High-resolution Imaging Based on Coher- Ent Processing for Distributed Multi-band Radar Data

Abstract—A coherent processing method for subband signals of distributed multi-band radar data is proposed and tested. The method uses de-noising cross-correlation (DNCC) algorithm and statistical method to obtain phase incoherent parameters (ICP) between subband signals. After compensating the phase ICP, a coherence function is defined and combined with statistical method to find amplitude ICP. Finally, data fusion method via two-dimensional gapped-data state space approach (2-D GSSA) is applied to subband signals and high-resolution imaging of target is achieved. The advantage of this method lies in that it can be used to process subband signals of different bandwidth and different gaps between them. To validate our work, electromagnetic calculation target and real target measured in microwave chamber are analyzed and used for testing different mutual-coherence and data fusion algorithms. Experimental results demonstrate the superiority of the proposed method over previous approaches in terms of improved imaging quality and performance.