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应用一种时域高频后向散射模型,对黄渤海41个站位的20 kHz单波束测深仪回波数据进行了沉积层地声参数反演底质分类研究。采用下山单行模拟退火算法(SIMPSA)对模型输出和接收回波的平均包络曲线进行最大似然匹配,估计海底沉积层的平均颗粒度。实验数据处理表明:对接收回波包络进行能量归一化处理有效地减小了由实验不确定性所导致的回波幅度异常起伏,将反演参数的方差降低至未加处理的50%;平均颗粒度的反演最优值与沉积层样本实验室测量值的一致性更高;将反演结果用于底质分类,正确识别率达到75.6%。
A time domain high frequency backscattering model was applied to study the inversion of ground acoustic parameters of 20 kHz single-beam echo sounder echo data from 41 stations in the Yellow Sea and the Bohai Sea. The maximum likelihood of the average envelope curve of the model output and the received echo was estimated by SIMPSA. The average particle size of the sediment was estimated. Experimental data processing shows that the energy normalization of the received echo envelope can effectively reduce the undulation of the echo amplitude caused by the experimental uncertainty and reduce the variance of the inversion parameters to 50% of the unprocessed ones. The average particle size of the inversion optimal value and sediment layer sample laboratory measurements are more consistent; the inversion results for the sediment classification, the correct recognition rate of 75.6%.