海基平台纯方位主动无源跟踪技术研究

发布时间：2018-01-16 00:00

本文关键词：海基平台纯方位主动无源跟踪技术研究　出处：《浙江大学》2016年硕士论文　论文类型：学位论文

【摘要】：在科技高速发展的今天,信息战、电子战被越来越多地应用于各种战争系统及国防系统,发挥着日益重要的作用。无源定位跟踪技术作为精准定位技术的佼佼者,具有探测距离远、隐蔽性强等技术优势,因此被广泛地应用于军事领域并得到了国内外众多学者的研究。本文基于海基平台无源观测系统展开了对纯方位主动无源定位跟踪技术的研究,结合实际应用场景提出若干新问题,并给出相应的解决方案。海基平台无源观测系统是一个典型的非线性系统。在实际应用中,噪声、初始误差等原因一定程度上影响了无源观测系统的估计精度。针对此问题,本文提出加入控制输入的容积卡尔曼平滑算法(CRTS-U),该算法将经典容积卡尔曼滤波(Cubature Kalman Filter, CKF)和Racuch-Tung-Striebel Smoother (RTSS)平滑算法结合起来,进一步提高了系统的估计精度。另外,该算法将系统控制输入作为待设计量引入系统方程并参与迭代,使同时求解系统的最优状态估计和海基平台的最优机动策略成为可能,仿真结果显示了CRTS-U算法的可行性及有效性。研究发现,系统的控制输入不仅影响系统的可观测性,而且会影响系统的估计性能,因此选择恰当的控制输入是非常重要的。常用的最优机动判别指标都仅能从单一维度评估观测机机动的好坏,本文考虑到海基平台机动时的燃料消耗,将燃耗控制指标与普通判别指标相结合,构建了最优机动复合判别指标,使我们能够多维度地评估观测机机动的优劣。随后,基于CRTS-U算法及最优机动判别复合判别指标,本文提出了最优控制求解算法和最优估计求解算法,同时解决了燃耗约束下系统的最优状态估计问题和海基平台最优机动策略设计问题。仿真结果显示了最优控制求解算法的可行性及有效性。
[Abstract]:With the rapid development of science and technology, information warfare and electronic warfare are more and more used in various war systems and national defense systems. Passive positioning and tracking technology, as the best in precision positioning technology, has the advantages of long detection distance and strong concealment. Therefore, it has been widely used in military field and has been studied by many scholars at home and abroad. In this paper, the research of azimuth-only active passive location and tracking technology is carried out based on the passive observation system of sea-based platform. Based on the practical application, some new problems are proposed, and the corresponding solutions are given. The passive observation system of the sea-based platform is a typical nonlinear system. In practical application, noise is used. The initial error and other factors affect the estimation accuracy of passive observation system to some extent. In order to solve this problem, a volume Kalman smoothing algorithm (CRTS-U) with control input is proposed in this paper. The algorithm uses classical volume Kalman filter cuboid Kalman Filter. CKF) and Racuch-Tung-Striebel Smoother / RTSS smoothing algorithm are combined to further improve the estimation accuracy of the system. The algorithm introduces the system control input into the system equation and participates in the iteration, which makes it possible to simultaneously solve the optimal state estimation of the system and the optimal maneuvering strategy of the sea-based platform. Simulation results show the feasibility and effectiveness of the CRTS-U algorithm. It is found that the control input of the system not only affects the observability of the system, but also affects the estimation performance of the system. Therefore, it is very important to select the appropriate control input. The commonly used optimal maneuvering discriminant indexes can only evaluate the maneuverability of the observing machine from a single dimension. This paper takes into account the fuel consumption of the sea-based platform maneuvering. By combining the burnup control index with the ordinary discriminant index, the optimal maneuvering composite discriminant index is constructed, which enables us to evaluate the maneuverability of the observing machine in many dimensions. Based on the CRTS-U algorithm and the optimal maneuvering discriminant compound discriminant index, the optimal control algorithm and the optimal estimation algorithm are proposed in this paper. At the same time, the optimal state estimation problem and the optimal maneuvering strategy design problem of the sea-based platform are solved. The simulation results show the feasibility and effectiveness of the optimal control algorithm.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：E11;TP13

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