贝叶斯频率估计中频率的先验分布对有色噪声作用的影响

在贝叶斯参数估计理论框架下,研究了被测参数的先验分布对有色噪声的抑制作用.选择一个受1/f~α型谱密度有色噪声影响的自旋1/2量子比特作为量子探测系统来估计一个磁场强度的大小,利用贝叶斯代价函数的动力学演化来评判估计的精度,重点研究先验概率分布对噪声非高斯性的限制作用.研究发现:当先验概率的不确定度比较大时,有色噪声的非高斯性对频率估计精度的影响比较小;当先验概率的不确定度比较小时,有色噪声的非高斯性对频率估计精度的影响比较大.     

双数态输入型M-Z干涉仪中量子相位的最大似然估计和贝叶斯分析

本文采用最大似然估计和贝叶斯分析两种方法,对双数态输入型马赫-曾德尔干涉仪中的量子相位估计进行研究.通过对干涉仪输出端粒子数差和宇称进行理论计算和数值模拟,发现采用贝叶斯分析和粒子数差测量的组合,可以在全相位空间实现最优测量,即待估相位精度达到由量子克拉美罗下界所给定的测量极限,同时,利用贝叶斯分析进行相位估计所需样本数较最大似然估计更少.在通过宇称测量进行相位估计的研究中,发现无法利用贝叶斯分析实现相位估计,但可采用最大似然估计进行研究.借助蒙特卡洛数值模拟分析,我们验证了理论计算结果,即相位估计精度会随待估相位θ₀的变化而改变,将其与粒子数差测量结果对比,进一步确认了粒子数差测量方案的优越性.     

超声回波参数估计的初值选取方法

针对超声回波参数估计中,初值随机选取带来的收敛速度慢,搜索效率低,易受噪声影响等问题,对回波参数估计的初值选取进行了探讨。理论上研究了超声回波信号的包络和能量与信号参数的关系,阐明了从信号自身选取参数初值的可行性。在此基础上,利用希尔伯特变换和傅里叶变换提取有效信息,为回波参数估计提供合适的初值,从而减少估计过程的迭代次数、提高参数估计速度。实验结果表明,与传统参数估计方法相比,该方法在不同信噪比情况下都可获得较高的估计精度,而且参数估计的收敛速度较快。      

广义互相关电晕放电辐射信号时延估计方法

电晕放电等辐射源定位多采用基于时延估计的时差定位方法实现的,在现场条件下,各种背景噪声和干扰对时延估计精度造成影响。在分析国内外研究动态的基础上,针对基本互相关时延估计存在的分辨率低、稳健性不高等局限性,研究基于广义互相关的时延估计算法,并且通过采用不同的权值函数进行仿真比较和实验验证,寻找适用于电晕放电辐射信号时延估计的方法。研究表明:基于Hassab-Boucher (HB)加权的广义互相关时延估计方法对实际测试环境中存在的周期性干扰具有较好的抑制效果,时延估计误差达4.5%,精度较高,在实际的工程应用中用于对电晕放电信号进行时延估计和远距离定位是可行的。     

面向低强度无线网络信号接收谱参数估计研究

针对以北斗卫星导航信号为代表的亚纳秒级的低强度无线网络信号在定位中难以获取精确时间估计及角度估计,且易受环境噪声影响,使其定位精度不高等难题,本文提出了基于亚纳秒级的低强度无线网络信号接收谱参数估计方法。首先通过抽样方式,将发射信号抽样为多维独立子信号并独立建模,通过构造噪声空间与子信号空间在对应列向量正交化的基础上精确获取TOA估计;随后利用复数域映射,在获取TOA估计基础上采取比对方式精确地获取DOA估计。最后对本文参数估计方法进行了精度分析。测试数据显示：与 PM算法、ESPRIT算法相比,本文技术在TOA及DOA估计上更为精确;同时在信号强度低且背景噪声干扰严重的情况下,本文方法仍可有效的维持参数估计精度。     

Nonequilibrium Effects on the Precision of Parameter Estimation

The impact of nonequilibrium environment effects on the accuracy of quantum parameter estimation is investigated, and it is found that these effects can significantly affect estimation accuracy. Using an individual estimation strategy reveals that the nonequilibrium effects consistently enhance accuracy, regardless of the coupling strength between the probe and its environment. In contrast, weak memory effects undermine estimation accuracy. When employing a multi-parameter simultaneous estimation strategy, it is observed that the nonequilibrium effects consistently improve the advantages of simultaneous estimation, as analyzed by the ratio of total variances between the two estimation scenarios. However, the memory effects on these advantages depend on the coupling strength between the qubit and the environment. These findings suggest that appropriate parameters of a nonequilibrium environment can increase the quantum Fisher information (QFI), thereby enhancing the accuracy of quantum parameter estimation. These significant results are essential for improving parameter estimation accuracy in quantum systems interacting with nonequilibrium environments.     

