Ultra-Wideband Imaging via Frequency Diverse Array with Low Sampling Rate

Abstract

Imaging systems based on millimeter waves (mm-waves) are advancing to achieve higher resolution and wider bandwidth. However, a large bandwidth requires high sample rates, which may limit the development of ultra-wideband imaging systems. In this letter, we introduce the concept of frequency diverse array (FDA) into mm-wave imaging systems. In particular, we propose an ultra-wideband imaging method based on the FDA configuration to reduce sampling rates. In the proposed method, the required sampling rate of an imaging system with N transmit elements is only one-Nth of the conventional systems. Hence, the proposed method can significantly reduce the sampling rate. Unlike compressed-sensing-based sampling methods, the proposed method does not require repeated observations, and is easier to implement. Thanks to the FDA concept, the proposed method can scan the space without phase-shifters or rotation of antennas. We perform matched filtering process in the frequency domain to obtain frequency-delay-dependent vectors. By discretizing the scene, we establish a dictionary covering the imaging scene. Accordingly, a convex optimization problem with measured results and the dictionary based on sparse reconstruction are formulated to realize super-resolution imaging. Compared to conventional methods, the proposed method can distinguish smaller target intervals with low sampling rate in an easy-to-implement way. The proposed method provides a different perspective for the development of ultra-wideband imaging systems.