一种自适应EPF算法及其在光纤水听器中的应用

基于椭圆拟合的相位生成载波(Phase Generated Carrier,PGC)解调方法是消除非线性因素对光纤水听器PGC解调结果影响的一种有效手段,椭圆曲线参数的最优估计问题是实现该方法的关键。扩展卡尔曼粒子滤波(Extended Kalman Particle Filter,EPF)是解决此类非线性估计问题的一种常用的最优估计算法。但传统的EPF算法在用于常参数过程方程的参数或状态估计问题时,过程噪声的方差通常设置为一个常量,这使得算法难以兼顾收敛速度和估计精度,一定程度上限制了算法的整体性能。为了解决这个问题,文章对现有的EPF进行了改进,提出了一种自适应扩展卡尔曼粒子滤波(Adaptive Extended Kalman Particle Filter,AEPF)算法。模拟仿真和实验结果表明,文中所提出的AEPF算法能根据基于椭圆拟合的PGC解调方法有效地解调出待测声信号,相比EKF算法和EPF算法,AEPF算法的收敛速度和估计精度都得到了提升。此外,文章所提出的AEPF算法也适用于其他具有常参数过程方程的参数或状态估计问题,具有一定的通用性。

An adaptive EPF algorithm and its application in optical fiber hydrophone

Phase generated carrier (PGC) demodulation method based on ellipse fitting is an effective method to eliminate the influence of nonlinear factors on the PGC demodulation results of optical fiber hydrophone. The optimal estimation of elliptic curve parameters is the key to realizing this method. Extended Kalman particle filtering (EPF) algorithm is a commonly used optimal estimation algorithm to solve this kind of nonlinear problem. When the traditional EPF algorithm is used for parameter or state estimation of process equations with constant parameters, the variance of process noise is usually set to a constant, which makes the algorithm difficult to take into account the convergence speed and estimation accuracy, and limits the overall performance of the algorithm. In order to solve this problem, the existing EPF algorithm is improved in this paper, and an adaptive extended Kalman particle filtering (AEPF) algorithm is proposed. The results of the simulation and experiment show that the AEPF algorithm proposed in this paper can effectively estimate the parameters of elliptic curve, and can effectively demodulate the acoustic signal to be measured according to the PGC demodulation method of optical fiber hydrophone based on elliptic fitting mentioned in this paper. And the AEPF algorithm has higher convergence rate and higher accuracy than the EKF and EPF algorithms. It should be noted that the AEPF algorithm proposed in this paper is also applicable to other parameter or state estimation problems with constant parameter process equations, and has certain universality.