Compressed sensing techniques for altitude estimation in multipath conditions


In very high frequency array radars, the multipath signal and direct signal, which fall inside the beamwidth of the receiving antenna, are highly correlated. This correlation degrades the performance of the low-angle direction-of-arrival (DOA) estimation in multipath conditions. By creating use of the sparsity of the targets, after filtering out the muddle in the Doppler dimension, two DOA estimation approaches primarily based on compressed sensing (CS) are proposed. The interpolated array- (IA-) CS and beamspace- (BS-) CS perform compressive sampling, respectively, on an IA and within the BS. The proposed methods are different from subspace-based methods in concept and aren't subject to the restricting necessities of spatial and temporal stationarities, still because the correlation between the sources and noise. Both simulated and measured results verify that the proposed ways give superior performance in resolving the DOAs as compared with the spatial CS technique and other standard DOA methods.

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