| 摘 要: 随着组合导航系统应用环境的复杂及多样性日益增加,Kalman滤波器的稳定性和发散性问题日趋明显。根据现有的Sage-Husa自适应滤波技术和强跟踪 Kalman滤波方法,提出了一种改进的自适应滤波算法。通过建立组合导航系统的状态方程与观测方程,应用该改进型算法进行控制,实现组合导航系统的伪距、伪距率融合。实验结果表明,该算法对滤波发散问题的抑制效果明显,且在一定范围内具有自适应能力,能够实现组合导航系统精度、可靠性、完备性的有效提高。 |
| 关键词: 组合导航 自适应滤波 Sage-Husa自适应滤波 强跟踪 Kalman滤波 |
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中图分类号: TP31
文献标识码: A
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| Data Fusion Based on Adaptive Kalman Filtering |
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(1.Haiying Enterprise Group Co., Ltd. Wuxi 214142, China;
2.Naval Equipment Department Military Representative Office in Wuxi, Wuxi 214142, China;
3.CSSC Marine Exploration Technology Research Institute Co., Ltd. Wuxi 214142, China)
617199546@qq.com; 1012925836@qq.com; chzy@163.com; wangjj@126.com; duxy98@163.com
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| Abstract: With the increasing complexity and diversity of the application environments of integrated navigation systems, the stability and divergence issues of Kalman filters have become increasingly prominent. Based on the existing Sage-Husa adaptive filtering technique and Strong Tracking Kalman Filtering method, an improved adaptive filtering algorithm is proposed. By establishing the state equation and observation equation of the integrated navigation system, the improved algorithm is applied for control to achieve the fusion of pseudo-range and pseudo-range rate in the integrated navigation system. Experimental results show that the algorithm effectively suppresses filter divergence and exhibits adaptive capabilities within a certain range, thereby improving the accuracy, reliability, and integrity of the integrated navigation system. |
| Keywords: integrated navigation adaptive filtering Sage-Husa adaptive filtering technique strong tracking
Kalman filtering |
