An Iterative Extended Kalman Filter for Coherent Measurements of Incoherent Network Nodes in Positioning Systems
An Iterative Extended Kalman Filter for Coherent Measurements of Incoherent Network Nodes in Positioning Systems
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用于定位系统中非相干网络节点相干测量的迭代扩展卡尔曼滤波器
DOI：
10.1109/access.2020.2975290
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
und M. Vossiek
中科院分区：
文献类型：
--
作者：
M. Hehn;E. Sippel;und M. Vossiek
许多定位和跟踪应用使用空间分布的传感器站，每个传感器站都配备了相干测量通道。每个节点的相干数据集被非相干地测量到所有其他节点的数据集，从而避免了站之间昂贵的同步过程。通常，通过将非相干测量的复值数据映射到诸如到达角或接收信号强度之类的实值数据来评估测量。在此预处理步骤之后，递归滤波对实值数据进行融合以估计系统状态。遗憾的是，即使原始测量是在加性高斯白噪声环境中执行的，预处理步骤也会导致相关的噪声形状误差，其方差依赖于系统状态。因此，违反了卡尔曼滤波中常见的加性高斯白噪声假设。因此，本文提出了一种迭代扩展卡尔曼滤波，它通过复值测量模型估计非线性实值系统的状态，该复值测量模型由非相干传感器站组成，每个传感器站具有多个相干测量通道。由于所提出的迭代扩展卡尔曼滤波非常适合于具有多个站的分布式定位系统，因此在仿真中通过两个传感器站来定位发射机，每个传感器站在四个通道上测量接收信号的幅度和相位。为了说明该算法的优点，将使用该算法的直接测量估计与估计每个传感器站的接收信号强度和到达角的卡尔曼滤波进行了比较。最后，在仿真场景中加入了反射墙，以演示所提出的卡尔曼滤波的灵活性。
Many positioning and tracking applications use spatially distributed sensor stations, each equipped with coherent measurement channels. The coherent data set of each node is incoherently measured to the data sets of all other nodes, avoiding expensive synchronization procedures between the stations. Usually, the measurements are evaluated by mapping the incoherently measured complex valued data on real valued data like angle of arrival or received signal strength. After this preprocessing step, recursive filters fuse the real valued data to estimate a system state. Unfortunately, even though the original measurements are performed in additive white Gaussian noise environments, the preprocessing step can result in correlated, noise shaped errors, whose variance is system state dependent. Hence, the additive white Gaussian noise assumption, which is commonly drawn in Kalman filters, is violated. Therefore, this paper proposes an iterative extended Kalman filter, which estimates the state of a nonlinear real valued system via a complex valued measurement model that consists of incoherent sensor stations, each with several coherent measurement channels. Since the proposed iterative extended Kalman filter is well suited for distributed positioning systems with several stations, a transmitter is localized in a simulation via two sensor stations, each measuring the received signal's amplitude and phase at four channels. To illustrate the advantages of the proposed algorithm, the direct measurement evaluation using the proposed algorithm is compared to a Kalman filter that evaluates the received signal strengths and angle of arrivals at each sensor station. Finally, a reflecting wall is incorporated into the simulation scenario to demonstrate the flexibility of the proposed Kalman filter.
高精度雷达测距与无线单元同步方法
DOI：
--
发表时间：
2007
期刊：
2007 IEEE/MTT-S International Microwave Symposium
影响因子：
--
作者：
S. Roehr;M. Vossiek;P. Gulden
通讯作者：
P. Gulden
基于仅轴承扩展卡尔曼滤波器的工业自动化无线 3D 定位概念
DOI：
--
发表时间：
2018
期刊：
Asia-Pacific Microwave Conference
影响因子：
--
作者：
Melanie Lipka;Erik Sippel;M. Hehn;J. Adametz;M. Vossiek;Yassen Dobrev;P. Gulden
通讯作者：
P. Gulden