基于FOA-LM算法的超声回波信号参数估计

在超声回波参数估计中,搜索莱文伯格一马夸特(Levenberg-Marquard,LM)算法的最优解会受到迭代初值与参数向量真实解接近程度的影响。针对LM算法对迭代初值敏感的问题,提出了果蝇优化算法(Fruit fly optimization algorithm,FOA)算法和LM算法结合的参数估计方法。该方法充分利用FOA算法善于进行全局搜索和LM算法善于进行局部快速搜索的优点,首先使用FOA算法求出超声回波信号的参数初值,然后利用这组初值进行LM法迭代搜索。仿真结果表明,基于FOA和LM算法相结合的方法,具有收敛速度快,精度高的特点。

Parameters estimation of ultrasonic echo signal based on fruit fly optimization and leveoberg marquardt algorithm

In ultrasonic echo signal parameters estimation tasks, Levenberg Marquardt(LM) methodis sensitive to initialization in parameters estimation of ultrasonic echo signal. To address this issue, a combined method of Fruit Fly Optimization Algorithm (FOA) and Levenberg Marquardt Method was proposed. FOA is effective in global solution space searching. FOA was used to solve the initial values of the ultrasonic echo parameters at first. Then, LM iteration search based on these initial values was adopted. Simulation results show that the combination of FOA and LM obtains a fast convergence and a high precision.