Near-field source localization based on sparse reconstruction of sensor-angle distributions
作者： Yimin D. Zhang , Si Qin , Moeness G. Amin
DOI: 10.1109/RADAR.2015.7131121
关键词:
摘要: In this paper, we consider a problem of near-field source localization using the sensor-angle distribution (SAD) that views range and direction-of-arrival (DOA) information as sensor-dependent phase progression. The SAD draws parallel to quadratic time-frequency distributions and, such, is able reveal changes in spatial frequency over sensor positions. particular, for moderate range, signature polynomial shape, thus simplifying parameter estimation. We sparse arrays where array sensors are located on grid but with missing Sparse reconstruction techniques used estimate joint space domain, results then mapped back DOA estimation localization. effectiveness proposed technique verified simulation results.
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