Sentient and CarteNav jointly announced today the deployment of Sentient’s Kestrel Land MTI software in support of the UK NPAS. Kestrel Land MTI is automated object detection software that can be used by the UK NPAS to cue airborne operators to potential objects of interest within the field of view of the electro optical / infrared sensors deployed on their helicopters. Kestrel has been specifically optimised to maximise detection performance in operational conditions typical of those faced by the UK NPAS. The software is integrated as a part of CarteNav’s AIMS-ISR® mission system. Objects of interest are detected by Kestrel and fed into the intuitive AIMS-ISR® software in real time for quick and effective decision making.
“Whether it is detecting suspects, counter terrorism or general patrol operations, Kestrel Land MTI, adds a critical cost effective real time automated detection capability to the NPAS rotary fleet,” said Simon Olsen, Director Business Development, Strategy and Partnerships for Sentient. “Kestrel will be provided as a part of the overall AIMS-ISR® mission system software providing improved situational awareness and an intuitive operating system to reduce operator burden in time critical operationalenvironments”, added Paul Evans, Chief Executive Officer of CarteNav.
Kestrel Land MTI has been extensively deployed in support of military operations in Australia, the US, South America, the Middle East, Europe and Africa. “Moving more into the commercial and civil market over the past couple of years, this deployment with the flagship UK NPAS is an important one for our Kestrel software suite”, added Olsen.
Kestrel Land MTI is a software solution that automatically detects small moving objects in real-time within EO/IR sensor feeds. Kestrel specializes in detecting objects that are difficult for the operator to see, such as vehicles and people moving in challenging environments. With Kestrel, operators are able to use wide field of view settings to cover larger search areas with a higher probability of detection.
Source: ASDWire ASD
Date: Jul 16, 2015