Target Tracking Error Simulation and Analysis of Acoustic Homing Torpedo
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摘要: 主动声自导鱼雷目标跟踪具有观测基座运动和观测时变的特点, 采用Kalman滤波方法进行目标跟踪时, 需要利用鱼雷航行姿态参数和鱼雷检测目标信息, 通过坐标变换将鱼雷检测目标的坐标从鱼雷坐标系变换到大地坐标系, 因此自导系统检测误差和导航定位系统航姿误差均对跟踪性能有一定影响。文中分析了主动声自导鱼雷目标跟踪误差来源及传递途径, 分别对偏航角误差、雷速误差及检测误差进行了跟踪性能仿真分析。仿真结果表明, 偏航角误差对目标速度估计及航向角估计影响不大 雷速误差线性传递至目标, 速度估计误差与雷速误差相等, 雷速误差对航向无影响 检测误差经过滤波可以基本消除, 运动参数经过多拍滤波后能有效逼近真值。Abstract: Active acoustic homing torpedo target tracking exhibits the characteristics of base motion and time-varying observation. When using the Kalman filtering method to track the target, it is necessary to use the torpedo navigation attitude parameters and torpedo detection target information as well as transform the torpedo detection target coordinate from the torpedo coordinate system to a geodetic coordinate system through coordinate transformation. Therefore, the detection error of the homing system and the attitude error of the navigation and positioning system affect the tracking performance. Herein, the source and transmission paths of the target tracking error of an active acoustic homing torpedo are analyzed. The tracking performances of the yaw angle error, torpedo speed error, and detection error are simulated and analyzed. The simulation results show that the yaw angle error does not significantly affect the target speed estimation and course angle estimation. The torpedo speed error is linearly transmitted to the target, the velocity estimation error is equal to the torpedo speed error, and the torpedo speed error does not affect the course. The detection error can be eliminated via filtering, and the motion parameters can effectively approximate the true value after multibeat filtering.
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Key words:
- acoustic homing torpedo /
- target tracking /
- navigation attitude error /
- detection error /
- error analysis
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[1] 曲毅, 刘忠, 屈津竹. 基于时延的水中目标纯方位跟踪算法[J]. 系统工程与电子技术, 2007, 29(1): 107-109.Qu Yi, Liu Zhong, Qu Jin-zhu. Research on Underwater Bearings-only Target Tracking Algorithm Based on Time-delay[J]. Systems Engineering and Electronics, 2007, 29(1): 107-109. [2] 刘伟, 王昌明, 赵辉. 基于卡尔曼滤波的水下近距目标运动分析[J]. 弹道学报, 2008, 20(4): 28-31.Liu Wei, Wang Chang-ming, Zhao Hui. Target Motion Analysis of Underwater Short-distance Target Based on Kalman Filter[J]. Journal of Ballistics, 2008, 20(4): 28-31.?/div> [3] 杨向锋, 杨云川, 陈亚林. 鱼雷目标跟踪建模与仿真[J]. 鱼雷技术, 2013, 21(1): 15-19.Yang Xiang-feng, Yang Yun-chuan, Chen Ya-lin. Modeling and Simulation of Target Tracking for Underwater Acoustic Homing Weapon[J]. Torpedo Technology, 2013, 21(1): 15-19. [4] 严卫生. 鱼雷航行力学[M]. 西安: 西北工业大学出版社, 2005. [5] 李志舜. 鱼雷自导信号与信息处理[M]. 西安: 西北工业大学出版社, 2004. [6] 储海荣, 段镇, 贾宏光, 等. 捷联惯导系统的误差模型与仿真[J]. 光学精密工程, 2009, 17(11): 2779-2785.Chu Hai-rong, Duan Zhen, Jia Hong-guang, et al. Error Model and Simulation of Strapdown Inertial Navigation System[J]. Optics and Precision Engineering, 2009, 17(11): 2779-2785. [7] 尹洪亮, 杨功流, 宋凝芳, 等. 旋转激光陀螺惯导系统误差传播特性分析[J]. 北京航空航天大学学报, 2012, 38(3): 345-350.Yin Hong-liang, Yang Gong-liu, Song Ning-fang, et al. Error Propagating Characteristic Analysing for Rotating LGINS[J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(3): 345-350. [8] 李魁, 徐烨烽, 张仲毅, 等. 旋转惯导系统误差自补偿原理分析及试验验证[J]. 系统工程与电子技术, 2011, 33(10):2268-2271.Li Kui, Xu Ye-feng, Zhang Zhong-yi, et al. Errors Auto-compensation Principle Analysis and Experiments Verification for Rotational Systems[J]. Systems Engineering and Electronics, 2011, 33(10): 2268-2271. [9] 孙枫, 孙伟, 郭真. 基于IMU旋转的捷联惯导系统自补偿方法[J]. 仪器仪表学报, 2009, 30(12): 2511-2517.Sun Feng, Sun Wei, Guo Zhen. Auto-compensation Method of SINS Based on IMU Rotation[J]. Chinese Journal of Scientific Instrument, 2009, 30(12): 2511-2517.?/div> [10] 曹萌, 李建辰, 国琳娜, 等. 自适应联邦滤波算法在鱼雷多参量导航定位中的应用[J]. 鱼雷技术, 2014, 22(6): 420-424.Cao Meng, Li Jian-chen, Guo Lin-na, et al. Application of Adaptive Federated Kalman Filter Algorithm to Multipa-rameter Estimation for Torpedo Navigation and Positioning[J]. Torpedo Technology, 2014, 22(6): 420-424. [11] 曹萌, 李建辰, 国琳娜, 等. 多模型自适应联邦卡尔曼滤波及其在鱼雷导航定位中的应用[J]. 鱼雷技术, 2015, 23(4): 305-310.Cao Meng, Li Jian-chen, Guo Lin-na, et al. Multi-model Adaptive Federated Kalman Filter and Its Application to Torpedo Navigation and Positioning[J]. Torpedo Technology, 2015, 23(4): 305-310.
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