基于可见光谱与轻量级卷积神经网络的冬小麦分蘖数估算

分蘖数是表征冬小麦生长的关键性参数,对于冬小麦苗情监测、产量预估具有重要意义。针对目前冬小麦分蘖数估算方法存在的数据获取繁复和估算模型体量大的问题,提出一种基于可见光图像和轻量级卷积神经网络的冬小麦分蘖数估算方法,以期实现冬小麦分蘖数无损快速估算,并且可嵌入移动终端设备。可见光图像具有获取便捷,处理简单的特点,利用数码相机连续采集2017年—2018年和2018年—2019年两个生长季的冬小麦冠层可见光图像。利用该数据图像,分别构建基于轻量级卷积神经网络MobileNetV2,SqueezeNett,ShuffleNet的冬小麦分蘖数估算模型进行比较试验,并与基于非轻量级卷积神经网络AlexNet和ResNet系列构建的估算模型进行对比试验。开展冬小麦分蘖数估算模型针对不同植株密度数据的鲁棒性以及针对不同生长季数据的泛化能力的验证试验。结果表明,基于MobileNetV2构建的冬小麦分蘖数估算模型的决定系数（R2）为0.7,归一化均方根误差（NRMSE）为0.2,在三个轻量级卷积神经网络中具有最优表现;基于非轻量级卷积神经网络构建的冬小麦分蘖数估算模型体积是基于MobileNetV2构建的冬小麦分蘖数估算模型的2.3~16.1倍。与非轻量级卷积神经网络相比较,基于MobileNetV2构建的估算模型在具有较好R2的同时有较小的体量,适宜嵌入移动终端设备;针对120,270和420 株·m-2三个不同植株密度的可见光图像数据集,基于MobileNetV2构建的冬小麦分蘖数估算模型的R2分别为0.8,0.8和0.7,表现鲁棒;针对两个生长季的可见光图像,基于MobileNetV2构建的冬小麦分蘖数估算模型通过迁移学习将R2提升了2倍,NRMSE下降了7.6%,表现出对数据季节性差异较好的适应性,体现了模型的泛化能力。利用可见光图像,基于MobileNetV2构建的估算模型能够满足冬小麦分蘖数估算需求,为冬小麦生长观测以及田间农艺措施管理决策提供了一个准确、鲁棒、可嵌入移动终端设备的工具。     

不同时间尺度下锂电池SoC估算研究

针对当前电池荷电状态(SoC)估算算法在处理器运算过程中计算量大,耗费处理器资源多的问题,提出在SoC估算中同时增大辨识时间尺度和估算时间尺度。采用带遗忘因子递推最小二乘算法辨识电池模型参数,并探究不同大小的时间尺度对SoC估算精度的影响。仿真结果表明,随着辨识时间尺度和估算时间尺度增大,SoC估算精度下降且计算量快速下降,计算消耗时间呈指数减少;当时间尺度过大时,SoC估算精度难以保证,计算消耗时间减少不明显,收敛时间长;在综合考虑估算精度和计算耗费时间情况下,可以找到一个最优的时间尺度用于保证SoC估算精度同时大大降低计算量。该方法为后续实现电动汽车SoC在线估算提供理论依据。     

Fast Estimation Algorithm for Calculation of Reflectance Map based on Wiener Estimation Technique

We propose a fast estimation algorithm for calculation of a reflectance map from measured radiances based on Wiener estimation technique. This technique uses many sample data of reflectance maps to decide transformation for accurate estimation. Reflectance maps of objects are estimated rapidly by linear operation between a vector of measured radiances and an estimation matrix previously calculated based on the sample data.     

