Application of Improved Adaptive Filtering Algorithm in BD／INS Integrated Navigation
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摘要: 针对目前北斗与惯性导航系统的组合导航系统的导航性能和鲁棒性较差,基于衰减因子和噪声加权的自适应卡尔曼滤波技术,研究了组合导航系统在不确定性噪声干扰下的组合新算法。并在Matlab中进行了仿真实验,通过对比传统卡尔曼滤波技术,验证了新算法的有效性。并在Matlab中进行了无人机数据后处理实验。结果表明,改进的自适应滤波算法可以有效地降低不确定性干扰对组合导航系统的影响,从而提高了系统的导航性能和鲁棒性。Abstract: Since the navigation performance and robustness of the integrated navigation system which combines the BeiDou and inertial navigation system are poor,the paper proposes a new algorithm under uncertainty noise interference, which bases on the attenuation factor and noise weighted adaptive Kalman filter technology. The paper first conducts simulation experiments with Matlab,comparing the traditional Kalman filter technology to verify the effectiveness of the new algorithm.Then the data postprocessing experiment of UAV is carried out. The results show that the improved adaptive filter algorithm can effectively increase the interference immunity of the integrated navigation system, thus improving the navigation performance and robustness.
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Key words:
- Integrated navigation system /
- information fusion /
- BeiDou /
- adaptive filter
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