ID 原文 译文
17375 该文提出一种基于改进3维后向投影的多圈CSAR相干3维成像方法，针对现有成像算法时间复杂度高的问题，提出一种构造几何插值核的CSAR改进3维后向投影算法， A coherent 3-D imaging method formulti-circular SAR based on an improved 3-D back projection algorithm is proposed. For the problem of hightime complexity of the imaging algorithm, an improved 3-D BP algorithm for CSAR based on constructinggeometric interpolation kernel is proposed.
17376 可将3维插值操作转化为1维插值操作和距离向量搜索操作，通过多圈CSAR改进3维后向投影成像结果相干积累的方式得到最终3维图像。 3-D interpolation operations are transformed into 1-D interpolationoperations and distance vector searching operations. The final imaging result is obtained by coherently accumulating the improved 3-D BP results of multi-circular SAR.
17377 该文所提方法可有效解决单圈CSAR 3维成像高程向分辨率低的问题，改善3维成像细节，同时能够大幅降低CSAR 3维成像时间。 The proposed method solves effectively the problem of low elevation resolution of single-pass CSAR, improves 3-D imaging details, and reduces greatly thetime of CSAR 3-D imaging simultaneously.
17378 仿真圆锥目标和美国空军实验室GOTCHA数据3维成像结果验证了该文所提方法的有效性。 The simulated 3-D imaging results of the conical target and GOTCHA data set from the US Air Force Laboratory verify the effectiveness of the proposed method.
17379 该文以通信系统中常用的典型微波部件——同轴连接器为研究对象，基于混沌理论对获得的同轴连接器的无源互调(PIM)功率时间序列进行分析，验证了使用混沌理论预测无源互调的有效性。 Passive InterModulation (PIM) products are spurious frequency signals which occur in microwaveand radio frequency communication system. And it is noticed that PIM levels have the characteristic ofchanging with time. In order to find out the relationship between PIM level and time, as the typical microwavecomponent which more often causes PIM in communication system, coaxial connector is chosen and analyzedusing chaotic method.
17380 首先通过实验系统获得同轴连接器的3阶无源互调功率时间序列，并对得到的实验数据进行相空间重构，确定该时间序列的最佳嵌入维数m和延迟时间τ。 Firstly, the third order PIM level time series of coaxial connector is obtained by PIMmeasurement system. Based on the experimental data, the phase space is reconstructed and the optimalembedding dimension m and delay time τ are confirmed.
17381 然后，结合最佳嵌入维数和延迟时间，分别构建相图和使用小数据量法计算该时间序列的最大Lyapunov指数，从而从定性和定量角度验证了该无源互调功率时间序列具有混沌特性。 Secondly, the largest Lyapunov exponent is calculated by the method named the small data sets with embedding dimension m and delay time τ. And from the qualitative and quantitative perspective, it is verified that the passive intermodulation level time series have the characteristic of chaos.
17382 在此基础上，基于获得的最大Lyapunov指数对该无源互调功率时间序列进行混沌预测，在最大可预测尺度范围内，理论预测值与实验值最大误差为2.61%，表明采用混沌方法预测无源互调功率效果较好。 Lastly, the prediction of PIM level with chaotic method is performed on the basis of the largest Lyapunov exponent.And the maximum error between the theoretical prediction value and the experimental value is 2.61% within the maximum predictable scale, indicating that the chaotic prediction is an effective way.
17383 该文提出的使用混沌理论预测通信系统中微波部件无源互调功率的方法，为开展无源互调抑制技术研究，提高通信系统的性能提供了新思路。 The method that predicts the PIM level of microwave components in the communication system discussed in this paper provides a new way of studying the PIM mitigation technique for communication system and provides a new idea for improving the performance of the communication system.
17384 近年来，基于机器学习(ML)的频谱感知技术为认知无线电系统提供了新型的频谱状态监测解决方案。 In recent years, Machine Learning (ML) based spectrum sensing technology has provided a newsolution in spectrum status identification for cognitive radio systems.