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Accuracy Analysis in Sensor Networks for Asynchronous Positioning Methods

机译:异步定位方法传感器网络的准确性分析

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The accuracy requirements for sensor network positioning have grown over the last few years due to the high precision demanded in activities related with vehicles and robots. Such systems involve a wide range of specifications which must be met through positioning devices based on time measurement. These systems have been traditionally designed with the synchronization of their sensors in order to compute the position estimation. However, this synchronization introduces an error in the time determination which can be avoided through the centralization of the measurements in a single clock in a coordinate sensor. This can be found in typical architectures such as Asynchronous Time Difference of Arrival (A-TDOA) and Difference-Time Difference of Arrival (D-TDOA) systems. In this paper, a study of the suitability of these new systems based on a Cramér-Rao Lower Bound (CRLB) evaluation was performed for the first time under different 3D real environments for multiple sensor locations. The analysis was carried out through a new heteroscedastic noise variance modelling with a distance-dependent Log-normal path loss propagation model. Results showed that A-TDOA provided less uncertainty in the root mean square error (RMSE) in the positioning, while D-TDOA reduced the standard deviation and increased stability all over the domain.
机译:由于与车辆和机器人相关的活动所需的高精度,传感器网络定位的精度要求在过去几年中增长。这种系统涉及广泛的规格,必须通过基于时间测量来通过定位设备满足。这些系统传统上设计了它们的传感器的同步,以计算位置估计。然而,该同步在坐标传感器中的单个时钟中的测量中的集中来介绍时间确定中的误差。这可以在典型的架构中找到,例如到达时的异步时间差(A-TDOA)和到达(D-TDOA)系统的差分时间差。本文首次在多个传感器位置执行基于CRAMÉR-RAO下限(CRLB)评估的基于CRAMÉR-RAO下限(CRLB)评估的适用性的研究。通过具有距离依赖性日志正常路径损耗传播模型的新的异源噪声方差模型进行分析。结果表明,A-TDOA在定位中的根均方误差(RMSE)中提供的不确定性较差,而D-TDOA降低了域中所有稳定性的标准偏差和增加的稳定性。

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