多路径识别和缓解用于城市环境中增强的GNSS定位
Qianxia Li1,2, Xue Hou1, Yuanbin Ye1
1Surveying and Mapping Institute Lands and Resource Department Guangdong Province, Guangzhou 510500, China.
Sensors (Basel, Switzerland)
|October 16, 2025
概括
本研究介绍了一种数据驱动的方法,用于检测和减少全球导航卫星系统 (GNSS) 在城市内定位的多路径错误. 该方法使用里埃和波形变换来提高城市位置的准确性.
科学领域:
- 地理学工程 工程地质学
- 信号处理 信号处理
背景情况:
- 城市全球导航卫星系统 (GNSS) 定位面临来自多路径反射和干扰的挑战.
- 在大都市地区,精确的基于位置的服务 (LBS) 需要对这些GNSS信号错误提供强大的解决方案.
研究的目的:
- 开发和验证一种适应性,数据驱动的方法来识别和减轻GNSS在城市环境中的多路径影响.
- 为了提高GNSS定位的准确性和可靠性,在具有挑战性的城市环境中用于LBS定位.
主要方法:
- 利用里叶变换 (FT) 来通过功率频谱分析代码多路径和其他频域错误源.
- 应用波纹分解和信号频谱分析,以检测多层信号分解中的多路径签名.
- 基于识别的多路径特征开发了缓解策略,以重建纠正的GNSS观测.
主要成果:
- 在使用频率和分解技术的GNSS观测中成功识别和描述了多路径效应.
- 证明有效缓解多路径冲击,从而提高定位精度.
- 在现实的城市条件下,在静态和动态场景中验证了拟议的方法.
结论:
- 拟议的适应性,数据驱动的方法为城市地区GNSS多路径缓解的复杂建模提供了可行的替代方案.
- 该方法与现有的定位模型无集成,并与标准导航终端和智能手机显示可行性.
- 这项研究有助于提高GNSS定位在具有挑战性的城市环境中的LBS的稳定性.
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