Microwave Staring Correlated Imaging (MSCI) is a newly proposed computational high-resolution imaging technique. The imaging performance of MSCI with the existence of modeling errors depends on the properties of the imaging matrix and the relative perturbation error resulted from existing errors. In conventional transient-radiation-fields-based MSCI, which is commonly accomplished by utilizing random frequency-hopping (FH) waveforms, the multiple transmitters should be controlled individually and simultaneously. System complexity and control difficulty are hence increased, and various types of modeling errors are introduced as well. The computation accuracy of radiation fields is heavily worsened by the modeling errors, and the transient effect makes it hard to take direct and high-precision measurements of the radiation fields and calibrate the modeling errors with the measuring result. To simplify the system complexity and reduce error sources, in this paper, steady-radiation-fields-sequence-based MSCI (SRFS-MSCI) method is proposed. The multiple transmitters are excited with coherent signals at the same observation moment, with the signal frequency varying in the whole frequency band during the imaging process. By elaborately designing the array configuration and the amplitude and phase sequences of the coherent transmitters, the SRFS-MSCI is thus implemented. Comparing the system architecture of the proposed SRFS-MSCI with the conventional random FH-based MSCI, it can be found that the proposed method significantly reduces the number of baseband modules and simplifies the system architecture and control logic, which contributes to reducing error sources such as baseband synchronization errors and decreasing deterioration caused by error cascade. To further optimize the design parameters in the proposed SRFS-MSCI system, the Simulated Annealing (SA) algorithm is utilized to optimize the amplitude sequences, the phase sequences, and the antenna positions individually and jointly. Numerical imaging experiments and real-world imaging experiment demonstrate the effectiveness of the proposed SRFS-MSCI method that recognizable high-resolution recovery results are obtained with simplified system structure and optimized system parameters.
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