基于概率假设密度滤波平滑器的检测前跟踪算法

基于概率假设密度滤波(PHD)的检测前跟踪(TBD)技术可以有效解决未知弱小多目标检测问题。PHD-TBD算法粒子权重计算受量测噪声影响明显,导致目标数估计存在起伏现象,制约了PHD-TBD算法性能。对PHD-TBD技术进行研究,引进概率假设密度滤波平滑器,提出基于平滑的PHD-TBD算法。该算法对当前帧目标数估计时,综合利用前向递推和后向平滑结果对粒子权重进行更新,在一定程度上克服了随机量测噪声的影响。通过仿真验证,该算法能够有效发现目标,准确估计目标数目和位置,性能有较大提高。     

区间衍生粒子滤波器

针对非线性、非高斯环境下具有不确定动态模型参数的系统状态估计问题,提出了一种新颖的区间衍生粒子滤波算法.该算法利用区间滤波生成的重要性密度函数,在系统状态转移概率密度的基础上,融入最新的系统观测数据,从而提高了对系统状态后验概率的逼近程度.为了进一步提高算法的实时性,提出一种类似光子衍射的粒子衍生过程,进而缓解了滤波精度与运算量之间的矛盾.通过陀螺/星敏感器组合定姿问题验证了该算法的有效性和鲁棒性.     

基于自适应EKF的弱GNSS信号跟踪算法

弱GNSS信号跟踪技术是卫星导航接收机关键技术之一,跟踪技术的好坏将直接影响卫星导航接收机在弱信号条件下的跟踪性能;在动态环境和先验信息不充分的情况下,由于扩展卡尔曼滤波(EKF)的固定设计使其不能满足要求,针对此不足引入一种自适应扩展卡尔曼滤波(AEKF)的信号跟踪算法;该自适应滤波算法能够实时监测残差或滤波器新息的动态变化,来修正观测噪声方差和状态噪声方差,以此调整滤波器增益,观测值和控制预测值在滤波结果中的权重;理论分析和结果表明,该算法能够充分利用观测信号的统计特性,克服了传统EKF算法不足,获得更好的跟踪性能。     

混合退火粒子滤波器

针对非线性、非高斯系统状态的在线估计问题，提出一种新的基于序贯重要性抽样的粒子滤波算法. 在滤波算法中，用状态参数分解和退火系数来产生重要性概率密度函数，此概率密度函数综合考虑了转移先验、似然、噪声的统计特性以及最新的观察数据，因此更接近于系统状态的后验概率. 理论分析与仿真实验表明该粒子滤波器的性能明显优于标准的粒子滤波器和扩展卡尔曼滤波器. 关键词： 非线性 非高斯 粒子滤波 序贯重要性抽样     

一种增强结构信息的图像平滑算法

基于非线性扩散滤波提出了可以同时对同质区域进行平滑和对结构信息进行增强的算法．该算法在同质区域采用各项同性滤波而在边缘附近采用各项异性扩散滤波，避免了图像平滑和增强结构信息之间的矛盾．在实现时，根据一致性程度选择扩散矩阵的扩散系数，可确保偏微分方程在离散化时的简洁性和一致性．数字实验结果表明，可以有效的平滑一致性低的区域并增强一致性高的结构．     

基于高斯混合概率假设滤波的水下目标跟踪算法

为了解决传统水下目标跟踪中目标数目估计不准确、状态估计误差增长过快的问题,提出了一种基于高斯混合概率假设滤波的水下目标跟踪算法。该算法基于双基地观测模型,采用高斯混合概率假设滤波算法处理方位和时延信息,利用粒子群算法处理多普勒频率获得矢量速度,进一步提升算法的跟踪精度。结果表明,该算法能完成在杂波环境下对目标的跟踪,相比传统的关联算法,能够有效地实现目标个数估计和抑制状态误差增长的目的。     

基于概率假设密度的无线传感器网络多目标跟踪算法

针对无线传感器网络多目标跟踪过程中杂波难以去除以及由数据关联复杂带来的计算复杂度高的问题,将概率假设密度滤波器应用于无线传感器网络,以更好地对多目标状态信息进行融合估计;首先,建立簇-树型无线传感器网络模型,并运用随机有限集理论对目标状态模型和传感器观测模型进行描述;然后,根据目标与节点之间的距离设置观测阈值,当传感器节点测量值小于观测阈值时,概率假设密度滤波器将实时对该组测量数据进行处理,从而实现传感器网络对目标状态的联合检测与跟踪;仿真结果表明,在无线传感器网络的多目标跟踪应用中,该算法比粒子滤波算法具有更高的跟踪效率和精度。     

