ID 原文 译文
20445 为在混响室中线缆共模干扰时的设备(EUT)进行临界辐射干扰场强测试，并确保与开阔场中测试结果一致，该文推导了线缆上共模电流满足的方程，将共模电流分解为相应的特征电流，计算了终端负载任意时线缆最大方向性系数的变化范围。 To test the radiated interference E-field threshold of Equipment Under Test (EUT) with common-mode interference of transmission lines in reverberation chambers and unify the test results with the open areas, the range of the maximum directivity of the lines with random loads is calculated by the derivation of the equation of the common-mode currents and decomposition of the currents into the corresponding characteristic ones.
20446 以单导体传输线和同轴线为EUT，分别在混响室和开阔场中测试线缆的临界干扰场强，对计算结果进行了验证。 The calculated results are validated with the experiments performed in a reverberation chamber and an open area, respectively, with a single conductor line and a coaxial cable as the EUT.
20447 结果表明：最大方向性系数的计算结果可以保证两种不同场地中测试结果的一致性，双线的共模干扰以及同轴线均可以等效为单线，且线缆弯曲对测试结果基本没有影响。 The theoretical and experimental results show that the test results in the two different areas can be unified with the calculated results. The common mode interference of two conductor lines and coaxial cables can be equivalent to single conductor lines and the bend of the lines almost has no influence on the test results.
20448 该文提出一种基于调频连续波(FMCW)雷达多维参数的卷积神经网络手势识别方法。 A multi-parameter convolutional neural network method is proposed for gesture recognition based on Frequency Modulated Continuous Wave (FMCW) radar.
20449 通过对雷达信号进行时频分析，估计手势目标的距离、多普勒和角度参数，构建出手势动作的多维参数数据集。 A multidimensional parameter dataset is constructed for gestures by performing time-frequency analysis of the radar signal to estimate the distance, Doppler and angle parameters of the gesture target.
20450 同时，为了进行手势特征提取和精确分类，提出多分支网络结构和高维特征融合的方案，设计出具有端到端结构的RDA-T多维参数卷积神经网络。 To realize feature extraction and classification accurately, an end-to-end structured Range-Doppler-Angle of Time (RDA-T) multi-dimensional parameter convolutional neural network scheme is further proposed using multi-branch network structure and high-dimensional feature fusion.
20451 实验结果表明，结合手势动作的距离、多普勒和角度信息进行多维参数学习，所提方法有效解决了单维参数手势识别方法中手势描述信息量低的问题，且手势识别准确率相较于单参数方法提高了5%～8%。 The experimental results reveal that using the combined gestures information of distance, Doppler and angle for multi-parameter learning, the proposed scheme resolves the problem of low information quantity of single-dimensional gesture recognition methods, and its accuracy outperforms the single-dimensional methods in terms of gesture recognition by 5%～8%.
20452 雷达通信一体化具有频谱利用率高、设备少等优势，该文在OFDM-LFM MIMO雷达的基础上，通过改变每个阵元发射信号的初始频率实现了雷达通信一体化。 Integration of radar and communication on the electronic war platform is an effective method to reduce volume and enhance spectrum usage and efficiency. A transmitted pattern based on OFDM-LFM MIMO radar is designed to realize the integration of radar and communication by changing initial frequency.
20453 通信接收端通过判别信号的频率实现信息解调； The communication receiver interpretation of the bit is based on the initial frequency of the signal.
20454 雷达接收端通过时域频谱拼接实现信号合成，达到与传统OFDM-LFM MIMO雷达一样的距离分辨率。 In radar receiver, the same range resolution as tradition OFDM-LFM MIMO radar can be get with get the time domain synthetic bandwidth methods.