SBIR-STTR Award

The space community has, over the course of the past several years, performed research into Space Situation Awareness (SSA). As SSA and reasoning technologies advance, SSA has become a central factor in identifying and responding to space threats. The ISS Team proposes to advance SSA capabilities through the development of predictive SSA technologies. The objective of the proposed Space Situation Awareness via Predictive Intelligent Reification of multi-INT Threat-models (SPIRIT) effort is to develop a collaborative SSA fusion capability that provides identification of and predictive insight into both deliberate hostile actions and environmental threats facing space assets. We propose a multi-stage fusion system in which the first stage monitors low-level data and relevant JMS feeds using threat and normalcy models. Activation of these models triggers stage two which leverages semantic web technologies to facilitate automated discovery of inter-entity relationships including spatiotemporal and contextual relationships from sources including structured, semi-structured, and unstructured text. Stage three leverages these semantically enriched products to perform predictive threat characterization using threat COA and impact assessment models. Partial evidence and uncertainty will be managed through fuzzy logic and probabilistic reasoning. Through this multi-stage process, SPIRIT’s predictive threat characterization will enable timely development of effective countermeasures.

Benefit:
SPIRIT will provide an extensible framework for supporting SSA in a net-centric environment that will be compatible with the upcoming Joint Space Operations Center Mission System (JMS) SOA architecture. Using a federation of normalcy, threat, and COA models, the multi-stage SPIRIT system will be able to rapidly identify and characterize threats, be they intentional or natural. Consuming streaming multi-INT data as well as open source text, the semantic enrichment capabilities of SPIRIT along with its multi-logic reasoning system will support predictive awareness of emerging threats from partial evidence, enabling timely threat identification and development of effective countermeasures. Although initially developed to support SSA, the SPIRIT framework could be adapted to support new domains given appropriate domain theories and models. The initial commercial applications of SPIRIT include SSA and DCS systems such as JMS.

Keywords:
Space Situation Awareness, Information Fusion, Formal Methods, Ontology, Event Processing, Service Oriented Architecture

The objective of the proposed Space Situation Awareness via Predictive Intelligent Reification of multi-INT Threat-models (SPIRIT) effort is to develop a real-time, multi-INT SSA fusion capability that provides predictive insight into both deliberate and environmental threats facing space assets. A key enabler of this capability is the application of semantic web technology towards the enrichment and fusion of multi-source observations. In Phase I of this SBIR the ISS team successfully demonstrated several powerful capabilities including: a capability to extract, semantically tag, and temporally align knowledge from unstructured data sources; how to extend semantic web technologies with temporal and probabilistic reasoning in support of multi-INT fusion; and how learned multi-INT indicator models can be applied towards predictive SSA. The primary objective of Phase II of this effort are to mature the functional prototypes developed under Phase I into a comprehensive JDL level 2/3 fusion service capable of supporting real-time, multi-INT predictive SSA within the JSPOC Mission System (JMS). In addition to a significant software engineering effort, SPIRIT Phase II also includes significant research into several challenging problems including semantic based fuzzy membership functions, multi-INT entity disambiguation, and assigning confidence to knowledge extracted from unstructured text.

Benefit:
SPIRIT will provide an extensible framework for supporting SSA in a net-centric environment that will be compatible with the new Joint Space Operations Center Mission System (JMS) SOA architecture. Using a federation of normalcy, threat, and COA models, the real-time, multi-INT SPIRIT system will be able to rapidly identify and characterize threats, be they intentional or natural. Consuming streaming multi-INT data as well as open source text, the semantic enrichment capabilities of SPIRIT along with its multi-logic reasoning system will support predictive awareness of emerging threats from partial evidence, enabling timely threat identification and development of effective countermeasures. Although initially developed to support SSA, the declarative knowledge framework can be adapted to support new domains with minimal if any software programming. The initial commercial applications of SPIRIT include SSA and DCS systems such as JMS.

Keywords:
Space Situation Awareness, Information Fusion, Formal Methods, Predictive Analysis, Semantic Web, Event Processing, Temporal Reasoning, Service Oriented Architecture