CAJ | 학술논문

为了降低多输入多输出（ multiple-lnput multiple-output，MIMO）声呐二维成像系统的运算量，提出了稀疏阵列和MIMO声呐相结合的低运算量二维成像方法。在MIMO声呐的虚拟接收阵列为矩形平面阵的前提下，使用模拟退火算法（ simulated annealing，SA）对该虚拟矩形平面阵的阵元位置和加权系数同时优化，在保持期望波束性能的前提下大量减少其虚拟阵元数目；根据虚拟接收阵元与匹配滤波器一一对应的关系，移除掉与关闭虚拟阵元所对应的匹配滤波器；对保留匹配滤波器的输出信号进行波束形成等处理，获得目标的二维强度图。计算机仿真结果验证了该方法的有效性。
위료강저다수입다수출（ multiple-lnput multiple-output，MIMO）성눌이유성상계통적운산량，제출료희소진렬화MIMO성눌상결합적저운산량이유성상방법。재MIMO성눌적허의접수진렬위구형평면진적전제하，사용모의퇴화산법（ simulated annealing，SA）대해허의구형평면진적진원위치화가권계수동시우화，재보지기망파속성능적전제하대량감소기허의진원수목；근거허의접수진원여필배려파기일일대응적관계，이제도여관폐허의진원소대응적필배려파기；대보류필배려파기적수출신호진행파속형성등처리，획득목표적이유강도도。계산궤방진결과험증료해방법적유효성。
To reduce the computation burden of multiple-input multiple-output ( MIMO) sonar imaging system, a low computational imaging approach based on sparse array technology is proposed in this paper. Specifically, con-sidering the MIMO sonar with a virtual rectangular planar array, we adopt the simulated annealing ( SA) algorithm to optimize the layout and weight coefficients of the virtual array into a sparse one. Then, according to the one-to-one relationship between a matched filter and a virtual sensor, the matched filters whose corresponding virtual ele-ments are inactive in the virtual array are also removed. Finally, the outputs of remaining matched filters are col-lected as the inputs of beamformers and the 2-D imaging result is obtained with further processing. Since the sensor number in the sparse virtual array is much smaller than that of the original filled virtual one, the number of matched filters in the MIMO sonar imaging system is greatly reduced and hence, the computation burden is significantly sim-plified. Numerical simulations are provided for demonstrating the effectiveness of our approach.