蚁群算法中参数设置对超声回波估计性能的影响

The effects of parameters settings of ant colony algorithm on the performance of ultrasonic echo estimation

针对超声回波参数估计问题存在着耗机时长,估计结果严重依赖于初始值的缺点,本文将蚁群算法应用到超声回波参数估计中,结合超声回波的非线性高斯模型,提出了基于蚁群算法的超声回波参数估计算法,并就蚁群算法在超声回波估计中参数的优化组合设置进行了分析研究.通过数值仿真,在信噪比为10 dB条件下计算了蚁群算法中各参数的不同取值对估计结果的不同影响,包括计算时间、估计精度和算法稳定性,得出了算法中各参数的组合优化设置,给出了最优参数下的超声回波参数估计结果,并通过与其他算法的比较验证了蚁群算法在超声回波参数估计问题中的有效性.该研究有助于提高超声回波估计的精度和算法的稳定性,缩短蚁群算法的计算时间,以达到优化算法性能的目的.

The computational time and the estimated results of other algorithms for ultrasonic echoes depend significantly on the initial values. In this investigation, we develop an algorithm based on the ant colony algorithm to estimate ultrasonic signals in term of a nonlinear Gaussian echo model. Fhrthermore, the combinatorial optimization settings of the parameters for the ant colony algorithm are analyzed and investigated. The effect that each parameter has on the estimated results, including the computational time, estimation accuracy, and the stability of the algorithm, are analyzed. Optimal parameter settings are achieved through numerical simulation with an SNR （signal to noise ratio） of 10 dB. The estimated results are given according to tile optimal parameter settings. Compared with other algorithms, the effectiveness of the ant colony algorithm applied to parameter estimation is verified. This investigation contributes to improving the accuracy of estimation of ultrasonic echoes and the stability of the algorithm. The computational time can be reduced effectively and good estimation performance is obtained by the algorithm.