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A New On-line Systematic Errors Registration Method

机译:新的在线系统错误注册方法

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In complex surveillance system, it is important to register sensor measurement with systematic errors. If measurements are not corrected, it leads to degradation in track accuracy. It is vital to estimate systematic errors, especially, it is necessary to estimate systematic errors with unknown prior knowledge. In this paper, a novel registration method named EX-UI (exact-unknown input) is proposed to estimate systematic errors. Firstly, we transform measurements from sensors and target state into pseudomeasurements, and utilize exact method (EX) method to conceive system including pseudomeasurement model and systematic errors model with unknown input (UI). Next, we design decoupled filter based on above system. Finally, the systematic errors are estimated by minimum variance unbiased (MVU) theory. Simulation results demonstrate that the systematic errors with unknown prior knowledge can be exactly estimated using proposed method, and it is convergent and outperforms other method.
机译:在复杂的监控系统中,重要的是通过系统误差注册传感器测量。如果未纠正测量,则会导致轨道精度下降。估计系统错误至关重要,特别是,有必要估计具有未知事先知识的系统错误。本文提出了一种名为EX-UI(精确未知输入)的新颖注册方法来估计系统错误。首先,我们将传感器和目标状态的测量变换为假瘤,并利用精确的方法(例如)方法来构思,包括具有未知输入(UI)的伪烹调模型和系统错误模型。接下来,我们根据上述系统设计解耦过滤器。最后,通过最小差异(MVU)理论来估计系统误差。仿真结果表明,使用所提出的方法可以完全估计未知的先验知识的系统误差,并且它是会聚和越优于其他方法。

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