Enhancing Synthetic Aperture Interferometric Radiometer Performance Through Imaging Quality-Centric Array Optimization

The synthetic aperture interferometric radiometer (SAIR) represents a cutting-edge technology for high-resolution imaging, with the antenna array configuration being essential to its imaging capabilities and system complexity. Existing methods for array optimization primarily focus on optimizing a single array-level metric, neglecting the intricate balance among metrics that is needed to ensure SAIR’s exceptional imaging performance. In this article, an innovative imaging quality-centric array optimization (IQC-AO) method is proposed, which takes imaging quality as the final optimization metric to achieve the optimal imaging performance of SAIR. The IQC-AO method adopts an accelerated optimization strategy, combines multiobjective and single-objective optimization techniques, and effectively addresses the problem of large solution space. This method not only reduces the optimization time, but also improves the overall performance of the SAIR array under the same conditions. In addition, the universality of the IQC-AO method makes it suitable not only for 1-D array optimization, but also for more complex 2-D array optimization tasks. The optimized arrays demonstrate increased sensitivity, resolution, and stability, as well as superior imaging quality. Empirical results demonstrate that the IQC-AO method can successfully balance the key array metrics such as degradation factor (DF) and redundancy, effectively enhancing computational efficiency and achieving high-performance array optimization. The optimized array configurations show a significant enhancement in imaging quality, confirming the efficacy of the IQC-AO method in advancing SAIR’s imaging capabilities.