Gnss performance enhancement in urban environment based on pseudo-range error model

N. Viandier, D. Nahimana, J. Marais, E. Duflos
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引用次数: 75

Abstract

Today, GNSS (Global Navigation Satellite System) systems made their entrance in the transport field through applications such as monitoring of containers or fleet management. These applications do not necessarily request a high availability, integrity and accuracy of the positioning system. For safety applications (for instance management of level crossing), the performances require to be more stringent. Moreover all these transport applications are used in dense urban or sub-urban areas, resulting in signal propagation variations. This increases difficulty of getting the best reception conditions for each available satellite signal. The consequences of environmental obstructions are unavailability of the service and multipath reception that degrades in particular the accuracy of the positioning. Our works consist in two main tasks. The first one concerns the pseudo-range error model. Indeed, the model differs in relation of the satellite state of reception. When the state of reception is direct, as described in literature, the associated pseudo-range error model is a Gaussian distribution. However, when the state of reception is NLOS (Non Line Of Sight), this assumption is no more valid. We have shown that the associated model can be approximated by a Gaussian mixture. The Second contribution concerns the reception state evolution. We have modeled the propagation channel with a Markov chain. From the state of reception of each satellite, we deduce the appropriated error model. This model is then used in a filtering process to estimate the position. The approach is based on filtering methodology and on the application of a Jump Markov System algorithm.
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基于伪距离误差模型的城市环境Gnss性能增强
如今,GNSS(全球导航卫星系统)系统通过集装箱监控或车队管理等应用进入运输领域。这些应用并不一定要求定位系统的高可用性、完整性和准确性。对于安全应用(例如平交道口管理),性能要求更为严格。此外,所有这些运输应用都是在人口密集的城市或郊区使用,导致信号传播变化。这增加了获得每个可用卫星信号的最佳接收条件的难度。环境障碍的后果是服务不可用和多路径接收,特别是降低了定位的准确性。我们的工作主要包括两项任务。第一个是伪距离误差模型。实际上,模型在卫星接收状态的关系上有所不同。当接收状态为直接时,如文献所述,相关的伪距离误差模型为高斯分布。然而,当接收状态为NLOS (Non Line of Sight)时,这种假设就不成立了。我们已经证明,相关模型可以用高斯混合近似。第二个贡献是关于接收状态的演变。我们用马尔可夫链对传播通道进行了建模。根据各卫星的接收状态,推导出相应的误差模型。然后在滤波过程中使用该模型来估计位置。该方法基于滤波方法和跳跃马尔可夫系统算法的应用。
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