MB-OFDM UWB系统频偏估计方法改进研究

针对多带OFDM超宽带(MB-OFDM UWB)系统,依据物理层国际标准ECMA-368,对现有的频偏估计方法做了改进,提出了一种高性能、低复杂度、高鲁棒性的联合载波和采样频偏估计方法。该方法在SC算法基础上,通过选择合适的相关距离,使频偏估计算法适合于所有的跳频模式,同时也改善了估计性能。仿真结果表明,新方法在保证估计性能的基础上可有效降低复杂度,适合于高速MB-OFDM UWB系统。     

基于音色模型的多基频估计方法

为了有效解决复调音乐泛音重叠问题,提出了一种基于音色模型的多基频估计方法.分析了音色的时频特征,指出衰退和维持阶段的谐波结构稳定可靠、适合基频估计.根据谐波匹配率和强度筛选候选基频,采用频谱迭代删除的方法确定确切基频.依据最小谐波匹配率删减谱线,应用比例删除机制解决泛音重叠问题.仿真实验和实际乐曲测试结果表明,该方法精度高,可广泛应用于具有稳定谐波结构的音乐信号分析之中.     

Recent advances in rapid frequency estimation

There are two main types of frequency estimator—the traditional, based on FFT's, and the more modern, based on linear filtering. Statistical and computational efficiency usually have to be traded off against each other. Typically the filter-based estimators are statistically grossly inefficient. This paper discusses the extension of the Quinn–Fernandes (filter-based, statistically optimal) technique to complex-valued signals, and the use of zero-padding to improve the statistical efficiency of the Fourier transform interpolative (FTI) estimator to statistical near-optimality.     

Global frequency estimation using adaptive identifiers

Online estimation of the frequencies of a signal which is the sum of n sinusoidals with unknown amplitudes, frequencies and phases is made through yet another well-known and simple system theoretical tool-adaptive identifiers. Convergence of the proposed estimator is proved. The new frequency estimator is of 3n order, as compared to the order 5n - 1 resulting from Marino-Tomei observers. Results are demonstrated via simulation     

基于抽取与重构的瞬时频率估计算法

研究了在AWGN信道中载波信号采样序列瞬时频率的概率密度分布模型,并通过假设检验验证该分布模型。分析了不同采样速率和信噪比对瞬时频率概率密度分布的影响,根据该分析结论提出了一种基于抽取与重构的瞬时频率的估计算法,并且对该算法的性能进行了详细的分析;还对多载波信号采样序列瞬时频率产生混叠以至无法分辨的情况进行分析,并推导了瞬时频率完全混叠时的极限公式。最后通过蒙特—卡罗仿真验证了提出的瞬时频率的概率密度分布的正确性。     

分段自相关频率估计算法研究

针对两步自相关频率估计算法（TSA算法）的估计性能和计算量不能兼顾的缺点, 提出了基于正弦信号LP性质的分段自相关频率估计新算法。该算法首先将观测信号二等分, 得到与源信号频率相同、相位不同且噪声互不相关的观测信号, 然后利用正弦信号的LP性质, 结合自相关函数建立参数估计方程, 得到高精度频率估计算法, 最后通过多次蒙特卡洛仿真对算法的有效性进行了验证。仿真结果表明, 分段自相关算法整体优于TSA算法, 有较强的实用性。     

Local instantaneous frequency estimation of multi-component signals

We present a method for estimating the instantaneous frequency (IF) of multi-component signals. This method involves the calculation of a time–frequency energy density of the signal, then obtaining a local IF estimate from this joint density. Time–frequency energy density is calculated as a least squares optimal combination of multi-window Gabor based evolutionary spectra. The optimal weights are obtained by minimizing an error criterion that is the difference between a reference time–frequency distribution and the combination of evolutionary spectra. IF of the signal components is estimated from the final evolutionary spectrum at small time–frequency regions as the average of frequencies at each time. As such, local IF information of a multi-component signal can be estimated in the time–frequency plane.     

