Resources

Custom Solutions

Nurjana Technologies is exceptionally skilled at solving challenges, no matter the size, and developing the ideal custom solution for each of our clients. Our experts join your team to discuss the need, desired outcome, and potential options for a solution. Then, we approach it from every angle, considering existing equipment and software while identifying any modifications or ground-up design we require to better meet the project’s needs. In the end, you receive a state-of-the-art solution customized to your needs and designed to deliver.

Multi-Sensor Central Control Station-Automatic Ballistic Tracking System

Customer: Weibel Doppler Radars

 

Challenge: Support Weibel in developing a ballistic tracking system (BTS) for the Australian Ministry of Defense by integrating radars and electro-optical tracking sensors to predict impact points.

 

Solution: NurjanaTech developed a proprietary multi-sensor central control station-automatic ballistic tracking system (MSCCS-ABTS), which processes data from various sensors, including radar electro-optical tracking sensors, and produces a visual output of the entire operation. Using NurjanaTech’s specific algorithm of ballistic prediction, the system also predicts impact points once a target’s position is identified.

 

Benefits: MSCCS-ABTS provides tools for a variety of mission analysis purposes. Building on NurjanaTech’s capabilities, the customer has adopted a more extensive portfolio of services to support its state-of-the-art operations.

Command and Control System

Customer: Roketsan (a Turkish weapons manufacturer)

 

Challenge: Roketsan required a command and control system capable of meshing data from various EOS located in the Karapınar Test Range.

 

Solution: NurjanaTech developed a multi-sensor central control station (MSSCS) to provide 3D visual accuracy using an Earth-centered Earth-fixed (ECEF) module. The command and control unit governs three electro-optical systems. A more complex integration aimed at obtaining optic stereometry was then achieved. The system works in conjunction with multiple radars and electro-optical systems.

 

Benefits: The MSCCS, together with the mobile trial simulator unit, a stand-alone mobile system, allowed the test range to operate a command and control system capable of managing and fusing a variety of sensor data. NurjanaTech’s expertise, experience, and short delivery times led to a very satisfied customer.

Research and Development

Nurjana Technologies designs and develops custom solutions for every customer, requiring our teams to perform considerable research and development (R&D) to ensure the ideal solution. Each challenge we tackle for our customers is driven by years of our own R&D and often sparks more. For every customer challenge, we vigorously research potential solutions and their potential effectiveness, then meticulously develop the ideal solution.

Advanced Strategies for Automatic Object Tracking during Test Range Activities using EOTS

A fundamental activity in modern test ranges, aerial object tracking relies on a capable video tracking system that closely follows airborne target dynamics based on the available imagery and a positioning system. Good tracking performance relies on a solid detection/tracking algorithm to retrieve the target position and a suitable controller to compute the positioning system trajectory to ensure the tracked object remains in the center of the image.

 

For this all to work well, a superior detection/tracking algorithm must be selected, and control action parameters, according to the scenario, must be chosen and carried out by an experienced operator.

 

NurjanaTech researched how to take the operator requirement out of the process by employing artificial intelligence and deep machine learning to select the best detection/tracking algorithm and control action parameters. Preliminary results show that a significant improvement is obtained with respect to the case where the operator performs the selection of the previously listed actions.

A New Improved Machine Learning Based Algorithm for Hotspots Detection

Wildfires are a growing threat worldwide, constantly putting people, property, and our environment at risk. Many are already out of control before they are even detected and often with a rapid forward rate of spread (FROS). Therefore, response time is crucial to contain wildfires and minimize damage and loss.

 

Agencies need a solution to quickly detect new fires and predict their behavior before they become a threat. To address this need, Nurjana Technologies, in collaboration with University La Sapienza of Rome, designed a new solution called S2IGI. This project detects wildfires hotspot early through satellite imagery. S2IGI performs automatic fire surveillance in an operator-determined region using geostationary satellites (MSG).

 

For this project, NurjanaTech introduced a polynomial multivariable model or a machine-learning-based model to estimate the mean and the standard deviation of the radiance of the SEVIRI channels in the region under surveillance. Two approaches were studied and compared in true positives, false positives, and not detected wildfires. The validation of the two methods was made possible thanks to the collaboration of the Italian Civil Protection, which provided the validation data.

Science of Trajectography

At the core of NurjanaTech’s intelligence offering is the science of  trajectography, which is the study and predictability of trajectory projections. Our expertise and demonstrated mastery of trajectography allows us to measure the predictability of how an object moves through air and space and accurately predict what is needed to counter this trajectory. We calculate the accuracy of tracking measurements using single sensor measurements, data fusion algorithms, the best sensor positions, and data analysis for each scenario.

 

With over tens years of studying and mastering trajectography, its effects, and counter resistance NurjanaTech can confidently offer our clients the best operational guidance and solutions to meet your predictability requirements.

 

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