综合权值递推最小二乘法估计从UUV航行参数

根据主UUV观测系统测量的从UUV方位信息精度高、距离信息精度低的特点,将遗忘因子和位置权值构成的综合权值融入递推最小二乘算法(RLS)用于从UUV航行参数分析,避免采用EKF算法对观测噪声要求高的缺陷,克服数据饱和现象。同时对从UUV方位信息进行预处理以提高航行参数估计的收敛速度。仿真实验证明了方法的有效性。

For the bearing measurements precision is high, and range measurements precision is low in the underwater observing system, both the forgetting factor and slave-UUV position weight which are called synthetical weights are brought forward into the recursive least squares(RLS) estimator for applying into slave-UUV motion analysis. This mean can avoid the disadvantage of EKF algorithm which is strict to observing noises, and hurdle the data saturation in the RLS algorithm. The pre-process of bearing is also presented for improving the convergent performance of the estimator. Simulation experiments show the validity of the method.