Space Domain Awareness
Success Stories
SHERLOC
Produces real-time threat assessments for space domain awareness (SDA) using probabilistic reasoning from multi-source information ranging from sensor data and pattern-of-life analytics to open source intelligence.
VIRSA
VIRSA is initially focusing on two specific skills: Summary and Keyword search. These two initial skills fill known information needs and provide a solid foundation for VIRSA; the number and variety of skills exhibited by VIRSA will continue to grow as the DARPA Hallmark program progresses.
TRACER
Provides an integrated set of data management, task management, analysis, and data visualization capabilities. These capabilities improve space situational awareness, reduce manpower requirements, dramatically shorten EMI response time, enable the system to evolve without programmer involvement, and support adversarial scenarios such as jamming.
RAPTOR (RFI Detection and Prediction Tool)
Provides better-quality schedules, faster scheduling, and the ability to handle larger, more complex sets of requests. RAPTOR negotiates resolution of conflicts in an automated or semi-automated manner and performs far-future and automatic abnormal real-time scheduling signal detection and prediction.
SSN Scheduling
Scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. Is able to schedule more observations with the same sensor resources and have those observations be more complementary.
RF-IR Data Fusion for Space Object Classification Using Human-Quality Artificial Intelligence Techniques:
In a recent effort, Stottler Henke used low-level pixel processing techniques to process actual infrared and radar images for better correlation, classification, and… read more