噪声方差未知时的分布式量化估计融合方法

为了解决观观测噪声和信道噪声概率分布不完全已知时的多传感器分布式量化估计融合问题,提出了一种期望极大化算法(EM算法)的分布式量化估计融合方法。该方法将未知的噪声参数以及局部量化器量化概率建模为EM算法中二元高斯混合模型参数,利用极大似然估计方法的估计不变性得到目标参数的估计融合结果。仿真实验结果表明:该方法在局部传感器观测样本数目大于6000和信噪比大于6 dB时与已有理想信道条件下的估计方法性能相当。本文方法对水下分布式协同探测问题提供了一种简化的估计融合实现途径。      

基于中国余数定理的欠采样下余弦信号的频率估计

基于中国余数定理的重构算法的信号频率估计是近年来信号处理、电磁学以及光学等领域的前沿问题,但目前这些研究仅限于对复指数信号做粗略频率估计.因而,本文把基于中国余数定理的频率估计从复指数信号粗估计拓展到实余弦信号精细估计领域,其所提出的估计方案处理过程如下:1)对高频余弦波形进行过零点检测,确定信号的相位信息;2)对各路欠采样信号做快速傅里叶变换,并借助Candan估计器对各路谱峰值做频率校正以获取高精度余数估计,基于此算出频偏值以做相位校正;3)用提出的基于相位特征分类方法对校正得到的余数做筛选;4)将筛选出的频率余数代入闭合形式的中国余数定理得到原信号频率的高精度估计.此外,本文还推导出了频率估计方差的理论表达式.数据模拟实验验证了该表达式的正确性,实验结果还反映了本文提出的方案具有高精度和高抗噪性能.     

动态图像序列运动矢量估计算法的研究

运动估计在电子稳像系统中起重要的作用。介绍和比较了几种运动矢量估计算法。为了提高电子稳像系统的性能,提出了在设计电子稳像系统时选取运动矢量估计算法的原则。通过比较应用在航摄图像序列中的投影算法和匹配算法的性能,说明了如何应用运动矢量估计算法的原则。仿真结果表明,根据此原则选取的运动矢量估计算法应用于电子稳像系统是可行的。     

The auto-measurement of the gap of LCD glass plates using sub-pixel accuracy estimation

In this paper, the distance between laser spots has been measured using sub-pixel accuracy estimation and the accuracy has been tested in a noise environment. Here, the correlation like method (CLM) is used for the distance measurement between two laser spots and to count the estimation precision effect under noise factor by relevant CLM theorems. From the maximum value of the data series, then the position of the center of laser spot can be derived by interpolation. The estimation precision effect under noise factor and DC offset are tested and analyzed by a computer system. Also, for improving the estimation precision, a Kalman filter, which is often applied for random estimation and control theorem, is adopted. The innovation research combines CLM, and Kalman filter in sub-pixel accuracy estimation is more precise. This method can be used for measuring the gap of LCD glass plates, of optical strain gauge and the characteristics of spectral, quickly and can be automated.     

Spectral estimation of NMR relaxation

In this paper, spectral estimation of NMR relaxation is constructed as an extension of Fourier Transform (FT) theory as it is practiced in NMR or MRI, where multidimensional FT theory is used. nD NMR strives to separate overlapping resonances, so the treatment given here deals primarily with monoexponential decay. In the domain of real error, it is shown how optimal estimation based on prior knowledge can be derived. Assuming small Gaussian error, the estimation variance and bias are derived. Minimum bias and minimum variance are shown to be contradictory experimental design objectives. The analytical continuation of spectral estimation is constructed in an optimal manner. An important property of spectral estimation is that it is phase invariant. Hence, hypercomplex data storage is unnecessary. It is shown that, under reasonable assumptions, spectral estimation is unbiased in the context of complex error and its variance is reduced because the modulus of the whole signal is used. Because of phase invariance, the labor of phasing and any error due to imperfect phase can be avoided. A comparison of spectral estimation with nonlinear least squares (NLS) estimation is made analytically and with numerical examples. Compared to conventional sampling for NLS estimation, spectral estimation would typically provide estimation values of comparable precision in one-quarter to one-tenth of the spectrometer time when S/N is high. When S/N is low, the time saved can be used for signal averaging at the sampled points to give better precision. NLS typically provides one estimate at a time, whereas spectral estimation is inherently parallel. The frequency dimensions of conventional nD FT NMR may be denoted D₁, D₂, etc. As an extension of nD FT NMR, one can view spectral estimation of NMR relaxation as an extension into the zeroth dimension. In nD NMR, the information content of a spectrum can be extracted as a set of n-tuples (ω₁, … ω_n), corresponding to the peak maxima. Spectral estimation of NMR relaxation allows this information content to be extended to a set of (n + 1)-tuples (λ, ω₁, … ω_n), where λ is the relaxation rate.     

