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首页> 外文会议>ION Pacific PNT Meeting >A Novel Federated Prefilter Design for Ultra-Tightly Coupled GPS/INS Integration
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A Novel Federated Prefilter Design for Ultra-Tightly Coupled GPS/INS Integration

机译：一种用于超紧密耦合的GPS / INS集成的新型联合预滤器设计

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The tracking performance is a challenge to the receiver designer in complex environments such as high dynamic scenarios, indoor environments, and urban areas, etc., where the GPS tracking loops may lose lock due to the signals being weak, subjected to excessive dynamics or completely blocked. Traditional GPS tracking loop can be replaced by the vector tracking loop (VTC) for solving some of the problems in complex/harsh environments. As a specific configuration of the VTC, The ultra-tightly coupled (UTC), sometimes referred to as the deeply coupled, GPS/INS navigation system integrates the signals from the tracking loops of the GPS receiver with the position and velocity obtained from the INS. In such configuration, the Doppler signal derived from INS aids the tracking loop to remove the dynamics from the GPS signals, which reveals many benefits, e.g., disturbance and multipath rejection capability, improved tracking capability for weak signals, and reduction of acquisition time. Due to the large computational load of the centralized filter configuration, the federated filter-based UTC integration structure has been developed to distribute the computing tasks between different filters, leading to overall filter complexity reduction and computational requirements, which is attractive for efficient real-time implementation. Since the measurement (I and Q accumulator outputs) for the prefilters and the system states are highly nonlinearly related, the nonlinear filters are potentially useful. In addition to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) approaches, one of the alternative methods is to use the Bayesian filter/particle filter (PF) to improve the mitigation/interference suppression capability. For certain problems, a Gaussian assumption cannot be applied with confidence. To overcome these problems, the probability-based estimator PF was proposed to approximate the posterior distribution for highly nonlinear systems. The PF possesses superior performance as compared to EKF and UKF as an alternative estimator for dealing with the nonlinear, non- Gaussian system. Incorporation of the adaptive algorithm into the nonlinear filters will be performed for dealing with the low quality signal and high dynamic environment. Exploration of the determination of the process and measurement noise covariance matrices needs to be involved for dealing with the varying dynamic scenario. Performance assessment will involves the improvement of tracking capability for weak signals in high dynamic environments and rejection capability for non-Gaussian disturbance. Performance evaluation for the proposed design as compared to the others will be carried out.
机译：跟踪性能是在复杂环境中的接收机设计者一个挑战，如高动态脚本，室内环境，和城市地区等，其中，GPS跟踪环路可能失去锁定因信号是弱，受到过大的动态或完全受阻。传统的GPS跟踪环路可以由矢量跟踪环路（VTC）为解决一些复杂/恶劣环境的问题来代替。随着VTC，超紧耦合（UTC）的具体的结构，有时被称为深度结合，GPS / INS导航系统集成了信号从与所述位置和速度从所述INS取得的GPS接收器的跟踪环路。在这样的配置中，来自INS导出的多普勒信号有助于跟踪环路从GPS信号，这揭示了许多好处，除去动力学例如，干扰和多径抑制能力，对于弱信号改进的跟踪能力，并且减少采集时间。由于集中过滤器配置的大计算量，联合基于过滤器的UTC集成结构已经发展到分配不同的过滤器之间的计算任务，从而导致整个过滤器降低复杂性和计算的要求，这是高效的实时吸引力执行。由于测量（I和Q累加器输出）的预过滤器和系统的状态是高度非线性的关系，在非线性滤波器是潜在有用的。除了扩展卡尔曼滤波器（EKF）和无迹卡尔曼滤波（UKF）接近，的备选方法是使用贝叶斯过滤器/微粒过滤器（PF），以改善减轻/干扰抑制能力。对于某些问题，高斯假设不能有信心应用。为了克服这些问题，基于概率的估计PF提出了近似的高度非线性系统的后验分布。所述PF具有相比于EKF和UKF作为处理非线性，非高斯系统的替代估计性能优越。自适应算法到非线性滤波器的掺入将用于处理的低质量信号和高动态环境下进行。过程和测量噪声协方差矩阵的需要的确定的勘探参与用于处理与变化的动态脚本。绩效评估将包括跟踪能力，在高动态环境和非高斯抗干扰能力弱信号的改善。所提出的设计比别人的绩效评价将被执行。

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