A Novel Block Focused Omega-K Algorithm for Millimetre-Wave Radar Imaging

Classical millimetre-wave (mmWave) radar imaging algorithms frequently encounter challenges arising from their substantial computational demands and the complexities inherent in addressing covert imaging effects. In this paper, an original block processing technique is introduced, where the echo data from each antenna is partitioned into two segments along a uniform plane array, simplifying complex matrix operations as observed in traditional approaches such as the back projection algorithm (BPA), the range-Doppler algorithm (RDA), and the omega-k ($\omega k$) algorithm. Additionally, a novel focusing step is introduced to increase the strength of the target signal at low signal-to-noise ratios, which entails partitioning the two-dimensional Fourier-transformed domain echo data into blocks based on the distance dimension. These improvements are integrated into the conventional $\omega k$ algorithm, yielding the proposed ”Block Focused Omega-k” (BF-$\omega k$) algorithm. Finally, a real experimental platform is established employing the official Ti IWR1642 experimental board. The effectiveness of the introduced algorithm is demonstrated through both simulation experiments and physical experiments. Extensive trials have been conducted encompassing imaging under varying signal-to-noise ratios and compression ratios, and the imaging of exposed and concealed objects across both single-target and multi-target scenarios.