As an Electronic Warfare System Engineer my key responsibilities are:System Design and Integration:Develop and engineer Electronic Counter-Countermeasure (ECCM) solutions for rotary-winged and fixed-winged aircrafts.Merging innovation with practicality, I have excelled in designing ECCM and RWR solutions that seamlessly integrate into existing electronic warfare architectures. Collaborating with cross-functional teams, I ensure the seamless deployment of cutting-edge technology.Testing and Validation:Conduct comprehensive testing and validation of ECCM systems to ensure optimal performance under various operational scenarios.Analyze test data to fine-tune ECCM algorithms and optimize system performance.Technical Documentation:Create detailed technical documentation, including specifications, test plans, and user manuals, to facilitate seamless integration and maintenance of ECCM systems.Collaboration and Teamwork:Work closely with multidisciplinary teams, including hardware engineers, software developers, and operational experts, to develop holistic and cohesive ECCM solutions.Research and Innovation:Stay abreast of industry trends, emerging technologies, and advancements in electronic warfare and ECCM techniques.Incorporate novel methodologies and innovative approaches to continually enhance ECCM capabilities.Project Management:Participate in project planning, execution, and monitoring, ensuring that ECCM milestones are achieved within stipulated timelines.Training and Support:Provide technical training and support to operational teams to ensure effective deployment and utilization of ECCM systems in real-world scenarios.Radar Warning Receivers (RWRs):With a specialized focus on RWR technology, I possess a deep understanding of signal processing, threat identification, and real-time situational awareness. I design RWR solutions that empower aircraft with the ability to detect and respond to radar-guided threats effectively.

The role encompassed the design of a 4-layered PCB, development of a Level 2+ Guidance Algorithm for Unmanned Aerial Vehicles (UAVs) using MATLAB and Simulink, and integration of data from an Inertial Measurement Unit (IMU) sensor via Keil uVision on an STM32F4 microcontroller. The journey through these projects provided hands-on exposure to electronics, software development, and aerospace engineering, contributing substantively to real-world applications.PCB Design:The journey commenced with the intricacies of designing a 4-layered Printed Circuit Board (PCB). Schematic creation, component selection, noise management, and signal integrity optimization were pivotal aspects of this project. This process offered insights into the intricacies of EDA tools, PCB manufacturing, and the delicate balance between functionality and manufacturability.UAV Guidance Algorithm:The core of the part-time job role delved into developing a robust Level 2+ Guidance Algorithm for UAVs. The algorithm, developed using MATLAB and Simulink, incorporated dynamic waypoint navigation, obstacle avoidance, and real-time path planning. This endeavor expanded knowledge in control systems, aerodynamics, and algorithmic design, culminating in a sophisticated UAV guidance system capable of intelligent decision-making.Sensor Integration with STM32F4:The role also encompassed the integration of an IMU sensor with an STM32F4 microcontroller. Leveraging Keil uVision, this involved interfacing, data acquisition, calibration, and real-time data fusion. This integration journey illuminated the complexities of sensor data synchronization, low-level microcontroller programming, and real-time data processing.

I performed my second summer practice in ARDICLABS which aims to be a globally recognized research and development establishment providing guidance, navigation and control for autonomous systems and aerospace industry. My practice lasted totally 3 weeks starting from 07.09.2020 and ending in 25.09.2020. I had works which are about Linux based operating systems, GPS systems, High Accuracy Positioning Enhancement and GPS correction - RTCM 3.2- data casting and receiving it from internet. During my summer practice, my supervisor was Bekir ŞEN who is a Co-Founder of the company.

AI-based Social Distance and Mask Detection ProgramThe AI-based Social Distance and Mask Detection System is a cutting-edge solution that utilizes the power of machine learning and computer vision technologies to ensure public safety during the ongoing global pandemic. By combining TensorFlow, Keras, and OpenCV, this program can accurately identify individuals who are not maintaining proper social distance and those who are not wearing masks. The system is designed to function in real-time, making it suitable for various environments, such as offices, public spaces, and retail establishments.