【作者】 赵艳丽；

【导师】 王国玉；

【作者基本信息】 国防科学技术大学 ， 信息与通信工程， 2007， 博士

【摘要】 弹道导弹是现代战争中极具威力的进攻性武器,导弹战将成为战争初期或关键时刻的主要作战方式。为了提高弹道导弹的突防能力,各种突防措施纷纷被提出,其中有源假目标欺骗干扰因其高“性价比”而越来越受到重视。雷达作为导弹防御系统中的核心探测器,其跟踪、识别性能的优劣对整个导弹防御系统的性能都有很大的影响。导弹目标跟踪是导弹防御雷达最基本、最核心任务,有源假目标欺骗干扰使导弹防御雷达面临严峻挑战,研究弹道导弹的雷达跟踪和识别技术,可为提高导弹防御雷达的跟踪能力和抗电子干扰能力提供技术支持,同时可为弹道导弹突防仿真实验软件提供核心算法支持,为有源欺骗干扰策略优化等提供参考依据,因此是迫切需要解决的军事前沿课题,具有重要的军事价值和现实意义。本文以导弹防御技术研究和发展的需求为背景,以雷达数据处理为内在主线,研究了弹道导弹的雷达跟踪和识别技术。具体包括:中段弹道目标跟踪、再入段弹道目标跟踪、单部雷达基于动力学特性的有源假目标识别、组网雷达下多目标跟踪和有源假目标识别。中段是弹道导弹飞行时间最长、飞行相对平稳的阶段,雷达在该阶段跟踪最为有利,精确的中段跟踪是雷达进行落点预报、宽带识别、制导拦截的基础。首先,对基础性的背景知识进行了介绍。接着,详细推导了四种典型坐标系下中段弹道目标的动力学模型,特别是对非笛卡尔的传感器坐标系下的目标动力学模型给出了独立的显式表达,使其可以直接套用EKF滤波(Extended Kalman Filter,EKF)结构。分析比较了不同跟踪坐标系下中段弹道目标跟踪性能的优劣。对基础性、共性的目标动力学模型和跟踪坐标系问题进行了系统整合归纳,为进一步从事该领域理论研究和实际应用提供了良好基础。最后,提出了一种改进的弹道中段目标跟踪算法,该算法比传统的EKF算法跟踪精度更高。当导弹再入大气层时,会受到两个主要的作用力:地球重力和空气阻力,如果发生机动,那么还必须考虑第三个力—空气升力。不执行机动的再入目标称之为弹道式再入飞行器,否则称之为机动再入飞行器。论文首先对空气动力进行了模型研究。接着,详细推导了四种典型坐标系下弹道式再入目标的动力学模型,比较了不同跟踪坐标系下再入段跟踪算法性能。最后,结合两种典型机动再入弹道,仿真分析了两类机动再入目标跟踪算法的性能。雷达系统前端和信号处理无法滤出、识别的高逼真有源假目标,会对雷达造成严重威胁。本文提出了利用动力学特性识别有源假目标的新思路和新方法。其原理是:有源假目标的运动特性与实体目标的运动特性存在本质差异;而滤波器动力学模型通常依据真目标运动模型而建立,那么假目标运动特性与滤波器动力学模型则必定不一致,这种不一致会导致雷达滤波器出现某种程度的“失配”,根据这种“失配”即可对有源假目标进行识别。如何把这种隐性的“失配”定量的表征出来,也即寻找能灵敏反映真假目标运动特性差异的识别特征量,是有源假目标识别技术的关键所在。根据识别特征量的不同,提出了三种有源假目标识别方法:基于弹道平面特性的识别;基于加速度模型匹配的识别;基于归一化误差的识别。利用目标动力学特性来识别高逼真有源假目标,其本质是在充分认识目标运动特性的基础上,对雷达滤波信息进行挖掘、再利用。利用动力学特性进行识别,是抗电子干扰理论和技术上的重要创新。针对高逼真有源假目标,组网雷达不仅可以利用动力学特性进行识别,还可以采用特有的同源检验技术进行识别。同源检验是指通过判断来自不同雷达分站的点迹或航迹在统一坐标系下是否一致进而识别目标真假。针对集中式组网雷达,可以采用量测点迹同源检验来识别有源假目标;针对分布式组网雷达,采用滤波航迹同源检验来识别有源假目标。有源假目标干扰下的组网雷达跟踪和识别是紧密耦合的过程。组网雷达下多目标跟踪和识别技术既是对目标跟踪技术的拓展,又是对抗电子干扰技术的丰富。论文最后对全文进行了总结,指出了论文的创新之处,对今后工作方向提出了一些参考意见和想法。本论文的研究工作来源于实际项目需求,其大多数研究结果和结论已经成功应用到实际工程项目中,并取得了良好的效果。更多还原

