乘性噪声背景下基于非线性渐消滤波的单信标测距定位算法  

Single Beacon Location Algorithm Based on Nonlinear Fading Filter Under Multiplicative Noise Background

作　　者：朱子尧 韩树平[1] 郭正东[1] 刘建波[1] ZHU Ziyao;HAN Shuping;GUO Zhengdong;LIU Jianbo(Navy Submarine Academy,Qingdao 266044,China)

机构地区：[1]海军潜艇学院,青岛266044

出　　处：《电子与信息学报》2019年第1期165-171,共7页Journal of Electronics & Information Technology

摘　　要：针对基于加性噪声模型的单信标测距定位算法不能精确表征距离观测量的实际特征,存在模型失配的问题,该文给出一种考虑乘性噪声特性的联合最小二乘法和非线性渐消滤波的两步定位算法。在分析有效声速误差与距离观测量乘性噪声内在联系的基础上,建立了乘性噪声背景下的测距误差模型,通过引入一种新的弱化因子计算方法对乘性噪声背景下带单重渐消因子的非线性渐消滤波算法进行了改进,利用基于最小二乘法的预定位过程解决改进算法对初值敏感的问题。仿真及试验数据表明该算法在水下航行器接近信标的态势下定位精度明显优于加性噪声背景下的扩展卡尔曼滤波算法。Single beacon location algorithm based on additive noise model can not accurately represent the actual characteristics of distance measurement,leading to a problem of model mismatch.A two step location algorithm considering the multiplicative noise characteristics is presented,which combines least squares algorithm and nonlinear fading filter.A range error model in the background of multiplicative noise is established based on the analysis of the effective sound velocity error.The nonlinear fading filtering algorithm with single fading factor under multiplicative noise background is improved by introducing the attenuation factor which increases the track continuity.Using the least squares based pre-location process to solve the problem that the improved algorithm is sensitive to the initial value.The simulation and experimental data show that the location precision of the proposed algorithm is obviously better than the extended Kalman filtering algorithm under the additive noise background.

关 键 词：单信标测距定位 乘性噪声 渐消因子 非线性滤波 有效声速 

分 类 号：TB568[交通运输工程—水声工程]