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An Applied Frequency Scaling Algorithm Based on Local Stretch Factor for Near-Field Miniature Millimeter-Wave Radar Imaging

The frequency scaling algorithm (FSA) is a popular imaging algorithm for dechirped SAR data. To obtain a large azimuth detection area, the miniature millimeter-wave (mmW) linear-frequency-modulated continuous-wave (LFMCW) surveillance radar requires a wider azimuth beamwidth, which leads to additional range frequency aliasing in FSA. Because of the adoption of the dechirp-on-receive technique, the sampling frequency is much smaller than the range bandwidth during near-field imaging, which further aggravates the aliasing effects. The target cannot be well focused, and it makes the weak targets submerged in the background. To acquire high-quality SAR images, an improved FSA using the local stretch operation is proposed. The aliasing bandwidth properties introduced by the FS operation and the desired objective range cell migration (RCM) factor are used in this proposed local-stretch FSA (LSFSA). The initial RCM factor is adjusted by the stretch operation to eliminate the frequency aliasing to a certain level without increasing the computing load. The LSFSA is suitable for solving the problem of range frequency aliasing in near-field side-looking SAR and high squint SAR with wide azimuth beamwidth. The proposed method is validated using reasonable simulations and convincing experiments.