Fast estimation of array gain of vertical transmit array in Pekeris waveguide

In order to estimate the sound intensity level of vertical transmit array(VTA) from that of single transducer,a fast estimation method of transmit array gain(TAG) in Pekeris waveguide is studied.At first,the average sound intensity of VTA is calculated on the basis of normal mode theory with the effective depth,and the TAG expressed by the summation of modes is derived.Then by using integral,instead of summation,of modes order,the fast estimation expression of TAG in 3/2 power field is derived along with error correction.Because only the first mode exists in effective shadow zone(ESZ),the fast estimation expression of TAG in ESZ is derived by directly simplifying the former expression.All of the fast estimation errors of computer simulations and experiment in shallow water are less than 1 dB,which can verify the validity of the fast estimation method.This fast estimation method of TAG can provide references for practical application.     

基于两级压缩感知的脉冲星时延估计方法

为了快速获得高精度的脉冲星累积脉冲轮廓时延估计,提出了一种基于两级压缩感知的时延估计方法.压缩感知主要包括三个部分:字典、测量矩阵、恢复算法,其中字典尺寸是影响压缩感知估计精度的重要因素.针对压缩感知中字典的原子数增加虽能提高估计精度但又带来计算量大的问题,该方法采用粗估计与精估计两级字典相结合,先利用粗估计字典原子间隔大的特点进行累积脉冲轮廓全相位估计,得到预估时延值,再利用精估计字典的原子间隔小且个数少适合局部估计的特点对累积脉冲轮廓进行精确时延估计.理论分析与实验结果表明:两级字典数据量比传统字典小两个数量级,在相同的时延估计精度下,该方法比传统压缩感知方法计算量大幅度减少,是一种能保持高估计精度并有效降低计算量的脉冲星时延估计方法.     

MIMO声呐的双尺度旋转不变子空间波达方向估计*

为了提高单基地多输入多输出(Multiple-Input Multiple-Output, MIMO)声呐阵列的波达方向(Direction of arrival, DOA)估计性能,提出了双尺度旋转不变子空间(Dual-Resolution Estimation of Signal Parameters via Rotational Invariance Techniques, DR-ESPRIT)算法。结合MIMO阵列虚拟阵列的结构特征,首先利用ESPRIT算法通过各条虚拟线阵内、基线间距不大于半波长的子阵间的旋转不变关系得到无模糊的粗估计结果,之后利用虚拟线阵间、基线较长的子阵间的旋转不变关系得到一组有模糊的精估计结果。参考粗估计结果对精估计结果进行解模糊,最终得到高精度无模糊的角度估计结果。为了降低运算复杂度,利用该思路对降维ESPRIT算法也进行改进,提出了双尺度降维ESPRIT算法。仿真试验首先验证了与传统算法相比,双尺度类DOA估计算法能够有效提高角度估计精度。此外,还分析了MIMO声呐阵列的发射、接收阵元的幅相扰动误差对算法角度估计性能的影响。     

Application of local polynomial estimation in suppressing strong chaotic noise

In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.     

Optimal State Estimation of Pure Qubits on Circles

We consider the problem of state estimation of qubits chosen from circles. It is shown that any qubit encoded in pairs chosen from a fixed circle parailel to the x-y equator with different phases contains the same information. We also investigate the problem of state estimation of qubits from three circles. The optimai estimation fidelity is derived.     

Pekeris波导中垂直发射阵的阵增益快速估计

为了利用单换能器的声强级估计垂直发射阵的声强级,研究了Pekeris波导中快速估计发射阵增益的方法。首先,基于等效深度简正波理论,计算了Pekeris波导中垂直发射阵的平均声强,进而得到用模态阶数求和表示的发射阵增益的表达式。然后对模态阶数用积分代替求和,并对引入的误差进行修,得到3/2次方衰减场区发射阵增益的快速估计表达式;有效声影区声场由于只剩1阶简正模态,可直接简化得到发射阵增益的快速估计表达式,在海底参数未知时可用海深近似代替等效深度来估计有效声影区的发射阵增益。计算机仿真和海上实验得到的阵增益快速估计误差均小于1 dB,验证了快速估计方法的有效性,这一发射阵增益快速估计方法可以为工程应用提供参考。