摘要
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。
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.
出处
《海军航空工程学院学报》
2012年第3期276-280,共5页
Journal of Naval Aeronautical and Astronautical University
基金
国家自然科学基金资助项目(60874112)
关键词
多传感器组合
导航系统
多尺度
异步信息融合算法
multi-sensor integrated
navigation system
multi-scale
asynchronous information fusion algorithm
