ID 原文 译文
12964 高频地波雷达(high frequency surface wave radar, HFSWR)对于海事监测具有重要的军用及民用意义，然而在HFSWR回波信号中，待检测的目标常常淹没在海杂波和各种背景噪声中。 High frequency surface wave radar (HFSWR) has important military and civilian significance for maritime surveillance. However, in echo signal of HFSWR, the signals of targets to be detected are often submerged in sea clutter and various background noises.
12965 因此，如何有效抑制杂波并实现多目标的自适应检测是HFSWR实现海事检测的关键和难点。 Therefore, effectve suppression of sea clutter and adaptve detection of multi-targets are the key and diffcult technque of maritime survelllance.
12966 该文提出了一种结合误差自校正极限学习机(error self-adjustment extreme learning machine, ES-ELM)和分数阶傅里叶变换 (fractional Fourier transform, FRFT)的多目标自适应检测算法。 In this paper, an adaptive detection a/gorithm of muti-targets combining error sef-adjustment extreme Earning machine (ES-ELM) and fractional Four i er transform (FRFT) i s proposed.
12967 算法根据相空间重构理论获得ELM的最佳状态空间,利用ES-ELM建立海杂波预测模型并对海杂波进行有效抑制。 In the algorithm, phase space reconstructon theory s employed to obta n the opt mal state space of ELM, and an ES-ELM s used to model and predct the sea clutter and suppress it effectively.
12968 再在分数域根据目标信号的峰值集聚特征，利用Haarlike算子提取目标点的形态特征，并通过ES-ELM神经网络对目标进行自动辨识。 In addtion, according to the agglomeraton characterstc of the peaks of objects n FRFT doman, Haar-lke descrptor s employed to obtan the morphologcal features of target po ints in FRFT domam, and a proposed ES-ELM based method is used to identify the multi-targets automatically and adaptively.
12969 实验结果表明，该文提出的算法具有良好的海杂波抑制能力，并可以实现海杂波背景下多运动目标的自适应高精度检测。 The experimental results show that the proposed algorithm has good sea clutter suppression abllity and realizes adaptive detection of multi—targets in background of high sea clutter with high detecon rate.
12970 气象卫星仪器使用的光谱中只有微波观测可以部分穿过云区,常被用来反演地表温度、海表温度等重要的地表参数。 Compared to visible and infrared spectrum used by meteorological satellite instruments,microwave remote sensing is not affected easily by atmosphere because of its strong penetration capability of the cloud, rain and atmosphere, and also its all weather and all day monitoring capabllity.
12971 近年来随着地面通信等主动微波技术的发展和商业服务中对微波波段的使用日益增多，被动接收来自地球-大气系统辐射的星载微波仪器观测越来越受到主动微波发射的影响，尤其是在低频波段遥感探测量中增加了不可预测的噪声，造成观测亮度温度相比视场内来自自然大气和地表发射、散射辐 射而言异常偏大，进而使反演的地表参数和资料同化的分析场具有较大偏差。 Moreover, microwave sensors are very senstve to changes of vegetaton characterstcs, sol mosture and snow parameters.
12972 卫星微波接收的来自地气系 统的被动热辐射与主动传感器发射的信号相混合,被称为无线电频率干扰(radio-frequency interference, RFI)，星载微波辐射计接收的辐射测量受地表反射的静止电视或通信卫星下行信号干扰,称之为电视频率干扰(TV frequency mterference, TFI)。 Such a phenomenon of satellte measured passive mi crowave thermal emission being miued with the signals from the active sensors is referred to as radio frequency interference (RFI). The interferences of the radance measurements from the meteorologcal satellite radiometric instruments with TV signals reflected off the ocean surface are known as television frequency interference (TFI).
12973 如果不正确识别和去除污染资料,将大大降低星载被动微波仪器的科学价值。 If not properly identified and rejected, this RFI or TFI contamination problem would could significantly reduce the science value of existing and future passive mcrowave missions.