多传感器组合导航系统的多尺度异步信息融合算法

首先,将状态方程采用数据块变换的方式得到新的状态块方程,并将量测方程表达为数据块的形式;然后,将量测向量进行多层小波变换以得到新的量测向量,结合状态块方程进行卡尔曼滤波;最后,利用异步贯序滤波的方法,建立了基于全局的最优估计值。将上述算法应用于GPS/SST/高度表/SINS多组合导航系统,仿真结果表明:相对于单一尺度的异步滤波算法,该算法可明显地提高系统的滤波精度。

Muliti-Scale Asynchronous Information Fusion Algorithm of Multi-Sensor Integrated Navigation System

At first, data-block transformation technique was used to change the original state equation into the new state-block equation, and the original measurement equation is expressed into the form of data-block. After that, the multi-layer wavelet transformation technique was used to the original measurement vector to achieve the new measurement vector which went into the Kalman filter with the state-block equation. At last. the optimal estimated data of the global information based on asynchronous filtering technique was built. The above algorithm could be applied to GPS/SST/altimeter/SINS integrated navigation system, and the simulated results showed that this algorithm could increase the filtering precision more than the singular-scale asynchronous filtering algorithm.