Unmanned systems are increasingly being adopted by military and civilian organizations for a variety of roles previously carried out with manned aircraft, including Intelligence, Surveillance and Reconnaissance (ISR), and search and rescue operations. These drones can carry a variety of sensor packages, and produce a high volume of data including FLIR and full-motion video.
However, the sheer volume of data produced can introduce operational challenges. Analysts typically pull data from various sources depicted on separate displays and try to decide what data is relevant and useful. After this lengthy process the analysist must then figure out how to get this data to where it is needed in the tactical environment. This takes time and often the initiative is lost.
While it's useful for unmanned system operators to have access to real-time ISR sensor data, the raw data is of limited use unless it can be analysed and shared. A lack of standards implementation for data exchange, and the sheer volume of sensor data collected confronts organizations with significant challenges, including:
MIDAS™ was developed to provide a rapid capability for the exploitation and further distribution of sensor data to include from Unmanned Systems (UxS). MIDAS enables the monitoring of the current mission sensor feeds and permits comparative analysis against legacy sensor feeds from the same search area. Providing this capability at the tactical level will reduce the current connectivity reliance and wait times associated with higher-level headquarters decisions.
MIDAS is based on the NATO Alliance Ground Surveillance project which required the storage and retrieval of vast amounts of intelligence data for Intelligence Analysts from a Triton (upgraded Global Hawk) Unmanned Aircraft System (UAS). Kongsberg Geospatial provided this strategic data storage capability and has now packaged that strategic capability into a tactical and portable form factor.
This MIDAS ISR capability can now be deployed anywhere a tactical UAS goes, giving to the front-line war-fighter an decided advantage in his/her situational awareness. This also provides civilian UAS operators and search and rescue organizations with a powerful capability to more effectively manage and use sensor data during search and rescue or survey missions.
The MIDAS form-factor consists a stand-alone laptop for the operator interface, and a portable server in a ruggedized case for the Data Storage and Retrieval (DSAR) component. It doesn't interfere with the Command and Control (C2) / Ground Control Station (GCS) for the UAS. The form factor of a laptop can be set up anywhere and is ideal for confined spaces encountered in a frontline C2 tent, a building, naval surface vessel or even in an aircraft.
Using the MIDAS Viewer analysts can view layers of open source or even classified data situated in a Common Operating Picture (COP) view. The MIDAS platform includes a common network connector Application Programming Interface (API) which allows any data source to be retrieved and displayed with temporal and spatial metadata in a map.
The DVR-style data animation playback capability of MIDAS is ideal for reviewing mission data, and allows analysts to animate massive data sets to see the progression of intelligence reports and incidents as they happened in time and space.
If an analyst notices something anomalous in the real-time FMV data feed from an UnmannedVehicle’s sensor feed, they can simply highlight the mission area on the MIDAS map display and MIDAS will search and return the range of historical intelligence products created from previous missions within that area for comparison with the current data.
This is shown in the image above where the analyst has drawn a green rectangle area of interest and MIDAS has searched and returned a series of bookmarks of previous intelligence products of note within that selected area. This means that an operator can now compare the current FMV sensor feed in near real-time to past sensor files, or intelligence products from that exact area. They can then create and disseminate briefing products created from these comparisons to inform decision makers.
This capacity to compare, analyse and create actionable intelligence at the tactical edge can dramatically increase the value of tactical UxS to decision-makers. Analysts can now understand how the local (tactical) situations on the ground is evolving without needing to wait on higher headquarters analysis - even assuming high bandwidth connectivity to pass FMV to HQ exists.
Patterns-of-Life (POL) on targets that might otherwise be lost in the noise of big data sets can now be identified in near real-time. This correlation of geographic and temporal data presents a tremendously powerful new paradigm for tactical-level data analysis and offers an efficient and effective path to disseminate actionable intelligence.