Two-dimensional direction-of-arrival (DoA) estimation in azimuth and elevation via radar systems equipped with uniform rectangular arrays (URAs) will play an important role in various application areas-most distinctiv...
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Two-dimensional direction-of-arrival (DoA) estimation in azimuth and elevation via radar systems equipped with uniform rectangular arrays (URAs) will play an important role in various application areas-most distinctively in future urban air mobility settings with unmanned aerial vehicles. A key factor is the fast and reliable provision of target detections in terms of range and DoA for safe autonomous operation of the vehicle using on-board antenna arrays with compact installation size. The authors present a technique for improving the performance of DoA estimation using compressive sensing in conjunction with multiple-input multiple-output arrays with electronically steered beams in the transmit direction. The simulation study investigates the impact of different design considerations on radar signal processing performance. An optimisation of a radar system using electronic beamsteering in the transmit domain is presented numerically. Based on the architecture of the URAs used, performance and detection accuracy can be improved. The authors deal with direction-of-arrival (DoA) estimation of obstacles in the field-of-view (FoV) using compressive sensing (CS) and compares multiple-inputmultiple-output (MIMO) radar signal processing with a codebook-based electronic beamsteering approach for compact radar sensors in future urban air mobility. Simulations show an improvement in the reliability of DoA estimation when using appropriate beamsteering directions, which can also be seen in the Grammian representation of the selected sensing matrix representing the electronic beamsteering ***
multiple-input multiple-output arrays in frequency modulated continuous wave (FMCW) radars provide the angular resolution required to isolate objects in complex automotive scenes. However, the demodulation of individu...
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multiple-input multiple-output arrays in frequency modulated continuous wave (FMCW) radars provide the angular resolution required to isolate objects in complex automotive scenes. However, the demodulation of individual antenna contributions increases the chirp repetition interval, which reduces the maximum unambiguously measurable velocity. Objects moving faster than this velocity are then incorrectly folded in the range-Doppler maps, leading to critical inaccuracies in the advanced driver assistance systems. Here, this problem is addressed from the binary phase modulation (BPM) perspective, which is a scheme particularly attractive due to its high signal-to-noise ratio, and whose intrinsic phase alterations prevent traditional disambiguation techniques from being reliable. The authors present a detailed analysis on the design, implementation, and validation of Doppler disambiguation techniques for BPM systems. The presented benchmark includes a variety of algorithms involving the Chinese remainder theorem, density-based spatial clustering of applications with noise (DBSCAN), hypothetical phase compensation, and an intuitive range-based approach. The techniques are extensively validated using synthetic data generated with MATLAB, and real data collected with a 77-GHz FMCW radar. The results show the best set of trade-offs for the enhanced DBSCAN (EDBSCAN) method in terms of robustness, computational overhead, velocity span, and disambiguation rate.
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