Cognitive sub-Nyquist hardware prototype of a collocated MIMO radar
| Autor: | Eli Shoshan, Kumar Vijay Mishra, David Cohen, Yonina C. Eldar, Shahar Dror, Robert Ifraimov, Maxim Meltsin, Moshe Namer, Ron Madmoni |
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| Jazyk: | angličtina |
| Předmět: |
FOS: Computer and information sciences
020301 aerospace & aeronautics Computer science business.industry Information Theory (cs.IT) Computer Science - Information Theory MIMO 020206 networking & telecommunications 02 engineering and technology Frequency-division multiplexing law.invention 0203 mechanical engineering Sampling (signal processing) Transmission (telecommunications) law 0202 electrical engineering electronic engineering information engineering Waveform Nyquist–Shannon sampling theorem Radar Antenna (radio) business Computer hardware Computer Science::Information Theory |
| Zdroj: | 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa) |
| DOI: | 10.1109/cosera.2016.7745699 |
| Popis: | We present the design and hardware implementation of a radar prototype that demonstrates the principle of a sub-Nyquist collocated multiple-input multiple-output (MIMO) radar. The setup allows sampling in both spatial and spectral domains at rates much lower than dictated by the Nyquist sampling theorem. Our prototype realizes an X-band MIMO radar that can be configured to have a maximum of 8 transmit and 10 receive antenna elements. We use frequency division multiplexing (FDM) to achieve the orthogonality of MIMO waveforms and apply the Xampling framework for signal recovery. The prototype also implements a cognitive transmission scheme where each transmit waveform is restricted to those pre-determined subbands of the full signal bandwidth that the receiver samples and processes. Real-time experiments show reasonable recovery performance while operating as a 4x5 thinned random array wherein the combined spatial and spectral sampling factor reduction is 87.5% of that of a filled 8x10 array. 5 pages, Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa) 2016 |
| Databáze: | OpenAIRE |
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