吉林大学硕士学位论文 1吉林大学学位论文信息表 姓 名 时成文 学 号 109905006 所属校区 吉林大学前卫校区北区 所属院系 电子科学与工程学院 专业方向 电路与系统 保密级别 秘密 论文上交日期 2002 年 6 月 14 日 学位级别 理学硕士 论文题名（中） 采用 1553B 总线的智能自卫对抗系统 论文题名（外） Intelligent Self- Defense Countermeasure System Using 1553B Data Bus （注：外文题名除首字母和专有字母大写外，其余均小写） 第一导师姓名 郭树旭 第二导师姓名 总 页 码 80 参考文献数 42 分 类 号 TP18 中 文 关 键 词 （3- 5 个） 1553B 总线，质心干扰，自卫对抗专家系统 中文文摘 本文提出的采用 1553B 总线的智能自卫对抗系统就是基于上述技术的一种新型自卫对抗系统。 系统由威胁告警系统、管理控制、专家系统、综合对抗系统及 1553B数据总线等组成。 威胁告警主要有雷达告警(RWR)和导弹逼近告警(MWS)，对抗系统有雷达有源干扰(AECM)和干扰物投放系统(CMDS)。 智能对抗系统主要解决了当前作战飞机所面临的主要威胁 雷达和红外制导导弹 对抗决策问题。 当存在威胁告警时，专家系统根据智能控制规则，在对抗规则库中查询与威胁类型相匹配的对抗决策记录， 并引导对抗系统按决策要求进行对抗。对未知威胁源的告警，按经验数据吉林大学硕士学位论文 2或对数据进行不精确推理进行对抗决策。 专家系统由知识库、推理机、解释器、综合数据库、人机接口等组成。 自卫对抗专家系统接收威胁源信息后利用知识库进行威胁判断，参考干扰物的性能、战场环境、飞机状态以及敌方、 友方等条件， 利用推理机， 确定出干扰方式、干扰时机、干扰范围与干扰强度等干扰决策。而系统的推理方法，是建立在合适的投放控制决策目标函数上的，因此本文对投放控制决策目标函数的基本操作函数： 规则决策函数、规则查找函数、规则前提测试函数、规则优化函数、规则结论执行函数、规则推理函数进行了较为详尽的分析。 智能自卫对抗系统经测试后表明， 系统可以实时接收 各种告警的威胁源信息、载机飞行参数及离散控制信号， 按照电子战专家知识、 书本知识及推理建立对抗各种威胁 源的数学模型，建立威胁源数据库和对抗规则数据库，能 够按照电子对抗规则实时处理各种信息， 当存在告警威胁 时，专家系统根据智能控制规则，从已知的对抗结果数据 库中找出与威胁类型相匹配的对抗决策记录， 并引导对抗 系统按决策要求进行对抗。对于未知或新型的威胁源，可 按经验数据或对数据进行不精确推理达到对抗目的。 系统 对多目标进行了决策优化，具有对抗多目标的能力。可对 载机干扰物投放后的威胁程度进行预测， 运用计算机仿真 载机、干扰物、导弹的运动轨迹，进行干扰效果检测。专 家系统具备知识学习、知识更新、知识删除、知识查询、 知识输出等功能。通过将实际威胁源数据、载机数据、干 扰物数据输入系统，输出结果经验证与实际试飞结果相 近，系统有较好的逼真度。经实测系统反应时间达到指标 要求。 吉林大学硕士学位论文 3外文文摘 （5000 字符以 内） The intelligent self- defense system using 1553B data bus presented in this paper is a new version self- defense countermeasure system based on the technologies listed above. The system consists of threat warning system, management control, expert system, integrated countermeasure system and 1553B data bus. The threat warning system is composed of radar warning receiver (RWR) and missile approaching warning system (MAWS)，and the countermeasure system is composed of radar active electronic countermeasure (AECM) and countermeasure dispensing system (CMDS). Intelligent countermeasure system resolved mainly the problem of countermeasure decision for the current combat aircraft facing the threats such as radar and IR guided missiles. When there is the threat, the warning expert system will search in the countermeasure base the countermeasure record that is matched with the threat type, control and initiate the countermeasure system against the threat according to the expert decision requirements. For the unknown threat sources, the countermeasures decision will be taken based on the empirical data or the coarse reasoning. Expert system is composed of knowledge base, reasoning machine, explanator, global database, human- machine interface, The knowledge of the expert system is obtained from the EW theory of the experts, practice experiences, test data and facts, data and principles in the field, including various mathematics models (aerial platform model, threat motion 吉林大学硕士学位论文 4model, countermeasure model) and target functions (waning levels, flight characteristics, threat azimuth, threat types mission status, atmospheric conditions etc). The expression method of the expert system is production rule method. This paper analyses and classifies the missiles various launching and guidance. Four intelligent launching mathematics models are created under the centroid jamming mode, they are: 1. Active radar homing air to air missile mathematics model, 2. Semi- active radar homing air to air missile mathematics model, 3. surface to air missile mathematics model, 4. IR homing air to air missile mathematics model. The countermeasure conditions are derived successfully: mFsinQ D(1+m)tg(Qp/2), the calculation formula of the countermeasure dispensing parameters Ta, Tb, Tc, Nb, Ng are obtained. Database of the self countermeasure expert system is the combination of self countermeasure knowledge. Countermeasure knowledge consists of dispensing rule and Meta- knowledge. Dispensing rule is the combination of the rules of dispensing time, dispensing direction, dispensing quantity. Meta rule is used to make the decision according to the type of the threat source, threat level, threat range, attack azimuth, platform characteristics and guidance weapons against host platform. The reasoning rule selection will enhance the reasoning effectiveness and the capability to resolve the problems. The tree structure is used for the knowledge base, which is the best structure for the knowledge base. 吉林大学硕士学位论文 5On detection of the threat information, the self countermeasure expert system will identify the threats, and based on the conditions such as performance of the countermeasure, combat field environment, aircraft status, host and foe etc, by using the reasoning machine, the decision for countermeasure mode, countermeasure time, countermeasure range and countermeasure intensity will be made. The reasoning method is based on the appropriate dispensing control decision target function. So this paper analyses in detail the basic operation function of the dispensing control decision target