RAPTAR: Radar Radiation Pattern Acquisition through Automated Collaborative Robotics
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916858314096640 |
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| author | Qureshi, Maaz Bagheri, Mohammad Omid Elbadrawy, Abdelrahman Melek, William Shaker, George |
| author_facet | Qureshi, Maaz Bagheri, Mohammad Omid Elbadrawy, Abdelrahman Melek, William Shaker, George |
| contents | Accurate characterization of modern on-chip antennas remains challenging, as current probe-station techniques offer limited angular coverage, rely on bespoke hardware, and require frequent manual alignment. This research introduces RAPTAR (Radiation Pattern Acquisition through Robotic Automation), a portable, state-of-the-art, and autonomous system based on collaborative robotics. RAPTAR enables 3D radiation-pattern measurement of integrated radar modules without dedicated anechoic facilities. The system is designed to address the challenges of testing radar modules mounted in diverse real-world configurations, including vehicles, UAVs, AR/VR headsets, and biomedical devices, where traditional measurement setups are impractical. A 7-degree-of-freedom Franka cobot holds the receiver probe and performs collision-free manipulation across a hemispherical spatial domain, guided by real-time motion planning and calibration accuracy with RMS error below 0.9 mm. The system achieves an angular resolution upto 2.5 degree and integrates seamlessly with RF instrumentation for near- and far-field power measurements. Experimental scans of a 60 GHz radar module show a mean absolute error of less than 2 dB compared to full-wave electromagnetic simulations ground truth. Benchmarking against baseline method demonstrates 36.5% lower mean absolute error, highlighting RAPTAR accuracy and repeatability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_16988 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | RAPTAR: Radar Radiation Pattern Acquisition through Automated Collaborative Robotics Qureshi, Maaz Bagheri, Mohammad Omid Elbadrawy, Abdelrahman Melek, William Shaker, George Robotics Accurate characterization of modern on-chip antennas remains challenging, as current probe-station techniques offer limited angular coverage, rely on bespoke hardware, and require frequent manual alignment. This research introduces RAPTAR (Radiation Pattern Acquisition through Robotic Automation), a portable, state-of-the-art, and autonomous system based on collaborative robotics. RAPTAR enables 3D radiation-pattern measurement of integrated radar modules without dedicated anechoic facilities. The system is designed to address the challenges of testing radar modules mounted in diverse real-world configurations, including vehicles, UAVs, AR/VR headsets, and biomedical devices, where traditional measurement setups are impractical. A 7-degree-of-freedom Franka cobot holds the receiver probe and performs collision-free manipulation across a hemispherical spatial domain, guided by real-time motion planning and calibration accuracy with RMS error below 0.9 mm. The system achieves an angular resolution upto 2.5 degree and integrates seamlessly with RF instrumentation for near- and far-field power measurements. Experimental scans of a 60 GHz radar module show a mean absolute error of less than 2 dB compared to full-wave electromagnetic simulations ground truth. Benchmarking against baseline method demonstrates 36.5% lower mean absolute error, highlighting RAPTAR accuracy and repeatability. |
| title | RAPTAR: Radar Radiation Pattern Acquisition through Automated Collaborative Robotics |
| topic | Robotics |
| url | https://arxiv.org/abs/2507.16988 |