水面舰艇对来袭鱼雷联合定位方法

张虹; 肖明恺

doi:10.11993/j.issn.2096-3920.2023-0019

水面舰艇对来袭鱼雷联合定位方法

doi: 10.11993/j.issn.2096-3920.2023-0019

张虹,
肖明恺

中国人民解放军91439部队, 辽宁大连, 116041

详细信息

作者简介:
张虹：张　虹(1981-), 女, 工程师, 主要从事鱼雷试验技术研究

中图分类号: TJ630.34
计量
- 文章访问数: 140
- HTML全文浏览量: 36
- PDF下载量: 45
- 被引次数: 0
出版历程
- 收稿日期: 2023-03-01
- 修回日期: 2023-03-23
- 录用日期: 2023-04-12
- 网络出版日期: 2023-05-26

Joint Target Localization Method for Warships Facing Incoming Torpedoes

Unit 91439^th, The People’s Liberation Army of China, Dalian 116041, China

摘要

摘要: 针对传统舰载声呐以及拖曳阵声呐在进行鱼雷预警时缺失鱼雷距离、位置信息, 导致鱼雷防御器材效能较低的问题, 开展了水面舰艇对来袭鱼雷联合定位方法研究。针对来袭鱼雷方位估计信息误差大、存在野值等问题, 提出基于局部加权线性回归的测向信息预处理方法, 降低了目标方位估计精度不足引入的定位误差, 结合典型鱼雷攻击弹道运动特性, 利用卡尔曼滤波算法, 建立了目标状态解算模型。同时针对水声信号收发不同时、信号处理延迟等问题, 提出时空关联算法, 形成稳健声呐联合定位算法。该方法在增强舰船联合作战指挥系统的鱼雷防御能力, 维护舰艇安全等方面具有广泛的应用前景。
- 舰艇 /
- 联合定位 /
- 鱼雷 /
- 局部加权线性回归 /
- 时空关联 /
- 卡尔曼滤波算法
Abstract: Existing shipborne sonar or tow array sonar might influence the effectiveness of torpedo countermeasures, compromising torpedo localization information during torpedo alarming. To address this problem, a joint target localization method is proposed for incoming torpedoes. First, a preprocessing method based on local weighted linear regression is investigated to resolve issues such as large error and outliers in the bearing estimation information of incoming torpedoes. This method can be used to lower the localization error by improving the torpedo bearing estimation accuracy. In combination with typical torpedo attacking trajectory analysis, a target state solution model is then established using a Kalman filtering algorithm. A space-time correlation algorithm is used for solving the problem caused by unsynchronized underwater acoustic signals and delayed information processing. Finally, a robust joint localization approach for shipborne sonar is established. This approach has reasonably wide applications, such as in torpedo defense capacity reinforcement of warship joint combat command systems and security assurance for warships.
- warship /
- joint localization /
- torpedo /
- local weighted linear regression /
- time-space correlation /
- Kalman fitler algorithm

HTML全文

图 1 时空关联算法仿真场景

Figure 1. Simulation scenario of the space-time correlation algorithm

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图 2 采用LWLR法进行野值剔除的仿真结果

Figure 2. Simulation results of the outlier elimination by LWLR method

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图 3 LWLR滤波后角度测量值

Figure 3. Angular measurement after filtering by LWLR method

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图 4 态势1条件下定位轨迹及定位误差

Figure 4. The localization trajectories and errors under situation 1

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图 5 态势2条件下定位轨迹及定位误差

Figure 5. The localization trajectories and errors under situation 2

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图 6 态势3条件下定位轨迹及定位误差

Figure 6. The localization trajectories and errors under situation 3

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