基于频域ICA的波达方向估计方法

为降低阵元数目和提高相干多径入射信号的波达方向(DOA)估计精度。提出了一种基于频域独立分量分析与波束零点形成相结合的DOA估计方法。该方法综合利用阵列结构信息和目标信号的统计独立特性,与常规算法相比,降低了算法对阵元数目和精度的依赖,并能实现对相干多径入射信号的DOA估计。计算机仿真结果表明,该算法具有少阵元、收敛快、误差小的特点。     

三次插值频率估计的改进算法

对正弦信号频率估计的几种插值算法进行了研究,重点介绍了一种精度较高的三次插值算法,针对其估计误差仍然较大,而且在频率接近某一区域时精度下降的情况,提出了一种修正算法,仿真结果证明该算法在只增加少量计算量的情况下性能非常优越。     

Recent history of known network breaches

One of the problems of network security is the belief by many managers that the expense in network defensive mechanisms are unsubstantiated and unsupportable as the problems with network security are simply not valid. There is no need to spend money on a non-problem and, if it is a problem, then the cheapest way out is usually selected.     

基于车载信息的多普勒频移估计方法研究

列车高速移动带来的多普勒频移问题增大了无线通信系统的误码率。经典Fitz估计算法已经无法适应高速环境下频偏大且变化速率大的特点。提出基于车载信息的多普勒频移估计方法,首先推导列车在不同行驶条件下的多普勒频偏公式,然后获取实时车载信息估计出多普勒频偏,最后结合改进Fitz估计算法进行第二次精确估计。通过构建无线信道传输误码率的仿真模型,利用matlab的simulink工具箱对列车行驶过程中误码率进行仿真。结果表明联合估计算法可以精确、实时估计列车高速移动带来的多普勒频偏,并且间接地增大了改进Fitz算法频偏估计范围。     

基于PN序列的频偏估计算法

本文提出了一种基于时域PN序列导频相关性的频偏估计算法,通过计算接收信号和发送信号共轭乘积的自相关函数,将频偏估计问题转化为一个单频谱估计问题,并且给出了简化的谱估计算法,从而避免了频率搜索,具有较低的实现复杂度,另外,此算法使用和符号同步相同的PN序列资源,节省系统频谱资源。在多径信道下也给出了相应的形式,经过理论分析和仿真证明了,在多径信道下,改进算法的获得了频率分集增益,提高了估计性能。     

基于粒子群算法的跳频信号参数估计*

针对基于时频分布的参数估计存在信噪比阈值和低信噪比下方差大的问题,提出了一种基于多峰优化粒子群算法的跳频信号参数估计新算法。该算法首先将跳频信号分解为时频原子的线性组合,然后由匹配原子获取跳频信号的参数估计。仿真结果表明,基于改进的物种形成粒子群算法能够搜索到与跳频信号分量相匹配的原子,与平滑伪魏格纳分布相比,提出的参数估计算法在低信噪比下具有较小的估计方差,更加适宜于电子战的实际应用。     

频率估计的多段正弦信号快速频谱融合算法

多段正弦信号频谱融合法（简称“原融合算法”）是提高低信噪比条件下正弦信号频率估计精度的一条有效途径,具有重要研究意义和应用价值。为满足雷达、声纳、电子对抗等实时性要求较高的频率估计应用需求,提出多段正弦信号快速频谱融合算法。该方法通过设计离散时间傅里叶变换（Discrete Time Fourier Transform,DTFT）快速算法、降维处理加权融合频谱矩阵和1/3主瓣相关性分析处理等措施来降低算法计算量,提高实时性。重点对上述三项措施的原理进行了阐述与分析。计算量对比和仿真实验表明,多段正弦信号快速频谱融合算法在精度损失极小的前提下,能够大幅降低计算量;在信噪比极低的情况下[(SNR-13 dB)],其性能略优于原融合算法。     

Entropy-based subspace separation for multiple frequency estimation

A subspace-based algorithm for estimating the order and the frequencies of multiple sinusoids embedded in noise is proposed. The new estimator (referred to as E-MUSIC) uses the entropy of a random variable related to the angles between the signal and noise subspaces as its objective function. Maximizing the entropy tends to achieve uniform angle distribution and thus leads to maximal subspace separation. The entropy-based objective function and the performance of the E-MUSIC algorithm is compared with some reference algorithms in the literature. Simulations which are performed in additive white and colored Gaussian noise show that the E-MUSIC offers an improvement for both model order and multiple frequency estimation. The improvement is more pronounced for high model orders and large SNR values.     

一种低复杂度的载波偏移估计算法

针对载波偏移引起OFDM系统的严重子载波干扰和性能下降这一问题,提出一种在承载数据子载波中间插入不承载数据的子载波的算法,算法是通过从时域OFDM符号的前半部分和后半部分的相位差获取频率偏移的信息来估计频偏的。这种算法不仅计算复杂度较低,而且估计准确,在多径信道条件下频偏校正后系统的性能能基本接近信道理想估计条件下的误比特率。