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首页> 外文期刊>International journal of mobile computing and multimedia communications >An Enhanced Mobile Device-Based Navigation Model: Ubiquitous Computing
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An Enhanced Mobile Device-Based Navigation Model: Ubiquitous Computing

机译：增强的基于移动设备的导航模型：无处不在的计算

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pThis article formulated, simulated and evaluated an enhanced model for a non-linearon-Gaussian integrated Global Positioning System (GPS) and Inertial Navigation System (INS) mobile-based device navigation system using the Particle Filter (PF). This was with a view to enhancing the accuracy and minimize the delay experienced in the existing system which relies on linear data. An android driven Infinix X5 mobile device with GPS and INS-based sensors was used to implement the model formulated, standard Bayesian estimators were used to generate non-linear datasets with Gaussianon-Gaussian white noises for mobile device based INS/GPS sensors. A mathematical model was formulated using Sampling Importance-weight Resampling (SIR) algorithm of the PF. The conceptual model was developed using Simulink and the design specification was done using Unified Modeling Language (UML). The model was simulated with MATLAB and the simulation results obtained were evaluated using standard metrics, and benchmarked with existing model. The overall results showed that the proposed model performed better than existing ones in term of accuracy. However, the model did not impact on delay reduction./p
机译：>本文使用粒子滤波器（PF）为基于非线性/非高斯集成的全球定位系统（GPS）和基于惯性导航系统（INS）移动设备的设备导航系统制定了增强模型，并对其进行了评估。这样做是为了提高精度并最大程度地减少依赖线性数据的现有系统中遇到的延迟。使用具有GPS和基于INS的传感器的android驱动的Infinix X5移动设备来实现所制定的模型，标准的贝叶斯估计器用于为基于移动设备的INS / GPS传感器生成具有高斯/非高斯白噪声的非线性数据集。使用PF的采样重要性加权重采样（SIR）算法制定了数学模型。使用Simulink开发概念模型，并使用统一建模语言（UML）完成设计规范。使用MATLAB对模型进行仿真，并使用标准指标评估获得的仿真结果，并使用现有模型进行基准测试。总体结果表明，所提出的模型在准确性方面要优于现有模型。但是，该模型对延迟减少没有影响。

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