Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

某型制导雷达部分元器件失效模式的分析

对某型号制导雷达部分元器件进行了失效分析，找出了导致元器件失效的原因，指出设计是提高可靠性的关键，并根据有关元器件情况对生产方与使用方提出了建议。着重讨论了设计师应注意的问题和应该遵循的设计原则。针对失效情况，提出了一些具体的设计构想。     

基于磁场映像的印制电路板故障诊断方法研究

简要分析了印制电路板的电磁场，提出了用电磁感应法测量磁场的电咱故障诊断新方法，并给出了测试系统组成方案。最后通过验证实验证明了该方法是确实可行的。     

频率及频率变化率的快速最大似然估计

信号参数估计是许多领域 (如雷达、通信、导航和声钠等 )都会遇到的共同问题。文中证明 ,牛顿法是实现频率 (η)和频率变化 (β)最大似然估值器的快速有效算法 ,并且详细分析了牛顿估值器的性能。研究证明 ,对于牛顿法 ,(η,β)是以三次方律收敛于真值 (η,β)的。模拟结果表明 ,当输出信噪比 ( SNR) o≥ 15 d B时 ,估计量的均方误差 ( MSE)达到Cramer- Rao界     

提高图像轮廓清晰度的快速插值放大方法

分析了当前主要的高清晰度图像插值放大方法,为实现快速放大而选择了基于图像轮廓插值改善清晰度的技术路线,并在已有算法的基础上开展了进一步的研究.提出了新的图像轮廓线光顺数值算法,对轮廓线划分的两类子区域提出了精度更高的插值算法.最后,以典型平面图形的图像和由3DMax生成的三维渲染图像为例对本文方法进行检验,与双线性插值结果的对比说明,该方法可以明显改善插值放大效果.     

逆合成孔径雷达信号处理方法研究进展

在简要评述国内外现有的逆合成孔径雷达（ISAR）信号处理的运动补偿和成象方法之后，介绍了南京航空航天大学ISAR课题组近年来在ISAR信号处理方法研究中取得的主要进展，包括基于多散射点定位观点的雷达成象观测模型，基于最大似然原理的同时运动补偿和成象方法，基于最大似然原理的多目标成象方法和基于时频分析的多目标成象方法，以及超分辩成象方法，文末指出了在ISAR信号处理方面有待进一步研究的问题。     

神经网络在未来超分辨雷达中的应用

最新的技术发展已为研制超分辨雷达创造了条件。它能够突破普通雷达基于匹配滤波原理的分辨能力,而实现超分辨。超分辨雷达的巨大计算量通常来自求解非线性最小二乘问题时的多维搜索。本文针对这一问题,研究了雷达信号处理中的两个典型例子:(1)利用阵列处理检测个数已知而方向未知的雷达目标;(2)对波音727飞机进行超分辨距离多普勒成像。说明Hop-field神经网络通过集体运算能够求解各种困难的最优化问题,因而在未来的超分辨雷达中有广阔的应用前景。     

航天雷达高度表

介绍几种航天雷达高度表，其中包括弹载雷达高度表、“土星”雷达高度表和“天空实验室”雷达高度表，最后介绍一种卫星雷达高度表的设计方法。