Time delay-based the 5th Generation Mobile Communication Technology (5G) positioning is a main method to perform high-precision positioning in Global Navigation Satellite System (GNSS) denied areas. However, in practical applications, the occlusion of signals in a complex environment results in few observable base stations, which affects the reliability and accuracy of positioning. The aim of this study is to improve the performance of the 5G positioning in complex environments with an insufficient number of observable base stations. First, the Angle of Departure (AOD) capability of multi-antennas is integrated into Multi-Round-Trip-Time (Multi-RTT) positioning, establishing a novel 5G RTT/AOD positioning model. Then, the influencing factors of positioning performance, including the Dilution of Precision (DOP) and the accuracy of the AOD measurements, is analyzed. The relationship between DOP and RTT/AOD positioning accuracy is deduced. Afterwards, simulation experiments are performed on 5G positioning with the Multi-RTT and RTT/AOD methods in two scenarios with good and complex environments. The theoretical analysis and experimental results show that 5G positioning with the RTT/AOD method increases the horizontal and vertical accuracies by approximately 25 and 65%, respectively, compared with the Multi-RTT method. The positioning reliability is also greatly improved. The proposed model can well solve the inefficiency of 5G positioning with the RTT method in scenarios where the number of base stations is less than three.

中文翻译：

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利用多天线角度测量提高 5G 定位性能

基于时间延迟的第五代移动通信技术（5G）定位是在全球导航卫星系统（GNSS）拒绝区域进行高精度定位的主要方法。但在实际应用中，复杂环境下的信号遮挡导致可观测基站少，影响定位的可靠性和准确性。本研究的目的是在可观测基站数量不足的复杂环境中提高 5G 定位的性能。首先，将多天线的出发角（AOD）能力集成到Multi-Round-Trip-Time（Multi-RTT）定位中，建立一种新颖的5G RTT/AOD定位模型。然后，定位性能的影响因素，包括精度稀释 (DOP) 和 AOD 测量的准确性，进行了分析。推导了DOP与RTT/AOD定位精度的关系。随后，分别在良好和复杂的两种场景下，分别使用 Multi-RTT 和 RTT/AOD 方法对 5G 定位进行了仿真实验。理论分析和实验结果表明，与Multi-RTT方法相比，RTT/AOD方法的5G定位水平和垂直精度分别提高了约25%和65%。定位可靠性也大大提高。该模型可以很好地解决5G在基站数量小于3的场景下RTT定位效率低的问题。随后，分别在良好和复杂的两种场景下，分别使用 Multi-RTT 和 RTT/AOD 方法对 5G 定位进行了仿真实验。理论分析和实验结果表明，与Multi-RTT方法相比，RTT/AOD方法的5G定位水平和垂直精度分别提高了约25%和65%。定位可靠性也大大提高。该模型可以很好地解决5G在基站数量小于3的场景下RTT定位效率低的问题。随后，分别在良好和复杂的两种场景下，分别使用 Multi-RTT 和 RTT/AOD 方法对 5G 定位进行了仿真实验。理论分析和实验结果表明，与Multi-RTT方法相比，RTT/AOD方法的5G定位水平和垂直精度分别提高了约25%和65%。定位可靠性也大大提高。该模型可以很好地解决5G在基站数量小于3的场景下RTT定位效率低的问题。理论分析和实验结果表明，与Multi-RTT方法相比，RTT/AOD方法的5G定位水平和垂直精度分别提高了约25%和65%。定位可靠性也大大提高。该模型可以很好地解决5G在基站数量小于3的场景下RTT定位效率低的问题。理论分析和实验结果表明，与Multi-RTT方法相比，RTT/AOD方法的5G定位水平和垂直精度分别提高了约25%和65%。定位可靠性也大大提高。该模型可以很好地解决5G在基站数量小于3的场景下RTT定位效率低的问题。