RNC Avionics strongly invests in Research and Development as a mechanism to bring new and potentially market disruptive products, as well as to reinforce the company’s intellectual property.

We adopt the open innovation paradigm and work closely with an extensive network of recognised leading experts, including universities, research laboratories and international study groups. Over the past years, we invested more than £1 million in R&D activities.  Our expertise and competences were recognised in several grants awarded by UK and European bodies.


THERMAL-NAV (Smart On-Board UAV Thermal Signature Analysis for Surveillance, Tracking and Navigation) was an Innovate UK funded Project for a novel UAV on-board video analytics system.

RNC Avionics developed a novel integrated on-board imaging system employing ‘thermal signature’ analysis algorithms for detecting heat trails left by a vehicle/vessel and explore this in real time (together with other on-board sensors) for adjustment of its flight plan.  The algorithms were designed to detect and track the object of interest and, subsequently, adjust the UAV pre-defined flight plan to ensure that the object is continuously tracked. This approach offers a step change in current capabilities with significant potential to change the way thermal imaging is used in UAV surveillance.

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Funded by the Innovate UK Smart Award programme, the project ran over a 15 month period and was successfully completed on the 14th January 2015. Throughout the project the following achievements were met:

  • Development of a new algorithm that is capable of detecting heat trails (thermal wake) left by the vessel.
  • Development of a new Kalman filter-like algorithm to detect and track moving objects on video captured from a moving camera.
  • Demonstrated algorithm capability to detect multiple objects within one frame, even in conditions where severe camera motion is evident.
  • Transferability of the developed algorithms to other applications using generic video sensors (grayscale camera, RGB camera, thermal imager).
  • Application of an object position estimation technique - based on a geographical co-ordinates calculation given Euler angles and the geographical co-ordinates of the camera – for flight plan adjustment.
  • Demonstration of algorithms over several datasets with different conditions.
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