Quantity over Quality: Dithered Quantization for Compressive Radar Systems

Abstract: In this paper, we investigate a trade-off between the number of radar observations (or measurements) and their resolution in the context of radar range estimation. To this end, we introduce a novel estimation scheme that can deal with strongly quantized received signals, going as low as 1-bit per signal sample.

Sparsity-Driven Moving Target Detection in Distributed Multistatic FMCW Radars

Abstract: We investigate the problem of sparse target detection from widely distributed multistatic textitFrequency Modulated Continuous Wave (FMCW) radar systems (using chirp modulation). Unlike previous strategies e.g., developed for FMCW or distributed multistatic radars), we propose a generic framework that scales well in terms of computational complexity for high-resolution space-velocity grid.

1-bit Localization Scheme for Radar using Dithered Quantized Compressed Sensing

Abstract: We present a novel scheme allowing for 2D target localization using highly quantized 1-bit measurements from a Frequency Modulated Continuous Wave (FMCW) radar with two receiving antennas. Quantization of radar signals introduces localization artifacts, we remove this limitation by inserting a dithering on the unquantized observations.