大失准角传递对准算法研究

经典Kalman滤波器不适用于大失准角情况下的传递对准,故只能采用非线性滤波器进行失准角的次优估计,其工程实现效果无法满足惯性姿态系统对姿态精度的要求。针对上述问题,提出了动态解析对准与传递对准相结合的大失准角传递对准算法,设计了"速度+角速度"匹配的传递对准滤波模型。该算法利用动态解析对准算法完成大失准角的初步补偿,解决传递对准非线性误差模型无法进行线性化的问题。基于Kalman滤波最优估计理论,设计FIR低通滤波器完成观测信息去噪滤波,实现姿态失准角的最优估计补偿,以达到惯性姿态系统大失准角条件下快速精确传递对准的目的。试验结果表明,在大失准角条件下,惯性姿态系统可在50s内完成方位精度为3′、水平姿态精度为1′的初始对准。     

眼底图像中视盘的平滑滤波与CV模型分割

可靠、有效的视盘分割对自动眼底病变诊断分析具有重要意义。提出了一种基于平滑滤波和CV模型的视盘分割算法。在利用投影法定位出视盘中心后,首先采用Gabor滤波技术提取并移除视盘局部区域的主血管,然后利用邻域信息通过插值运算填充被移除血管区域的像素,采用边缘保留平滑滤波对视盘区域进行平滑,最后利用基于区域信息的CV水平集模型分割出视盘的边界。该方法在MESSIDOR数据库上进行了测试,平均分割准确率为0.83,表现出了良好的分割性能。     

一种基于粒子滤波的雷达抗欺骗干扰方法

针对雷达的抗欺骗干扰问题,利用欺骗干扰信号强于目标信号的特点,基于粒子滤波进行了抗欺骗干扰研究。当存在欺骗干扰时,粒子滤波中各粒子的重要性权值会明显减小,据此可以检测干扰,并对受到干扰的数据点进行置零处理,使得欺骗干扰不再与匹配滤波器匹配,从而达到抑制干扰的目的。设计的粒子滤波算法不需要估计系统状态转移函数、系统量测噪声,从而使得算法更具实用性。仿真结果表明,该算法能有效地抑制欺骗干扰,且对干信比不敏感。     

Information and Entropy Flow in the Kalman–Bucy Filter

We investigate the information theoretic properties of Kalman–Bucy filters in continuous time, developing notions of information supply, storage and dissipation. Introducing a concept of energy, we develop a physical analogy in which the unobserved signal describes a statistical mechanical system interacting with a heat bath. The abstract universe comprising the signal and the heat bath obeys a non-increase law of entropy; however, with the introduction of partial observations, this law can be violated. The Kalman–Bucy filter behaves like a Maxwellian demon in this analogy, returning signal energy to the heat bath without causing entropy increase. This is made possible by the steady supply of new information. In a second analogy the signal and filter interact, setting up a stationary non-equilibrium state, in which energy flows between the heat bath, the signal and the filter without causing any overall entropy increase. We introduce a rate of interactive entropy flow that isolates the statistical mechanics of this flow from marginal effects. Both analogies provide quantitative examples of Landauers Principle.     

鲸群优化的粒子滤波算法研究

针对标准的粒子滤波存在粒子贫化问题,提出了一种鲸群优化的粒子滤波算法。用粒子表征鲸鱼个体, 模拟鲸鱼群体搜寻猎物的过程,引导粒子向高似然区域移动。将粒子滤波中粒子的状态值作为鲸鱼群的个体位置,将粒子的状态估计转化为对鲸鱼群的寻优;通过鲸群的螺旋运动方式优化粒子的重要性采样过程,使粒子分布更加合理,对鲸群算法中的全局最优值引入最优邻域随机扰动策略,并在鲸鱼位置更新过程中加入自适应权重因子;选用一种典型的单静态非增长模型进行仿真测试。测试结果表明:提出的方法与传统的粒子滤波以及引力场优化的粒子滤波相比,在保证相同粒子数的前提下,算法的均方误差分别降低了28%和9%,证明了鲸群优化的粒子滤波算法具有更高的估计精度,并且在粒子数较少的情况下,可实现更准确的状态估计。     

Full Causal Theory of Bulk Viscosity and Specific Entropy of the Universe

This article deals with the full Israel–Stewart causal theory of bulk viscosity as employed to the dissipative expansion of the early universe. It is shown that the nontruncated full theory can be cast in the form of a noncausal theory with an auxiliary condition which states that the square of dissipative contribution to the speed of sound varies with the particle number in a comoving volume. Also, a generalized temperature appears in a cosmological invariant which is shown to hold good for the dissipative expansion in an intermediate brief transition period (around the epoch time = 10^–23 s) between the very early mild inflation stage of the universe and the standard radiation-dominated FRW era of it. With this generalized temperature, the Gibbs equation has been generalized. This equation is also shown to have an alternative form with a term depending on bulk viscosity. In the dissipative transition period, the universe as a thermodynamically open system of viscous fluid can generate specific entropy. In this period the temperature rose to a considerable extent. Due to the cosmological invariant, the dissipative contribution to the speed of sound and consequently the particle number decreased sharply, ensuring the second law of thermodynamics. It is possible to have an estimate of the specific entropy in consistency with the observations. The total entropy and the particle number of the observable universe have also been found here. These estimates agree with the accepted values for them.     

