As the development of traditional scalar tracking loops, different additional enhancement techniques in a GNSS receiver are proposed to help improve the positioning service quality. Up to now, Kalman-based tracking loop has gained much attention due to its potential superiorities, it has been widely exploited and studied in different specific applications. But meanwhile, there is still a lack of the detailed exploration regarding the Kalman tuning and the fully in-depth analysis and validation. Based on our former related work, an improved mathematical expression of Kalman gain and proper tractable models are proposed to help the analysis of Kalman tuning. An explicit tuning rule is proposed step by step regarding every single parameter involved and the validation is carried out in real experiments by the comparison of different receivers with different configurations. The results verify the proposed tuning rule and advantages of KF-tracking with proper setting. Thanks to the accurate and reliable signal parameter estimation, it can dramatically relieve the burden of the following processing modules, like PVT, RTK and other similar algorithms.

/pdf/the-explicit-tuning-investigation-and-validation-of-a-full-4zmcmj643t.pdf

The Explicit Tuning Investigation and Validation of a Full Kalman Filter-Based Tracking Loop in GNSS Receivers

Industrial plant safety is of paramount importance, and the effective operation of Fire and Gas Detection Systems (FGDS) plays a critical role in preventing and mitigating incidents. This study presents a comprehensive parametric computational fluid dynamics (CFD) analysis of nozzle flow, aimed at enhancing our understanding of the complex fluid dynamics within nozzle geometries. Nozzles find wide applications in industries ranging from aerospace propulsion systems to industrial processes. The analysis employs CFD simulations with varying geometric parameters, such as nozzle shape, throat diameter, and expansion ratio, to investigate their influence on flow characteristics, including velocity profiles, pressure distributions, and shock formations. The parametric study involves systematic variations of these geometric parameters, allowing for the identification of optimal configurations for specific applications. The results shed light on the intricate interplay between nozzle geometry and flow behavior, providing valuable insights for nozzle design and optimization.

Dynamic Modelling and Simulation of Industrial Plant Fire and Gas Detection Systems; Parametric Analysis of Nozzle Flow

For global navigation satellite system receivers, Kalman filter (KF)-based tracking loops show remarkable advantages in terms of tracking sensitivity and robustness compared with conventional tracking loops. However, to improve the tracking sensitivity further, increasing the coherent integration time is necessary, but it is typically limited by the navigation data bit sign transition. Moreover, for standard KF-based tracking receivers, the KF parameters are initialized by the acquired results. However, especially under weak signal conditions, the acquired results have frequency errors that are too large for KF-based tracking to converge rapidly to a steady state. To solve these problems, a two-stage KF-based tracking architecture is proposed to track weaker signals and achieve faster convergence. In the first stage, coarse tracking refines the acquired results and achieves bit synchronization. Then, in the second stage, fine tracking initializes the KF-based tracking by using the coarse tracking results and extends the coherent integration time without the bit sign transition limitation. This architecture not only utilizes the self-tuning technique of the KF to improve the tracking sensitivity, but also adopts the two-stage to reduce the convergence time of the KF-based tracking. Simulation results demonstrate that the proposed method outperforms conventional tracking techniques in terms of tracking sensitivity. Furthermore, the proposed method is compared with the standard KF-based tracking approach, proving that the proposed method converges more rapidly.

https://www.mdpi.com/1424-8220/19/6/1369/pdf

A Two-Stage Kalman Filter-Based Carrier Tracking Loop for Weak GNSS Signals

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A Two-Stage Kalman Filter-Based Carrier Tracking Loop for Weak GNSS Signals