盒子波调查技术在六盘山黄土塬区的应用分析

六盘山盆地被巨厚的黄土所覆盖,是表层和深层双复杂区域。巨厚的黄土和复杂的地形条件使该区干扰波非常发育,严重影响了地震资料的信噪比。为了有效调查该区干扰波发育特征,并进行针对性地压制,通过盒子波调查技术在该区的应用分析,提出了和生产结合进行盒子波调查的有效方式,克服了静校正问题对盒子波调查数据的影响。针对两种地形条件下的盒子波资料,分析了在不同地形和表层条件下干扰波场的变化,认为影响浅层和中深层信噪比的干扰波特征存在差异;并通过组合压噪效果分析,提出对不同深度勘探目标进行针对性压噪的组合接收方式,提高了六盘山地区巨厚黄土塬勘探区目标层采集资料的信噪比。     

顾及空间相关性的遥感影像信息量的度量方法

提出了一种结合信息论与地学统计法的遥感影像信息量计算的方法。此方法基于遥感影像加性噪声模型和互信息上界的计算原理,同时考虑了噪声和空间相关性等影响遥感影像信息量的因素,适于计算具有稳健空间相关性、不同地物类型的光学影像的信息含量。利用Landsat TM影像子集,分别计算了城市、农田、山地3种不同地物类型的影像信息量。结果表明,城市含有最大的信息量,同时影像信息量与影像方差呈对数正相关关系。     

噪声抑制的多极化SAR海冰图像分割

合成孔径雷达(SAR)海冰图像分割对全球气候研究和保证船舶航行安全具有重要意义。现有的基于区域的马尔可夫随机场(MRF)多极化SAR分割方法,由于受相干斑噪声影响,其区域划分不尽合理,不能有效完成分割。因此,提出一种噪声抑制的多极化SAR海冰图像分割算法,首先在极化总功率图上引入降低噪声的滤波算法,合理划分初始区域,其次考虑区域之间的差异度,从而实现多极化SAR海冰图像的准确分割。以RADARSAT-2和SIR-C获得的全极化海冰图像为实验数据进行验证,结果表明:和其他较先进算法相比,本文算法优势明显,既能高效保持图像连通性,又能增强图像的细节信息,具有更高的分割精度。     

高轨卫星轨道预报中神经网络模型优化设计

高轨卫星是我国卫星导航系统的重要组成部分。提升该类卫星的轨道预报精度有利于用户定位精度的提高。提出了一种改进高轨卫星轨道预报精度的新方法。该方法避开了精化动力学模型的困难,尝试从轨道预报误差的规律中寻找突破。利用神经网络作为建立预报模型的工具,将某历史时刻的轨道预报误差作为训练样本,利用训练好的神经网络模型补偿当前时刻的预报轨道以提高轨道预报精度。对影响神经网络模型补偿效果的各因素进行了详细分析,制定了适应于高轨卫星短期、中期和长期预报的神经网络最优模型。利用实测数据进行了试验分析,结果表明:预报8,15及30 d应选择的训练步长分别为10,20及25 min;轨道预报8~30 d时,训练噪声均选取0.01。神经网络模型有效地改进了高轨卫星的轨道预报精度,预报4~30 d,轨道精度提高幅度为34.67%~82.37%不等。     

Seismic random noise attenuation and signal-preserving by multiple directional time-frequency peak filtering

Time-frequency peak filtering (TFPF) is an effective method for seismic random noise attenuation. The linearity of the signal has a significant influence on the accuracy of the TFPF method. The higher the linearity of the signal to be filtered is, the better the denoising result is. With this in mind, and taking the lateral coherence of reflected events into account, we do TFPF along the reflected events to improve the degree of linearity and enhance the continuity of these events. The key factor to realize this idea is to find the traces of the reflected events. However, the traces of the events are too hard to obtain in the complicated field seismic data. In this paper, we propose a Multiple Directional TFPF (MD–TFPF), in which the filtering is performed in certain direction components of the seismic data. These components are obtained by a directional filter bank. In each direction component, we do TFPF along these decomposed reflected events (the local direction of the events) instead of the channel direction. The final result is achieved by adding up the filtering results of all decomposition directions of seismic data. In this way, filtering along the reflected events is implemented without accurately finding the directions. The effectiveness of the proposed method is tested on synthetic and field seismic data. The experimental results demonstrate that MD–TFPF can more effectively eliminate random noise and enhance the continuity of the reflected events with better preservation than the conventional TFPF, curvelet denoising method and F–X deconvolution method.     

小波框架的彩色图像泊松去噪

噪声是影响图像质量的重要因素,噪声的存在导致图像的某些特征细节不能被辨识以及图像的信噪比下降,所以图像去噪是图像处理中的一个重要问题.本文提出了基于小波框架的彩色图像的泊松去噪模型.在该模型中,赋权的l²项作为保真项,包含小波框架的l¹项作为正则项.同时,又提出了解决该模型的重新赋权的split Bregman算法.最后,利用仿真实验以及PSNR（峰值信噪比）指标对该模型的去噪效果进行评估,评估结果表明该算法可行、有效.     

确定风廓线雷达功率谱噪声功率方法

风廓线雷达以测风为主要目的设计,没有充分考虑强度的定量测量。如果能够实现强度定量测量将大大扩展风廓线雷达的应用范围。首要的扩展应用就是可以获取雨滴谱分布、解决降水定量测量准确性问题。若实现强度定量测量,需要解决的一个关键技术问题是如何由其功率谱数据准确计算噪声功率。该文根据风廓线雷达功率谱估计方法、依据噪声频域统计特性,提出了一种计算风廓线雷达功率谱噪声功率的方法,并利用风廓线雷达实测功率谱数据进行检验。检验结果表明:即便在有降水或存在地物时,该方法仍可以准确、快速分辨出噪声功率谱, 且客观有效。     

Model of wind-generated ambient noise in stratified shallow water

In order to build a rapid ocean ambient noise model adapted for a stratified shallow water, a hybrid model of normal mode method (for far field) and ray method (for near field) is suggested which combines the advantages of both methods. Since the near field of wind-generated noise is not sensitive to the sound speed profile, the sound speed profile is regarded as a constant; which makes the model rapid and accurate. The simulation results are in agreement with those of the wave model.     

高稳定性数字钟的分析与实现

介绍一种高稳定、低功耗、多功能、小型化的数字钟 ,由数字钟插入相位噪声引起的 1pps输出信号相位抖动为 5 .3ps,前沿上升时间为 4 .6ns ,指标测量通过 2m长 5 0Ω高频同轴电缆并接 5 0Ω电阻性负载 ,输入信号为 10MHz正弦波信号 ,移相精度为 10 0ns,同步精度≤ 10 0ns,通过RS 2 32接口每秒一次的速率以ASCII码格式输出时间信息 (年、月、日、时、分、秒 ) ,在接数显钟面时其功耗为2W ,不接数显钟面时为 1.2W。     

On the analysis of light curves in asteroseismology

We provide a detailed introduction to the main problems arising when analyzing light curves in asteroseismology. Attention is first paid to the signal model delivered by the pulsating stars and to the noise sources corrupting this model in photometric observations. The main pitfalls and ambiguities occurring in Fourier analysis are summarized and illustrated. Some classical, Least Squares (LS) based methods for spectrum analysis are analyzed and commented on from the point of view of ill-posed problems. The insight that can be gained from such analyses is discussed.