小快拍高分辨目标方位估计算法 GMUSIC的性能分析*

针对水下运动阵列在运动过程中进行方位估计时存在快拍不足的问题,研究了基于随机矩阵理论的MUSIC改进算法GMUSIC,该方法通过Stieltjes变换建立起统计协方差矩阵真实特征值、特征向量与样本协方差矩阵之间在逼近域中的关联,以修正样本协方差特征分解的结果,进而实现小快拍方位估计。仿真与试验表明:GMUSIC算法可以更好地分辨相邻目标,且需要的快拍数较MUSIC算法要少;在低信噪比情况下,GMUSIC算法方位估计均方根误差远小于MUSIC算法,估计成功概率远大于MUSIC算法。因此,GMUSIC算法适用于解决水声目标的小快拍方位估计问题。     

基于渐进添边的准循环压缩感知时延估计算法

针对时延估计问题中压缩感知类算法现有测量矩阵需要大量数据存储量的问题,提出了一种基于渐进添边的准循环压缩感知时延估计算法,实现了稀疏测量矩阵条件下接收信号时延的准确估计.该算法首先建立压缩感知与最大似然译码之间的理论桥梁,然后推导基于低密度奇偶校验码的测量矩阵的设计准则,引入渐进添边的思想构造具有准循环结构的稀疏测量矩阵,最后利用正交匹配追踪算法正确估计出时延.对本文算法的计算复杂度与测量矩阵的数据存储量进行理论分析.仿真结果表明,所提算法在测量矩阵维数相同的条件下正确重构概率高于高斯随机矩阵和随机奇偶校验测量矩阵,相比于随机奇偶校验矩阵,在数据存储量相等的条件下,以较少的计算复杂度代价得到了重构概率的较大提高.     

一种基于模态域波束形成的水平阵被动目标深度估计

水面水下目标分辨与识别一直是被动声呐探测领域的难题.利用一种水平阵模态域波束形成算法获得己知方位目标声源的各阶模态强度,将其与不同深度的各阶参考模态强度进行匹配,最终实现了对声源的深度估计.仿真结果表明,该算法可以在信噪比为-10 dB的情况下,用300Hz带宽的信号样本,实现对声源深度的有效估计.系统分析了不同参数和不同波导条件对该方法目标深度估计性能的影响.其中,阵元数越多,模态样本数越多,计算频段越宽,方位估计精度越高,有效阵长越长,深度估计的性能越好.阵元间距和波导深度的变化不会影响该方法的深度估计性能,并且该方法的深度估计性能在声速剖面、海底参数等波导条件存在扰动时具有鲁棒性.     

An efficient spectral method and rigorous error analysis based on dimension reduction scheme for fourth order problems

In this paper, we propose an effective spectral method based on dimension reduction scheme for fourth order problems in polar geometric domains. First, the original problem is decomposed into a series of one‐dimensional fourth order problems by polar coordinate transformation and the orthogonal properties of Fourier basis function. Then the weak form and the corresponding discrete scheme of each one‐dimensional fourth order problem are derived by introducing polar conditions and appropriate weighted Sobolev spaces. In addition, we define the projection operators in the weighted Sobolev space and give its approximation properties, and further prove the error estimation of each one‐dimensional fourth order problem. Finally, we provide some numerical examples, and the numerical results show the effectiveness of our algorithm and the correctness of the theoretical results.     

基于视觉感知的光谱评估尺度

光谱颜色复现和色度精度是评价光谱重建算法准确的基础。简单而直观的评价指标对颜色复现控制是必不可少。该指标需要同时表征复现颜色的光谱差和色度差。在研究光谱匹配评估的方法基础上,提出基于颜色视觉感知的三种光谱评估指标,通过加权人眼视觉匹配函数,实现颜色光谱差与色度的评估。通过孟塞尔颜色系统的光谱数据,该论文分析与验证三种视觉加权的评估指标的有效性。通过孟塞尔颜色系统数据,这些指标在CIELab均匀色空间中分布均匀而稳定,从而证明加权算法的评估指标是既表征到颜色感知又反映出颜色的光谱相似度。实证结果表明,加权的指标可以实现同时表征实际人眼的颜色感知和颜色光谱差异。基于人眼视觉感知的评估指标解决了颜色的原始光谱和重建光谱的光谱匹配精度的定量评价问题。所提出评价指标通过一个简单而直观的数值实现对复现颜色光谱与色度评估。     

干涉型光纤水听器PGC解调的参数估计方法

对于干涉型光纤水听器外调制式相位生成载波(PGC)解调方案,光干涉强度和调制深度两个参数的波动会影响解调结果。为了消除影响,本文提出利用椭圆曲线拟合以及频域搜索的参数估计方法。根据理论分析,当调制深度在[0,3.83]区间内两种方法有效,可以适应实际情况中调制深度缓慢且小范围波动的情况。为了分析验证两种方法,本文利用不同类型的待测信号进行了数值仿真,根据仿真结果,在声信号引起的相位较大的情况下,两种方法都能对参数进行正确估计;利用频域搜索的方法适用的动态范围更大;当相关参数缓慢波动时,频域搜索法能正确跟踪估计相关参数。     

多速率STFT超宽带信号瞬时频率估计研究

提出多速率短时傅里叶变换(Multi Rate Short Time Fourier Transform,MR-STFT)瞬时频率估计算法,提高了超宽带信号瞬时频率估计精度。该方法将多速率信号处理算法与短时傅里叶变换(STFT)技术相结合,兼顾采样频率和被测频率,将宽频范围进行分段采样,对分段处理结果进行拟合,构成多速率STFT算法,实现超宽带信号瞬时频率的高精度测量。论文通过对仿真信号和实测信号进行处理,研究了方法的可行性和频率估计精度,结果表明MR-STFT算法较大提高了超宽带信号瞬时频率估计精度,尤其对低信噪比的超宽带信号效果显著。     

Risk estimation of infectious diseases determines the effectiveness of the control strategy

Usually, whether to take vaccination or not is a voluntary decision, which is determined by many factors, from societal factors (such as religious belief and human rights) to individual preferences (including psychology and altruism). Facing the outbreaks of infectious diseases, different people often have different estimations on the risk of infectious diseases. So, some persons are willing to vaccinate, but other persons are willing to take risks. In this paper, we establish two different risk assessment systems using the technique of dynamic programming, and then compare the effects of the two different systems on the prevention of diseases on complex networks. One is that the perceived probability of being infected for each individual is the same (uniform case). The other is that the perceived probability of being infected is positively correlated to individual degrees (preferential case). We show that these two risk assessment systems can yield completely different results, such as, the effectiveness of controlling diseases, the time evolution of the number of infections, and so on.     

Adjustable dimension descriptor observer based fault estimation for switched nonlinear systems with partially unknown nonlinear dynamics

This paper focuses on the fault estimation problem for switched systems with partially unknown nonlinear dynamics, actuator and sensor faults, simultaneously. The fault estimation observers are constructed, in which the observer dimension is not fixed and can be selected in a certain range. Both the disturbance decoupling and disturbance attenuation are considered, where the unknown nonlinear dynamics can be decoupled and the effect of modeling error and measurement disturbance is attenuated. Based on the average dwell time and the piecewise Lyapunov function, the observer parameter matrices can be calculated by solving LMIs and matrix equations. Finally, two examples are listed to verify the proposed fault estimation approach.     

Refractivity estimations from an angle-of-arrival spectrum

This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum.Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile.The estimation of the refractivity is organized as an optimization problem and a genetic algorithm is used to search for the optimal solution from various trial refractivity profiles.Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters.Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.