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Using propeller rotation to aid UAV detection
Small size UAVs pose a challenge in terms of their detection and tracking due to their small size. In this context, the task is to implement algorithms for enhancing the radar/vision system capabilities, allowing the detection of UAVs at larger distances and/or under poor environmental conditions.
The continuous increase of small-sized unmanned aerial vehicles (UAV) represents a threat for civilian and military activities. Moreover, small size UAVs pose a challenge in terms of their detection, especially in non-ideal weather conditions. Radar aided systems offer a robust solution for UAV target detection and tracking applications, due to their long range measurement capabilities in the presence of rain, dust and air contamination. For the case of low altitude, slow motion, small size (LSS) UAVs, the target radar signature (received power from the UAV target) is small and the radar systems receive indirect back scattered signals from the ground. Therefore, tracking such vehicles is more demanding and requires additional effort in processing the radar measurements. In this context, the task of the student is to implement and tune a micro Doppler algorithm for processing the radar signals, so as to detect UAV propeller motion. This would ultimately aid in the detection of UAVs at larger distances and/or under poor environmental conditions.
In particular, this includes:
- The development of a Micro-Doppler signal isolation algorithm which uses the target UAV's propeller rotation to aid detection.
The student will develop an algorithm for allowing the improved detection of UAV targets by using micro-Doppler techniques. The algorithm will ultimately be fused as a part of a radar system for allowing real-time enhanced UAV detection and tracking.
The continuous increase of small-sized unmanned aerial vehicles (UAV) represents a threat for civilian and military activities. Moreover, small size UAVs pose a challenge in terms of their detection, especially in non-ideal weather conditions. Radar aided systems offer a robust solution for UAV target detection and tracking applications, due to their long range measurement capabilities in the presence of rain, dust and air contamination. For the case of low altitude, slow motion, small size (LSS) UAVs, the target radar signature (received power from the UAV target) is small and the radar systems receive indirect back scattered signals from the ground. Therefore, tracking such vehicles is more demanding and requires additional effort in processing the radar measurements. In this context, the task of the student is to implement and tune a micro Doppler algorithm for processing the radar signals, so as to detect UAV propeller motion. This would ultimately aid in the detection of UAVs at larger distances and/or under poor environmental conditions. In particular, this includes:
- The development of a Micro-Doppler signal isolation algorithm which uses the target UAV's propeller rotation to aid detection.
The student will develop an algorithm for allowing the improved detection of UAV targets by using micro-Doppler techniques. The algorithm will ultimately be fused as a part of a radar system for allowing real-time enhanced UAV detection and tracking.
- Literature review for radar based detection systems for UAVs
- Implement a signal isolation algorithm based on micro Doppler.
- Evaluate the algorithm performance in simulation and via post processing.
- Contribute to the fusion of the radar tracking algorithm into the radar system framework for allowing enhanced on-board real-time UAV tracking.
- Literature review for radar based detection systems for UAVs - Implement a signal isolation algorithm based on micro Doppler. - Evaluate the algorithm performance in simulation and via post processing. - Contribute to the fusion of the radar tracking algorithm into the radar system framework for allowing enhanced on-board real-time UAV tracking.
- Highly motivated and independent student.
- Interest in radar systems, signal processing, and hands-on hardware interfacing.
- Excellent programming skills (MATLAB and C++) mandatory.
- Experience with working under ROS
- Enrolled at ETH Zurich.
- Highly motivated and independent student. - Interest in radar systems, signal processing, and hands-on hardware interfacing. - Excellent programming skills (MATLAB and C++) mandatory. - Experience with working under ROS - Enrolled at ETH Zurich.
Amir Melzer (amir.melzer@mavt.ethz.ch), Martin Adams (martin.adams@mavt.ethz.ch)
Amir Melzer (amir.melzer@mavt.ethz.ch), Martin Adams (martin.adams@mavt.ethz.ch)