基于严格解析谱的同轨双基SAR的CS成像算法

针对双基地合成孔径雷达(synthetic aperture radar, SAR)包络徙动的空变问题,提出一种同轨等速双基构形下基于几何关系公式方法推导出的严格解析双基频谱的线频调变标(chirp scaling, CS)成像算法,不同于波数域的成像算法,整个成像过程不需要进行插值运算,在频域聚焦实现快速成像。高精度的双基频谱使得其对基线的长短不再敏感,可以进行长基线情形下的数据处理。仿真实验验证了本文算法的有效性。     

窄带相参雷达调制谱超分辨处理方法

针对采用时分体制下窄带相参雷达对单个目标的连续跟踪时间变短,导致频谱分辨率降低的问题,提出了一种连接不同时间段回波信号的方法。该方法利用MUSIC算法估计窄带雷达时域回波的模型参数,然后用该模型连接不同时间段信号。通过该方法,可以提高窄带相参雷达时分多目标跟踪时的频谱分辨率,有利于调制谱特征的提取。对仿真和实测数据的分析处理验证了该方法的有效性。     

基于特征值的频谱感知算法仿真研究

频谱感知是认知无线网络中的一个重要功能,是实现其他功能的基础。研究了新型的基于特征值的感知算法,充分利用随机矩阵的渐近谱分布特性和特征值的收敛特性来设置判决门限,提高感知性能。理论分析和仿真结果均表明,新型算法性能明显优于典型的能量检测算法,克服了能量检测算法的噪声不确定性问题。

Abstract：

Spectrum Sensing is an important function in the cognitive radio networks.A new eigenvalue-based detection scheme for spectrum sensing was studied,and decision thresholds were set to have good performance by using the property of asymptotic spectrum distribution and convergence of maximum eigenvalue of random matrices.Theoretical analysis and simulations results show that the new detection scheme can obviously outperform the classical energy detection,and overcome the noise uncertainty problem.     

脉冲无线电技术在军事通信中的应用

衡量一种军事通信技术优劣的重要指标是其抗干扰性能和隐蔽性,而具备这些优良特性的脉冲无线电技术当前的研究热点是在短距离宽带无线接入中的应用。针对典型的超宽带实现方案脉冲无线电技术进行研究,首先分析了它与传统的直接序列扩频技术的差别,然后着重研究了它的抗干扰性能和抗检测/截获性能,并与DSSS技术进行对比,结果表明脉冲无线电超宽带技术比传统的DSSS技术具有更好的抗干扰性能和隐蔽性,更加适于军事通信应用。     

频谱分析方法在仿真可信性研究中的应用

应用频谱分析方法进行仿真可信性评估。分析了傅立叶谱估计、最大熵谱估计的统计特性,并分别构造相容性检验。引入瞬时谱估计分析非平稳随机信号,以及应用于某型近炸引信数字仿真模型验证的一个实例。     

子波变换新方法

本文在理论分析子波变换物理概念的基础上,提出了一种工程上应用的新颖快速子波变换算法,即“频谱切割法”。该方法能够在电路上实现实时的快速子波变换。     

Opportunistic spectrum sharing in software defined wireless network

Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.     

FORECASTING ：EXCHANGE RATES： AN OPTIMAL APPROACH

This paper looks at forecasting daily exchange rates for the United Kingdom, European Union, and China. Here, the authors evaluate the forecasting performance of neural networks （NN）, vector singular spectrum analysis （VSSA）, and recurrent singular spectrum analysis （RSSA） for fore casting exchange rates in these countries. The authors find statistically significant evidence based on the RMSE, that both VSSA and RSSA models outperform NN at forecasting the highly unpredictable exchange rates for China. However, the authors find no evidence to suggest any difference between the forecasting accuracy of the three models for UK and EU exchange rates.     

灰色Verhulst预测模型的病态特性

为揭示灰色Verhulst模型的建模精度在原始序列存在微小扰动下的变化规律,采用矩阵谱条件数作为研究工具对该模型系数矩阵谱条件数的取值进行分类讨论. 研究结果表明,当且仅当系统原始数据序列第一项为大于零的常数,其他所有项数据皆为0时,建立灰色Verhulst模型才会呈现严重病态性,而采用已呈现特定规律的数据序列构建灰色Verhulst预测模型毫无实际意义. 研究结论认为,灰色Verhulst模型并不存在严重病态性.     

光纤耦合器对光谱响应的研究

 通过对耦合的理论分析,模拟了实际的拉锥过程,构建了光纤耦合器对光谱响应特性的理论模型。详细分析了不同熔烧长度和不同拉伸距离对光谱响应的影响,熔烧长度越短,拉锥曲线震荡越剧烈,到达归一化光功率为0.5所需要的拉伸长度越短,会出现更多的震荡包络;拉伸距离越长,产生的包络震荡越多,波长间隔越密,对光谱响应越为敏感,从实验中验证其合理性。这一模型的建立将大大减少实际工作中的盲目性,对光纤耦合器制作有一定的指导意义。