【Abstract】 The ballistic missiles are great powerful attacking weapons in modern wars and will play an important role at the beginning or key moment in the wars. To improve the survival captibility of the ballistic missiles, many peneration measures are proposed. Among all these measures, the active decoys have obtained more and more attention because of the high efficiency. As the key sensors in ballistic missile defense (BMD) system, the quality of tracking and discrimination of the radars has a crucial impact on the whole system’s performance. Tracking ballistic missiles is the basic and primary task for the radars in BMD, but active decoys bring serious challenges in this area. Researching on the ballistic missile tracking and discrimination can provid the technology support to improve the tracking and anti-deception capability of the radar. Simultaneously, the key algorithm in the platform of the ballistic missile penetration simulation and the theory of the deception jamming optimization can be provided by this researching. So, as an urgent project, deeply researching on this topic has a great military value and reality significance.Taking the request of the researching and development of the missle defence technology as the background, the tracking and discrimination technologies are investigated based on the radar data processing. The investigation includes the ballistic target tracking in midcourse and reentry regime of the trajectory and the discrimination of active decoys by the single radar or the radar network.The midcourse, as the longest and stablest phase in the track, is the most valuable phase for radar tracking. Precisely tracking is the basis for falling point prediction, target recognition, guiding and intercepting. First, necessary and rudimentary background information concerning ballistic tracking is provided. Then, the target dynamics models are derived in four typical coordinate systems (CS). Especially the decoupled explicit equation in non-Cartesian CS is given, which is suitable for EKF directly. The performances of tracking in different CS are compared and summarized, which provides a good basis for further theory and practice research. Finally, an improved algorithm is proposed for ballistic missile tracking in midcourse, which has a better performance than EKF.During the reentry phase, there are two major forces impact on the missile: the gravity and atmospheric drag. If maneuver is presented, a third force—aerodynamic lift force—must be considered. If the maneuver exists, the reentry vehicle (RV) is called ballistic RV (BRV). If the maneuver doesn’t exist, it is called maneuvering RV (MaRV). First, aerodynamic forces are described with the concerning of the air density, drag and lift forces. Then, the target dynamics models are derived in four typical CS, and the performance of tracking in different CS are compared and summarized. Finally, with the background of two typical maneuvering reentry trajectories, two kinds of tracking algorithms are utilized and the performances are comparedThe high-fidelity active decoy is a great threat to radar, which can’t be filtered or discriminated by radar receiver and signal processing. The theory and technique on active decoy discrimination are proposed based on the radar tracking. The motion model of the active decoy is different from the real target essentially. The dynamic model of the radar filter is generally built based on the real target, so it must be unfit for the active decoy. The unmatchable filter, which is produced by the unfitness, can be utilized to discriminate the active decoy. The quantitative expression of the recessive unfitness and the sensitive measurement of the motive character discrimination are the keys of the discrimination technology. Three methods are proposed based on different characteristics: the trajectory’s planarity; the acceleration model; the normalized error. These methods are all based on the target’s dynamics characteristic, and made the best use of the radar filtering data. The theory and technique on discriminating active decoy based the dynamics characteristic is great creativeness in the field of electronic counter-countermeasures (ECCM).Radar network can discriminate the high-fidelity active decoy not only based on the target dynamics characteristics but also based on the same-source-testing. The same-source-testing discriminates the active decoys by judging whether the points or filtered trajectories measured by the different radars can be matched or not in the same CS. In the same-source-testing, the measured points are utilized for the centralized radar network, and the filtered trajectories are adopted for the distributed radar network. For the discrimination technology of radar network, the discriminating is coupled with the tracking. Not only the tracking technique is expanded, but also the ECCM is enriched by the tracking and discrimination technologies of radar network.In the last part, the whole dissertation is summarized, the major creativite topices are pointed out and some suggestions for the future work are brought out.The research in the dissertation stems from the request of practical projects and its conclusion and methods are successfully applied in practice and fairly good effects are obtained.更多还原