Centre for Automation and Robotics (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Ctra. Campo Real km 0.2, La Poveda, Arganda del Rey, 28500 Madrid, Spain.
Sensors (Basel). 2021 Mar 4;21(5):1787. doi: 10.3390/s21051787.
The location of people, robots, and Internet-of-Things (IoT) devices has become increasingly important. Among the available location technologies, solutions based on ultrawideband (UWB) radio are having much success due to their accuracy, which is ideally at a centimeter level. However, this accuracy is degraded in most common indoor environments due to the presence of obstacles which block or reflect the radio signals used for ranging. One way to circumvent this difficulty is through robust estimation algorithms based on measurement redundancy, permitting to minimize the effect of significantly erroneous ranges (outliers). This need for redundancy often conflicts with hardware restraints put up by the location system's designers. In this work, we present a procedure to increase the redundancy of UWB systems and demonstrate it with the help of a commercial system made by Decawave. This system is particularly easy to deploy, by configuring a network of beacons (anchors) and devices (tags) to be located; however, its architecture presents a major disadvantage as each tag to be located can only measure ranges to a maximum of four anchors. This limitation is embedded in the Positioning and Networking Stack (PANS) protocol designed by Decawave, and therefore is not easy to bypass without a total redesign of the firmware. In this paper, we analyze the strategies that we have been able to identify in order to provide this equipment with multiple range measurements, and thus enable each tag to be positioned with more than four measured ranges. We will see the advantages and disadvantages of each of these strategies, and finally we will adopt a solution that we implemented to be able to measure up to eight ranges for each mobile device (tag). This solution implies the duplication of the tags at the mobile user, and the creation of a double interleaved network of anchors. The range among tags and the eight beacons is obtained through an API via a wireless BLE protocol at a 10 Hz rate. A robustified Extended Kalman filter (EKF) is designed to estimate, by trilateration, the position of the pair of mobile tags, using eight ranges. Two different scenarios are used to make localization experimentation: a laboratory and an apartment. Our position estimation, which exploits redundant information and performs outlier removal, is compared with the commercial solution limited to four ranges, demonstrating the need and advantages of our multi-range approach.
人的位置、机器人和物联网 (IoT) 设备的位置变得越来越重要。在可用的定位技术中，基于超宽带 (UWB) 无线电的解决方案由于其精度而非常成功，其精度理想情况下可达到厘米级。然而，由于障碍物会阻挡或反射用于测距的无线电信号，因此这种精度在大多数常见的室内环境中会降低。一种解决此问题的方法是通过基于测量冗余的稳健估计算法，从而可以最小化显著错误范围 (异常值) 的影响。这种对冗余的需求通常与定位系统设计人员所施加的硬件限制相冲突。在这项工作中，我们提出了一种增加 UWB 系统冗余度的方法，并通过使用由 Decawave 制造的商业系统来证明该方法的可行性。该系统特别易于部署，只需配置要定位的信标 (锚点) 和设备 (标签) 网络即可；但是，其架构存在一个主要缺点，即每个要定位的标签只能测量到最多四个锚点的距离。这种限制嵌入在 Decawave 设计的定位和网络堆栈 (PANS) 协议中，因此，如果不彻底重新设计固件，则不容易绕过。在本文中，我们分析了我们能够确定的策略，以便为该设备提供多个距离测量值，从而能够使用超过四个测量的距离对每个标签进行定位。我们将看到每种策略的优缺点，最后我们将采用我们实施的解决方案，以便能够为每个移动设备 (标签) 测量多达八个距离。此解决方案意味着在移动用户处复制标签，并创建双交错的锚点网络。标签之间的距离和八个信标是通过通过无线 BLE 协议以 10 Hz 的速率通过 API 获得的。设计了鲁棒化的扩展卡尔曼滤波器 (EKF)，通过三边测量法，使用八个范围来估计移动标签对的位置。使用两种不同的场景进行定位实验：实验室和公寓。我们的位置估计利用冗余信息并执行异常值去除，与限于四个范围的商业解决方案进行比较，证明了我们的多范围方法的必要性和优势。
