrate the scalability of the developed technology, transition the component technology to the MDA system integrator or payload contractor, mature it for operational insertion, and demonstrate the technology in an operational level environment. COMMERCIALIZATION: The contractor will pursue commercialization of the various technologies and models developed in Phase II for potential commercial uses in such diverse fields as air traffic control, weather systems, and other tracking applications.
