基于异质多传感器的网络分布数据融合的一种算法

An algorithm of the fusion of network data based on multi-sensor heterogeneity distribution

针对多异质传感器数据融合能够实现信息互补,改善目标跟踪精度,提出了一种异质多传感器异步量测融合算法,即首先将量测方程线性化,再在融合中心通过建立伪量测方程,得到同步的量测数据,然后利用噪声相关的伪序贯思想进行融合处理得到全局估计,与现有算法进行仿真比较,结果表明了该算法的有效性。

Due to heterogeneous sensors＇ implementation of information complementary, improvement of target tracking precision, a asynchronous measurement fusion algorithms is proposed in this paper. The process is as following ： First step is linearization of the measurement equation.. Synchronous data are obtained secondly by building pseudo measurement equation at the fusion center. Finally, since correlation of process noise and pseudo noise, the filter towards one-step correlated noise and measurement noise is utilized to achieve the optimal state estimate. Simulation instance is provided to compare the new algorithm with the existing approach. The results show that the optimality of the new algorithm is developed in this paper.