Near real-time, on-the-move multisensor integration and computing framework

Abstract

Implanted mines and improvised devices are a persistent threat to Warfighters. Current Army countermine missions for route clearance need on-the-move standoff detection to improve the rate of advance. Vehicle-based forward looking sensors such as electro-optical and infrared (EO/IR) devices can be used to identify potential threats in near real-time (NRT) at safe standoff distance to support route clearance missions. The MOVERS (Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System) is a vehicle-based multi-sensor integration and exploitation system that ingests and processes video and imagery data captured from forward-looking EO/IR and thermal sensors, and also generates target/feature alerts, using the Video Processing and Exploitation Framework (VPEF) "plug and play" video processing toolset. The MOVERS Framework provides an extensible, flexible, and scalable computing and multi-sensor integration GOTS framework that enables the capability to add more vehicles, sensors, processors or displays, and a service architecture that provides low-latency raw video and metadata streams as well as a command and control interface. Functionality in the framework is exposed through the MOVERS SDK which decouples the implementation of the service and client from the specific communication protocols.

Real-time buried threat detection and cueing capability in VPEF environment

“…MOVER player [12] was used to publish the data in a near real-time fashion and processed by the detection pipeline running on the same workstation (using shared memory data transfer). The detected objects were saved to a KML location file which is post processed in MATLAB to evaluate number of true detections and number of false alarms.…”