Over the past few years, three-dimension fast imaging and identification with microwave has recently gained a lot of attention. Resulting from the over-simple imaging model and over-large computation cost, the existing three-dimension radar imaging methods are limited to few scenarios. To break this bottleneck, we introduce a novel physics-driven three-dimension fast radar imaging method based on general reflectivity model, far-field-approximation assumption and neighbor-cell approximation, in which the whole imaging region would be decomposed into a series of sub-regions to accelerate the imaging speed in parallel. The proposed method drastically decreases the cost of memory while maintaining fast imaging speed and high imaging quality. Therefore, the proposed fast imaging method based on general reflectivity model, far-field-approximation and neighbor-cell approximation is applicable to more large-scale radar imaging scenarios. Some selected simulation results are presented to demonstrate the state-of-the-art performance of the far-field-approximation methods.
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