基于陆地和基于卫星的定位的融合,使用受约束的加权最小平方
Paihang Zhao1, Linqiang Jiang1, Tao Tang1
1Institute of Information Engineering, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China.
Sensors (Basel, Switzerland)
|April 27, 2024
概括
这项研究引入了一种代算法,通过融合陆基短波和卫星数据来提高军事定位的准确性. 这种新的方法提高了精度,实现了近乎最佳的性能,并且性能优于单源本地化系统.
科学领域:
- 地理学工程 工程地质学
- 信号处理 信号处理
- 导航系统 导航系统
背景情况:
- 准确的本地化对于军事应用至关重要,目前的方法依赖于各种平台,如陆基短波系统和卫星.
- 短波和卫星定位都容易出现特定的错误:短波的电离层反射高度错误,卫星系统的卫星位置错误.
- 现有的本地化技术往往难以有效地减轻这些错误,从而影响系统的整体精度.
研究的目的:
- 开发和验证使用陆基短波平台和卫星进行融合本地化的一种新算法.
- 解决和减轻与电离层反射高度和局部化系统中的卫星位置相关的重大错误.
- 为了提高整体本地化准确度,超出了单个系统可以实现的准确度.
主要方法:
- 开发了一种代约束加权最小方程 (ICWLS) 算法,以处理电离层反射高度和卫星位置错误.
- ICWLS算法通过代改进将非凸式方程约束转化为线性约束,确保对全球最佳解决方案的趋同.
- 卡尔曼过被用来融合来自短波和卫星方法的本地化结果.
主要成果:
- 拟议的ICWLS算法证明了接近受约束的克拉梅尔-拉奥下界 (CCRLB) 的定位精度.
- 模拟证实了ICWLS算法在缓解短波和卫星定位中的特定错误源的有效性.
- 与依赖单一定位方法的系统相比,合并定位系统实现了更高的准确性.
结论:
- 开发的ICWLS算法有效地解决了短波和卫星定位中的关键错误来源,显著提高了准确性.
- 使用卡尔曼过的融合本地化,与ICWLS算法相结合,提供了一个强大的,高度准确的导航解决方案.
- 这项研究在军事定位技术方面取得了重大进展,为更可靠,更精确的定位系统铺平了道路.
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