The domain of Geospatial Intelligence Analysis is rapidly shifting toward a new paradigm of Activity Based Intelligence (ABI) and information-based Tipping and Cueing. General requirements for an advanced ABIAA system present significant challenges in architectural design, computing resources, data volumes, workflow efficiency, data mining and analysis algorithms, and database structures. These sophisticated ABI software systems must include advanced algorithms that automatically flag activities of interest in less time and within larger data volumes than can be processed by human analysts. In doing this, they must also maintain the geospatial accuracy necessary for cross-correlation of multi-intelligence data sources.
Historically, serial architectural workflows have been employed in ABIAA system design for tasking, collection, processing, exploitation, and dissemination. These simpler architectures may produce implementations that solve short term requirements; however, they have serious limitations that preclude them from being used effectively in an automated ABIAA system with multiple data sources.
This paper discusses modern ABIAA architectural considerations providing an overview of an advanced ABIAA system and comparisons to legacy systems. It concludes with a recommended strategy and incremental approach to the research, development, and construction of a fully automated ABIAA system.
Recent technological advances in computing capabilities and persistent surveillance systems have led to increased focus on new methods of exploiting geospatial data, bridging traditional photogrammetric techniques and state-of-the-art multiple view geometry methodology. The structure from motion (SfM) problem in Computer Vision addresses scene reconstruction from uncalibrated cameras, and several methods exist to remove the inherent projective ambiguity. However, the reconstruction remains in an arbitrary world coordinate frame without knowledge of its relationship to a xed earth-based coordinate system. This work presents a novel approach for obtaining geoaccurate image-based 3-dimensional reconstructions in the absence of ground control points by using a SfM framework and the full physical sensor model of the collection system. Absolute position and orientation information provided by the imaging platform can be used to reconstruct the scene in a xed world coordinate system. Rather than triangulating pixels from multiple image-to-ground functions, each with its own random error, the relative reconstruction is computed via image-based geometry, i.e., geometry derived from image feature correspondences. In other words, the geolocation accuracy is improved using the relative distances provided by the SfM reconstruction. Results from the Exelis Wide-Area Motion Imagery (WAMI) system are provided to discuss conclusions and areas for future work.
We describe a compact, multi-sensor design architecture capable of providing both spectral-polarimetric imaging and
adaptive matched filter target detection in real-time. The sensor suite supports airborne broad-area search missions using
multiple large-format, high speed TDI scanning sensors. The technology approach leverages Micro-Electro-Mechanical
System (MEMS) based spectral imaging systems and scanning TDI arrays originally developed for space based remote
sensing. The MEMS spectrometer system can dynamically select and switch linear combinations of single or multiple
VNIR/SWIR spectral bands with 5nm sampling resolution using a programmable MEMS mirror. The MEMS spectral
filter is capable of providing high quality spectral filtering across a large format sensor with > 1MHz optical switching &
update speeds. A dual instrument sensor suite architecture called the "PRISM sensor" has been developed which is based
on this technology and provides simultaneous spectral-polarimetric imaging and matched filter target tracking with
minimal on-board computing requirements. We describe how this technology can simultaneously perform broad-area
imaging and target identification in near real-time with a simple threshold operation. Preliminary results are illustrated
as additional layer of target-discriminate geospatial information that may be fused with geo-referenced imagery.
In this paper we present a new approach to the real-time generation and dissemination of steerable video chips from
large volume motion imagery streams. Traditional large frame motion imagery streaming and dissemination systems
employ JPEG 2000 (J2K) compression and associated JPEG 2000 Interactive Protocol (JPIP) streaming to encode and
deliver images over varying bandwidth communication channels. While J2K and JPIP technologies are suitable for many
large frame motion imagery applications, they often struggle to satisfy the needs of certain low power, low bandwidth
users. The J2K format does not currently support inter-frame compression and, therefore, cannot target the lowest
bandwidth motion imagery users. Additionally, J2K decompression and JPIP processing both consume more
computational resources than low-end client systems often have available. This is especially true for handheld and thin-client
devices. We address these issues by integrating region-of-interest J2K compression and JPIP streaming with
MPEG-2 and H.264 video compression technology, taking advantage of the ubiquitous hardware acceleration and client
ingest support for these full motion video product formats. The proposed architecture maintains all the benefits of
incorporating a J2K archival format, while also boasting the ability to disseminate J2K regions-of-interest and low
resolution overviews to an even greater number of simultaneous clients. We illustrate a real-time integration and
implementation of these technologies and show how they can be used to enable interactive and automated tracking and
dissemination of multiple moving objects from wide area persistent surveillance motion imagery.
Providing current, time-sensitive imagery and geospatial information to deployed tactical military forces or first
responders continues to be a challenge. This challenge is compounded through rapid increases in sensor collection
volumes, both with larger arrays and higher temporal capture rates. Focusing on the needs of these military forces and
first responders, ITT developed a system called AGILE (Advanced Geospatial Imagery Library Enterprise) Access as an
innovative approach based on standard off-the-shelf techniques to solving this problem. The AGILE Access system is
based on commercial software called Image Access Solutions (IAS) and incorporates standard JPEG 2000 processing.
Our solution system is implemented in an accredited, deployable form, incorporating a suite of components, including an
image database, a web-based search and discovery tool, and several software tools that act in concert to process, store,
and disseminate imagery from airborne systems and commercial satellites. Currently, this solution is operational within
the U.S. Government tactical infrastructure and supports disadvantaged imagery users in the field. This paper presents
the features and benefits of this system to disadvantaged users as demonstrated in real-world operational environments.
In this paper we present an approach to integrate sensors to meet the demanding requirements of Quick Reaction
Capability (QRC) airborne programs. Traditional airborne sensors are generally highly integrated and incorporate
custom sensor technologies and interfaces. Custom solutions and new technologies often require significant engineering
to achieve a high technology readiness level (TRL) and to meet the overall mission objective. Our approach differs from
traditional approaches in that we strive to achieve an integrated solution through regular review, assessment, and
identification of relevant industry "best athlete" technologies. Attention is focused on solution providers that adhere to
standard interfaces and formats, incorporate non-proprietary techniques, are deemed highly-reliable/repeatable, and
enable assembly production. Processes and engineering tools/methods have traditionally been applied to dozens of
longer-acquisition space-based ISR programs over 50 years. We have recently leveraged these techniques to solve
airborne Intelligence, Surveillance and Reconnaissance (ISR) mission challenges. This presentation describes and
illustrates key aspects and examples of these techniques, solving real-world airborne mission needs.
KEYWORDS: Image compression, Sensors, Image processing, Telecommunications, Field programmable gate arrays, Cameras, Detection and tracking algorithms, Data storage, Video compression, Video
ITT has developed and demonstrated a real-time airborne data management system that ingests, compresses, stores, and
streams imagery and video data from sensors based on users' needs. The data management system was designed to be
sensor agnostic, which was demonstrated when ITT quickly integrated several different cameras including an HD video
camera, an IR video camera, and large framing cameras. The data is compressed in real-time using ITT's high-speed
JPEG 2000 compression core and stored in the airborne unit. The data is then interactively served to users over downlink
communication based on the users' requests. This system's capability was demonstrated in several test flights where data
was collected from the sensors at 132 megapixels per second (1.5 gigabits per second), compressed, stored, and
interactively served as regions of interest to multiple users over a 48 megabit/second communication link. This data
management system is currently being incorporated into airborne systems for military and civil applications.
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