先进战斗机过失速机动大气数据融合估计方法

可控的过失速机动是先进战斗机超机动性能的重要标志，飞机飞行包线的扩大已超出传统的大气数据系统测量范围，可靠的迎角、侧滑角、总压、静压等飞行大气数据是制约先进战斗机过失速机动中飞行控制的关键因素。以中国推力矢量验证机为对象，基于过失速机动飞行试验的数据，开展大气参数估计与验证研究。结合过失速机动的时间与空间特性，研究了基于风速、地速、空速矢量和惯性姿态、导航参数的大气参数融合计算方法；针对过失速大迎角状态下飞机周围气流非定常、模型非线性导致的融合大气参数误差的复杂特性，进一步构建深度神经网络，对机动状态融合迎角、侧滑角的强非线性误差进行拟合。仿真和飞行试验表明：该方法可在大迎角飞行状态下实现主要大气参数的融合估计，过失速机动过程中融合迎角误差优于2.3°，融合得到的大气参数可为过失速大迎角机动飞行控制提供可靠的大气参数状态反馈。     

Ionospheric TEC disturbances over China during the strong geomagnetic storm in September 2017

From September 7 to 8, 2017, a G4-level strong geomagnetic storm occurred, which seriously impacted on the Earth’s ionosphere. In this work, the global ionospheric maps released by Chinese Academy of Sciences are used to investigate the ionospheric responses over China and its adjacent regions during the strong storm. The prominent TEC enhancements, which mainly associated with the neutral wind and eastward prompt penetration electric field, are observed at equatorial ionization anomaly crests during the main phase of the storm on 8 September 2017. Compared with those on 8 September, the TEC enhancements move to lower-latitude regions during the recovery phase on 9 September. A moderate storm occurred well before the start of the strong storm causes similar middle-latitude TEC enhancements on 7 September. However, the weak TEC depletion is observed at middle and low latitude on 9–10 September, which could be associated with the prevailing westward disturbance electric field or storm-time neural composition changes. In addition, the storm-time RMS and STD values of the ionospheric TEC grids over China increase significantly due to the major geomagnetic storm. The maximum of the RMS reaches 12.0 TECU, while the maximum of the STD reaches 8.3 TECU at ~04UT on 8 September.     

水平导航中转弯航线解算方法的研究和仿真

在飞机显示器的水平导航区域上需要为飞行员实时显示最新的航线信息，航线中的每个航路点均有不同的转弯方式，目前国内正在研发的飞机采用旁切转弯和飞越转弯两种方式，若错过了预计的转弯起始点，则需要重新进行航线解算，这被定义为超调转弯，给出三类转弯航线的解算方法。     

智能方法在惯性系统误差参数辨识中的应用

总结了目前我国提高惯性系统导航精度的技术途径,阐述了国内外惯性系统误差参数辨识方法的研究现状,介绍了当前滤波算法、智能优化算法和人工神经网络方法在惯性系统导航领域的应用情况以及存在的不足。最后,分析了空间飞行器惯性系统误差参数辨识技术的未来研究方向,即智能优化算法和人工神经网络方法等智能方法将在惯性系统误差参数辨识中发挥越来越重要的作用,通过将误差系数标定问题转换为参数辨识问题,采用智能方法在庞大的解空间内实现对惯性系统误差参数的快速辨识。     

主辅拦截器协同制导方法研究

随着现代导弹技术的发展,导弹的突防能力越来越强,对导弹的防御难度也逐渐增大。为增强拦截器的杀伤力并降低成本,可利用主辅拦截器协同制导对目标进行拦截。建立了拦截器与目标的相对运动模型,通过对运动方程进行线性化分析,发现协同制导问题实质为具有终端时间限制条件的导引问题,该问题可转化为线性化系统的最优控制问题。利用最优控制中的极小值原理设计了时间协同制导律。仿真结果表明:该制导律可实现多枚拦截器在同一时刻拦截目标的协同制导要求。     

Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan

Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.     

基于ANFIS的智能导航自适应滤波算法研究

智能导弹等智能化飞行器在快速跨域、高速机动飞行时,由于传感器切换、外形改变等因素,会对组合导航信息融合系统引入随机非Gauss噪声等影响,离线优化的参数往往不能满足滤波器精度的需求。自适应网络模糊推理系统ANFIS是一种将人工神经网络和模糊推理技术相结合而成,符合人类认知特点的决策方法,它可以对导航数据进行学习,实现智能决策、实时修改滤波器内部参数,对滤波器进行优化。仿真结果表明,基于ANFIS优化的智能导航自适应滤波算法可以有效减少噪声和干扰带来的影响,提高导航精度。     

拦截高速目标的比例与反比例导引捕获区分析

针对拦截高速目标的作战特点，分析了比例导引(PN)与反比例导引(RPN)的捕获区。首先，通过分析拦截弹与目标的相对运动关系，推导得到了顺轨和逆轨的零控拦截条件，此条件由目标和拦截弹的速度前置角以及二者速度比确定；其次，以拦截弹和目标速度前置角为坐标系，推导得到了PN以及RPN捕获区以及各自导航比设置范围。PN的捕获区由逆轨零控拦截条件以及与其相切且斜率为1/(N-1)的两条直线构成，RPN的捕获区由顺轨零控拦截条件以及与其相切且斜率为1/(-N-1)的两条直线构成；然后，利用函数对称性将PN与RPN捕获区转换到同一坐标区间，得到了相同条件下RPN捕获区要大于PN捕获区的结论；最后，开展了四种情形下的仿真，验证了本文捕获区分析的合理性及有效性。     

基于Kalman滤波的变体飞行器T-S模糊控制

针对变体飞行器的跟踪控制问题,提出了一种基于Kalman滤波的T-S模糊控制方法。考虑飞行器系统状态不可测,引入惯导数据作为辅助信息,利用Kalman滤波算法融合飞控信息与惯导信息实现状态估计。由于变体飞行器在不同变形结构下气动特性变化较大,为便于控制器设计,采用小扰动线性化方法得到飞行器在不同平衡点处的局部线性模型,并通过状态反馈方法设计局部控制器,局部线性模型和局部控制器通过模糊集和模糊规则聚合成一个连续光滑的全局T-S模糊模型和T-S模糊控制器。通过综合Kalman滤波器与T-S模糊控制器得到一个基于Kalman滤波的T-S模糊控制器。仿真结果表明,该控制器在变形过程中能够实现状态估计,保证飞机的跟踪性能。     

基于纯比例导引的拦截碰撞角约束制导策略

拦截碰撞角约束制导是当前导弹制导研究的关键问题之一。首先基于理想比例导引（IPN）律拦截非机动目标的解析解,推导了纯比例导引律（PPN）拦截固定目标的解析解,得到了弹目相对距离、制导指令加速度和导弹前置角的显示表达式,并进一步得到了拦截碰撞角与弹目相对运动状态和比例导引系数之间的解析表达式。其次,基于该解析表达式,提出了基于PPN的拦截碰撞角约束制导策略（PPNIACG）,并探讨了在铅垂面内进行落角约束打击和水平面内进行拦截碰撞角约束打击的2种实现方式。最后,以弹道成型制导律（TSG）和最优碰撞角约束制导律（OIACG）为参考,通过数值仿真算例,对PPNIAC的拦截性能进行了对比分析,验证了所提出制导策略的有效性和正确性。