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引用次数: 24
摘要
现实生活中的工业环境对当今基于无线电的定位系统提出了挑战,因为无线电信道受到环境中存在的多重干扰的高度影响。因此,本文提出了一种基于RSSI (Received Signal Strength Indicator,接收信号强度指标)对ToA(到达时间)测距测量产生加权多重位置估计的解决方案,以增强测距系统的容错性,降低测距系统的自干扰,最终提高位置估计的精度。本文提出了一种基于三维光线追踪结果的坐标下降算法。应用的三维环境模型非常复杂,因为它是通过三维激光扫描测量生成的。在最后的优化步骤中,通过功率电平调整来进一步提高定位系统的精度。最后,基于仿真、数值优化和工业目标环境实验测量的性能评估将证明我们的综合方法在准确性和鲁棒性方面的改进。
A comprehensive approach for optimizing ToA-localization in harsh industrial environments
Real-life industrial environments pose a challenge for today's radio-based localization systems, as the radio channel is highly affected by the multiple interference present in the environment. Therefore, this paper presents a solution for generating Weighted Multilateration Position Estimation based on the RSSI (Received Signal Strength Indicator) for ToA (Time of Arrival) ranging measurements to enhance the fault tolerance, reduce the self-interference of the ranging system and finally enhance the accuracy of the position estimation. A coordinate descent algorithm for optimal anchor placement is demonstrated in this paper, which is based on results of 3D ray tracing. The applied 3D environment model is highly sophisticated, as it was generated by 3D laser scanning for gauging. In a final optimization step, power level adjustment is shown to further enhance the accuracy of the localization system. Concluding, a performance evaluation based on simulations, numerical optimization and experimental measurements in the industrial target environment will demonstrate the improvements of our comprehensive approach in terms of accuracy and robustness.