Kalman filtering with noncoherent integrations for Galileo E6‐B tracking

M. Susi, D. Borio
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引用次数: 12

Abstract

The former Galileo Commercial Service (CS) will provide a High Accuracy Service (HAS) and a Commercial Authentication Service (CAS). The first will disseminate free Precise Point Positioning (PPP) corrections through the E6-B signal whereas the second will provide authentication capabilities through the E6-C pilot component that will be encrypted. For this reason, improved processing strategies for data-only processing need to be investigated. The combined use of Kalman filtering and noncoherent integrations is analyzed in this work. A Software Defined Radio (SDR) receiver has been developed and used for the analysis. Different scenarios were considered including simulated data with decreasing Carrier-to-Noise Power Spectral Density Ratio (C/N0) levels and live static and dynamic data collected under harsh environments. It emerges that the use of Kalman filtering with extended noncoherent integrations is an effective approach to improve the performance of data-only processing.
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伽利略E6-B跟踪的非相干积分卡尔曼滤波
前伽利略商业服务(CS)将提供高精度服务(HAS)和商业认证服务(CAS)。第一种将通过E6-B信号传播免费的精确点定位(PPP)校正,而第二种将通过将被加密的E6-C导频组件提供认证能力。因此,需要研究用于仅数据处理的改进处理策略。本文分析了卡尔曼滤波和非相干积分的组合使用。软件定义无线电(SDR)接收器已经被开发并用于分析。考虑了不同的场景,包括载波噪声功率谱密度比(C/N0)水平降低的模拟数据,以及在恶劣环境下收集的实时静态和动态数据。结果表明,将卡尔曼滤波与扩展的非相干积分相结合是提高纯数据处理性能的有效方法。
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