Tensor Data Conformity Evaluation for Interference-Resistant Localization

Tensor Data Conformity Evaluation for Interference-Resistant Localization
复制标题

DOI:
10.1109/ieeeconf44664.2019.9048697
复制
发表时间:
2019-11
期刊:
2019 53rd Asilomar Conference on Signals, Systems, and Computers
影响因子:
--
通讯作者:
Konstantinos Tountas;G. Sklivanitis;D. Pados;M. Medley
Konstantinos Tountas;G. Sklivanitis;D. Pados;M. Medley
中科院分区:
其他
文献类型:
--
作者:
Konstantinos Tountas;G. Sklivanitis;D. Pados;M. Medley

文献摘要

被引文献

相似文献

我们考虑在 GPS 拒绝的环境中稳健、抗干扰定位的问题。每个要自我定位的资产都配备了天线阵列,并利用来自放置在已知位置的锚节点的时域编码信标信号。随着时间的推移在天线阵列上收集的数据快照被组织在张量数据结构中。通过对 L1 范数张量子空间返回的稳健、高置信度数据特征表征进行迭代投影来评估接收到的张量数据的一致性。不合格的张量板更有可能因干扰而受到不规则、高度偏差的测量的污染,因此它们会从接收到的数据集中被删除。随后,我们通过在一致性调整数据集上使用 L2 范数和 L1 范数张量分解技术来估计信标信号的到达方向。最后,通过三角测量来估计资产与锚节点的相对位置。我们考虑在室内实验室环境中使用 2.4 GHz ISM 频段的射频信号对两个锚节点、一个干扰源和一项资产进行自定位。我们根据软件定义无线电测试台的到达角估计精度实验测量来评估所提出的定位系统的性能。
We consider the problem of robust, interference-resistant localization in GPS-denied environments. Each asset to be self-localized is equipped with an antenna array and leverages time-domain coded beacon signals from anchor nodes that are placed at known locations. Collected data snapshots over time at the antenna array are organized in a tensor data structure. The conformity of the received tensor data is evaluated through iterative projections on robust, high-confidence data feature characterizations that are returned by L1-norm tensor subspaces. Non-conforming tensor slabs are more likely to be contaminated by irregular, highly deviating measurements due to interference, thus they are removed from the received dataset. Subsequently, we estimate the direction-of-arrival of the beacon signals by using L2-norm and L1-norm tensor decomposition techniques on the conformity-adjusted dataset. Finally, the relative position of the asset to the anchor nodes is estimated via triangulation. We consider two anchor nodes, one interferer, and one asset to be self-localized using radio frequency signals at the 2.4 GHz ISM band in an indoor laboratory environment. We evaluate the performance of the proposed localization system in terms of angle-of-arrival estimation accuracy experimental measurements from a software-defined radio testbed.