无人机协同测控中SC-FDMA技术设计

针对无人机协同任务测控传输的多机接入问题,提出基于分布式任务分配模型的高动态SC-FDMA技术.通过将贪婪原则、信道动态分配机制和多用户接入技术结合,利用集中映射方式设计子信道数目可调的映射规则,配置各无人机节点所占用子载波数目.仿真结果表明,与传统FDMA、CDMA、TDMA、OFDMA等相比,基于SC-FDMA设计...     

遥感卫星多路数据传输系统同频共用方法

为节省频率资源，遥感卫星通常采用扩频体制实现多路数据的同频共用传输，针对通道间容易引起相互干扰的问题进行了研究，通过改进码分多址干扰估算模型，对采用平衡Gold码序列扩频系统抗干扰容限上界进行预测。在满足国际电信联盟（ITU）对卫星辐射功率通量密度约束条件下，提出了一种基于直接序列扩频体制的两路业务数据同频共用传输方法。仿真结果表明：当载波频率2GHz左右，两路辐射源的EIRP之差不大于8～15dBw时可以实现同频共用传输；如对信号扩频带宽进行差异化处理，则其相互兼容性还可进一步提高。     

一种航天接口芯片静电防护电路的软击穿现象

接口阻抗测试是航天产品中对产品状态是否正常来进行判断的常用方法。在航天产品应用中，通常认为接口芯片阻抗测试异常即代表该接口芯片已经失效。本文针对一种LVDS接口发送芯片由静电导致阻抗测试异常，但功能正常的现象进行分析。在元器件失效分析的基础上，定位静电损伤的位置为芯片内部静电防护电路，从而建立了对应的电路模型，对芯片静电损伤的现象进行理论分析。分析说明：该芯片在被静电打击时，其静电防护电路中一个NMOS管受损，但该电路保护了芯片的功能电路，被击穿的NMOS管等效为一个电阻，因此导致阻抗测试异常，但芯片功能电路未受损的现象，为静电软击穿现象。且可认为该芯片在受静电影响后并未失效，相关电路仍具有正常工作的能力。即阻抗异常现象并不是芯片失效的充分条件。     

主动全向声纳浮标性能预测

主动声纳浮标适合探测安静型潜艇,预测主动声纳浮标的性能已成为航空反潜战的重要内容。文章首先简要分析了水声传播模型、海底和海面损失模型以及混响模型等声纳模型的优劣并进行合理选择；在此基础上,提出了一种主动全向声纳浮标性能预测系统的总体方案,并设计了相应软件；最后,针对不同的海洋环境进行仿真实验。该系统能预测主动声纳浮标在各传播方向、水平距离和深度的传播损失及检测概率,可以用于分析浮标性能的时空变化特性,为优化使用声纳浮标提供参考。     

Transfer learning: A new aerodynamic force identification network based on adaptive EMD and soft thresholding in hypersonic wind tunnel

The aerodynamic test in the pulse combustion wind tunnel is very important for the design, evaluation and optimization of aerodynamic characteristics of the hypersonic aircraft. The test accuracy even affects the success or failure of hypersonic aircraft development. In the aerodynamic test of pulse combustion wind tunnel, the aerodynamic signal is disturbed by the inertial force signal, which seriously affects the test accuracy of aerodynamic force. Aiming at the above problems, this paper innovatively proposes an aerodynamic intelligent identification method, that is the transfer learning network based on adaptive Empirical Modal Decomposition (EMD) and Soft Thresholding (TLN-AE&ST). Compared with the existing aerodynamic intelligent identification model based on deep learning technology, this study introduces the transfer learning idea into the aerodynamic intelligent identification model for the first time. The TLN-AE&ST effectively alleviates the problem of scarcity of training samples for intelligent models due to the high cost of wind tunnel tests, and provides a new idea for further implementation of deep learning technology in the field of wind tunnel aerodynamic testing. And this study designed residual attention block with soft threshold and dense block with adaptive EMD in TLN-AE&ST model. Residual attention block with soft threshold module can more effectively suppress the influence of instrument noise signal on model training effect. Dense block with adaptive EMD makes the deep learning model no longer a black box to a certain extent, and has certain physical significance. Finally, a series of wind tunnel tests were carried out in the Φ = 2.4 m pulse combustion wind tunnel of China Aerodynamic Research and Development Center to verify the effectiveness of TLN-AE&ST.     

Contributions to data transmission at critical moments on unmanned aerial vehicles

As for unmanned aircraft, the knowledge of the aircraft performance is directly related with the navigation, guidance, and control system programming. Therefore, the measured data in each phase of the flight must be sufficiently precise to obtain a good characterization of aircraft. This article proposes new methods of sending information to ground, which make it possible to know the aircraft behavior accurately, and for this purpose, four contributions have been made for ALO (Avión Ligero de Observación, Spanish acronym for Light Observation Aircraft). Currently, the characterization is based on data obtained at ten samples per second, insufficient to acquire detailed knowledge of what happened during the whole flight of an aircraft. As a result of these contributions, many more samples per second of accelerations and angular velocities are obtained at the most critical moments of the flight, such as takeoff or landing. Among the improvements included are data compression techniques, providing references to locate the measured data in time and identifying labels of each parameter.     

复合材料整流罩声学等效建模与低频隔声性能研究

运载火箭发射过程中的恶劣噪声环境会导致整流罩内部电子设备失效。开展整流罩的内声场环境预测以及隔声分析,对其降噪研究和优化设计具有重要意义。复合材料整流罩舱壁大量使用蜂窝夹芯板,基于蜂窝夹芯结构精细化模型开展整流罩内声场环境预示计算量大,无法适用。本文建立了复合材料蜂窝夹芯板的力/声学等效模型,并利用精细化模型验证等效模型的精度;进一步基于有限元-边界元方法对某整流罩结构进行低频声振分析;同时,对整流罩的隔声量进行了评价。结果表明:整流罩内声场在频率为160 Hz附近声学环境较为恶劣,整流罩的降噪研究应针对该频段进行。