非完整性约束量测噪声在组合导航算法中的应用研究
首发时间:2020-12-30
摘要:非完整性约束作为一种不需要增加辅助传感器的、提高定位精度的辅助信息,被广泛运用于陆地车载导航系统。然而非完整性约束条件很大程度上依赖于路况和特定行驶车辆,这意味着超出其边界使用这种虚拟信息将产生反作用。为了验证非完整性约束量测噪声对组合导航算法导航性能的影响,本文使用不同的量测噪声值针对不同路段的导航数据进行测试。实验证明,在组合导航系统中,动态调整非完整性约束量测噪声很大程度上提高了导航的位置、速度、姿态精度,有效地确保了车载导航的导航性能
关键词: 非完整性约束 量测噪声 组合导航 卡尔曼滤波 导航性能
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Research on Application of Non-holonomic Constrained Measurement Noise in Integrated Navigation Algorithm
Abstract:As an auxiliary information without additional auxiliary sensors to improve positioning accuracy, non-holonomic constraints are widely used in land vehicle navigation system. However, non-holonomic constraints condition is heavily dependent on road conditions and specific vehicles in required motion, which means that it will be counterproductive to use this virtual information beyond its boundaries. In order to verify the influence of non-holonomic constrained measurement noise on the navigaion performance of integrated navigation algorithm, different measurement noises are used to test navigation performance in different stretches of road. The experiment shows that, in integrated navigation algorithm, the dynamic adjustment of non-holonomic constrained measurement noise greatly improves the positioning, velocity and attitude accuracy, and effectively ensures the performance of vehicle navigation.
Keywords: Non-holonomic Constraints Measurement Noise Integrated Navigation Algorithm Kalman Filter Navigation Performance
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非完整性约束量测噪声在组合导航算法中的应用研究
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