An Initial Alignment Method Using Backtracking Algorithm Combined with Data Sequence Reconstruction Fusion Filtering
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摘要: 为了在提高鱼雷初始对准精度的同时保证较短的对准时间, 文中在采用回溯算法进行初始对准的基础上, 通过对存储数据的调用及线下处理, 提出一种数据时序重构融合滤波算法, 通过对存储数据进行再次调用、整体辨识、特征量提取和时序重构, 构建多级滤波器, 与传统“正向—逆向—正向”滤波回溯算法比较, 实现了一定时间内滤波估计及对准精度的进一步提高。实航数据的仿真对比试验证明了该方法在精度及时间上的有效性。Abstract: In order to improve the initial alignment accuracy of torpedo and ensure shorter alignment time, on the basis of applying the backtracking algorithm to the initial alignment, a data sequence reconstruction fusion filtering method is proposed by calling and offline-processing the stored data. The proposed method can further improve the filtering estimation and alignment accuracy within a certain time compared with the traditional “forward-backward-forward” filtering backtracking algorithm by re-calling of the stored data, overall identification, feature extraction, time sequence re-construction, and construction of a multi-stage filter. Comparison between simulation results and sea trial data proves the effectiveness of the proposed method in accuracy and time.
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Key words:
- torpedo /
- initial alignment /
- backtracking algorithm /
- sequence reconstruction /
- fusion filtering
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