Abstract
On the premise of guaranteeing high-quality measurement data, active wireless localization (A-WL) locates the target by at least three anchor nodes (ANs) with known coordinates, while passive wireless localization (P-WL) requires more ANs. In addition, P-WL requires a cumbersome training process to maintain the robustness in application scenarios as much as possible. However, the optimal deployment of ANs is not an easy task, and the application scenario will not remain unchanged. Therefore, a lightweight localization system that satisfies the localization accuracy requirements and can be quickly deployed should be one of the preferred solutions for WL. In this paper, we propose a single-anchor localization system based on continuous time-of-arrival (TOA) measurement. Specifically, we fix the AN on the blade with uniform rotation, construct the time-length distribution map by using the cyclically varying TOA caused by blade rotation, and intercept it according to the rotation period. We extract the change angle and distance information from the intercepted data in real time to achieve single-anchor localization. Meanwhile, we also construct a support vector machine classifier to identify the line-of-sight state of each interception period to assist the angle estimation in harsh environments and further improve the adaptability of the system. Experimental results show that the line-of-sight recognition accuracy of higher than 92% under continuous movement, and the average localization error of less than 0.6m. The average localization error is less than 0.3m in the mixed motion state.
Highlights
R ESEARCH in the filed of wireless indoor localization has attracted extensive attention over the past decade, especially in complex indoor environments, where it is often necessary to locate personnel, facilities and items to meet the needs for location and navigation information [1]– [3]
Using the variation rule of TOA measurement during rotation and its relation with the rotation period, distance calculation and angle estimation are completed simultaneously. This makes it feasible to achieve target localization with only one single antenna anchor nodes (ANs). 2) We propose an angle reconstruction strategy based on support vector machine (SVM) classification
3) We develop a localization platform based on UWB hardware, and implement the proposed method on the platform to validate its performance in different indoor scenarios with extensive experiments
Summary
R ESEARCH in the filed of wireless indoor localization has attracted extensive attention over the past decade, especially in complex indoor environments, where it is often necessary to locate personnel, facilities and items to meet the needs for location and navigation information [1]– [3]. We propose a single-anchor localization scheme based on periodic rotation and continuous TOA measurements. We calculate the distance of the target from the axis and the time interval between the minimum TOA measurements in the adjacent rotation period. Using the variation rule of TOA measurement during rotation and its relation with the rotation period, distance calculation and angle estimation are completed simultaneously This makes it feasible to achieve target localization with only one single antenna AN. We construct a SVM classifier to identify the line-of-sight state of each intercepted measurement period On this basis, we save and update the angle estimation results corresponding to the latest three LOS states in real time, and use them for the angle reconstruction process caused by severe NLOS. If the above conditions still cannot be satisfied, the measurements of t+1-th rotation period should be added, and the measurements of rotation period t and t+1 will be merged to find ∆Tmin and ∆Tmax again according to the above restriction conditions
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