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海上发射平台运载器的快速自动对准策略。

A Rapid Self-Alignment Strategy for a Launch Vehicle on an Offshore Launching Platform.

机构信息

School of Astronautics, Harbin Institute of Technology, Harbin 150001, China.

Institute of Modern Optics, Nankai University, Tianjin 300350, China.

出版信息

Sensors (Basel). 2022 Dec 28;23(1):339. doi: 10.3390/s23010339.

DOI:10.3390/s23010339
PMID:36616936
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9823459/
Abstract

To reduce the impact of offshore launching platform motion and swaying on the self-alignment accuracy of a launch vehicle, a rapid self-alignment strategy, which involves an optimal combination of anti-swaying coarse alignment (ASCA), backtracking navigation, and reverse Kalman filtering is proposed. During the entire alignment process, the data provided by the strapdown inertial navigation system (SINS) are stored and then applied to forward and backtrack self-alignment. This work elaborates the basic principles of coarse alignment and then analyzes the influence of ASCA time on alignment accuracy. An error model was built for the reverse fine alignment system. The coarse alignment was carried out based on the above work, then the state of the alignment system was retraced using the reverse inertial navigation solution and reverse Kalman filtering with the proposed strategy. A cycle-index control function was designed to approximate strict backtracking navigation. Finally, the attitude error was compensated for after the completion of the first and the last forward navigation. To demonstrate the effectiveness of the proposed strategy, numerical simulations were carried out in a scenario of launch vehicle motion and swaying. The proposed strategy can maximize the utilization of SINS data and hence improve the alignment accuracy and further reduce the alignment time. The results show that the fully autonomous alignment technology of the SINS can replace the complex optical aiming system and realize the determination of the initial attitude of a launch vehicle before launch.

摘要

为降低海上发射平台运动和摇摆对运载火箭自对准精度的影响,提出了一种快速自对准策略,该策略涉及反摇摆粗对准(ASCA)、回溯导航和反向卡尔曼滤波的最优组合。在整个对准过程中,存储捷联惯性导航系统(SINS)提供的数据,然后将其应用于前向和回溯自对准。这项工作阐述了粗对准的基本原理,然后分析了 ASCA 时间对对准精度的影响。建立了反向精细对准系统的误差模型。基于上述工作进行粗对准,然后使用提出的策略,通过反向惯性导航解和反向卡尔曼滤波回溯对准系统的状态。设计了循环索引控制函数来近似严格回溯导航。最后,在前向导航完成后,补偿第一次和最后一次的姿态误差。为了验证所提出策略的有效性,在运载火箭运动和摇摆的场景中进行了数值模拟。所提出的策略可以最大限度地利用 SINS 数据,从而提高对准精度,并进一步减少对准时间。结果表明,SINS 的完全自主对准技术可以替代复杂的光学瞄准系统,实现运载火箭发射前初始姿态的确定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/95c7cb20db37/sensors-23-00339-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/ffd42b5b6523/sensors-23-00339-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/975429d3bc14/sensors-23-00339-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/9b81a722b9c7/sensors-23-00339-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/098eb2311f33/sensors-23-00339-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/d3d0f186a791/sensors-23-00339-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/c428d2d13ff1/sensors-23-00339-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/71a66b4e5f74/sensors-23-00339-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/0c4521627115/sensors-23-00339-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/95c7cb20db37/sensors-23-00339-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/ffd42b5b6523/sensors-23-00339-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/975429d3bc14/sensors-23-00339-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/9b81a722b9c7/sensors-23-00339-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/098eb2311f33/sensors-23-00339-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/d3d0f186a791/sensors-23-00339-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/c428d2d13ff1/sensors-23-00339-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/71a66b4e5f74/sensors-23-00339-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/0c4521627115/sensors-23-00339-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/774a/9823459/95c7cb20db37/sensors-23-00339-g009.jpg

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