基于相对信息观测量的INS/USBL非线性组合导航方法

INS/USBL nonlinear integrated navigation method based on observations of relative information

针对传统惯性导航系统/超短基线定位系统(inertial navigation system/ultra short base line,INS/USBL)组合导航利用绝对位置做观测信息存在导航精度较低,且噪声异常引起抗干扰能力弱的问题,提出基于相对信息观测量的INS/USBL非线性组合导航方法。以INS解算的应答器相对于INS在基阵坐标系下的入射角、斜距信息与超短基线输出的入射角、斜距信息之差作为观测量建立量测方程。在改进Sage-Husa算法基础上采用容积规则,设计一种适用于非线性系统的自适应容积卡尔曼滤波估计器。仿真结果表明,该方法定位精度较传统方法提升2.4倍,在噪声异常情况下,滤波收敛,组合导航性能稳定。

To solve the problems of low precision and weak capability of resisting the noise disturbance caused by using traditional inertial navigation system/ultra short base line (INS/USBL) integrated navigation system, an INS/USBL nonlinear integrated navigation method based on observations of relative information is proposed. An observation equation is introduced based on difference between two incidence angles and between two slant ranges which are respectively resolved by INS and USBL . Then, an adaptive noise statistics estimator designed for nonlinear systems is derived by applying the cubature rule based on the modified Sage-Husa algorithm. Simulation results show that, the positioning precision of the proposed algorithm is 2.4 times of that of the traditional algorithm. In the circumstance of unusual noise, the filter has better convergence and the system has better stability.