Entropies of the various components of the universe

In this study, we investigate the entropies of photons, ideal gas-like dust (baryonic matter), and a special kind of dark energy in the context of cosmology. When these components expand freely with the universe, we calculate the entropy and specific entropy of each component from the perspective of statistics. Under specific assumptions and conditions, the entropies of these components can satisfy the second law of thermodynamics independently. Our calculations show that the specific entropy of matter cannot be a constant during the expansion of the universe, except for photons. When these components interact with the space-time background, particle production (annihilation) can occur. We study the influence of the interaction on the entropies of these components and obtain the conditions guaranteeing that the entropy of each component satisfies the second law of thermodynamics.     

Study of fully developed wind wave spectrum by application of quantum statistics

The spectrum of fully developed wind waves is studied by application of the method of quantum statistics. A particle picture of water waves is introduced as an analogy of wave–particle duality. “Water wave particles” are conceived which are similar to phonons for elastic waves in solids. However, due to the property of wave breaking, the number of “water wave particles” in a quantum state is restricted. The spectrum of fully developed wind waves is studied on the basis of the maximum entropy principle. The similarity law of fully developed wind wave spectrum is proved. In the high frequency range, the spectral form is in agreement with the result of observations. In the particle picture, a saturated spectrum is introduced which is in conceptual consistency with the saturated spectrum introduced by Phillips in the wave picture, and the form of which is the same as Phillips’. It is further shown that in the high frequency range the spectrum is only half saturated for fully developed wind waves. The frequency downshifting phenomenon which cannot be explained by wave theory is explained in the particle picture.     

Dim moving target tracking algorithm based on particle discriminative sparse representation

The small dim moving target usually submerged in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio (SNR). A target tracking algorithm based on particle filter and discriminative sparse representation is proposed in this paper to cope with the uncertainty of dim moving target tracking. The weight of every particle is the crucial factor to ensuring the accuracy of dim target tracking for particle filter (PF) that can achieve excellent performance even under the situation of non-linear and non-Gaussian motion. In discriminative over-complete dictionary constructed according to image sequence, the target dictionary describes target signal and the background dictionary embeds background clutter. The difference between target particle and background particle is enhanced to a great extent, and the weight of every particle is then measured by means of the residual after reconstruction using the prescribed number of target atoms and their corresponding coefficients. The movement state of dim moving target is then estimated and finally tracked by these weighted particles. Meanwhile, the subspace of over-complete dictionary is updated online by the stochastic estimation algorithm. Some experiments are induced and the experimental results show the proposed algorithm could improve the performance of moving target tracking by enhancing the consistency between the posteriori probability distribution and the moving target state.     

完全变光滑长度SPH法及其实现

提出完全变光滑长度SPH法及其算法实现.方程组基于对称形式核函数近似,SPH密度演化方程与变光滑长度方程隐式关联;在Springel提出的全守恒SPH方程组基础上,通过将分散核近似形式改进为对称核近似形式得到SPH动量方程和能量方程.采用迭代求解密度演化方程和变光滑长度方程,显式求解SPH动量方程和能量方程,增加的计算量相对很少.给出三个1D激波管算例和2D Sedov算例验证方法的有效性.数值结果表明,算法保持动量和能量的守恒律,解决了传统SPH法中由于变光滑长度影响带来的计算误差,且在模拟2DSedov问题时能得到比Springel方法更准确的压强峰值位置和中心压强值.特别适合于模拟爆炸与冲击、大变形大扭曲等密度梯度和光滑长度梯度剧烈变化的问题.     

Thermodynamic anomalies in the presence of general linear dissipation: from the free particle to the harmonic oscillator

A free particle coupled to a heat bath can exhibit a number of thermodynamic anomalies like a negative specific heat, reentrant classicality or a nonmonotonic entropy. These low-temperature phenomena are expected to be modified at very low temperatures where finite-size effects associated with the discreteness of the energy spectrum become relevant. In this paper, we explore in which form the thermodynamic anomalies visible in the specific heat and the entropy of the free damped particle appear for a damped harmonic oscillator. Since the discreteness of the oscillator’s energy spectrum is fully accounted for, the results are valid for arbitrary temperatures. As expected, they are in agreement with the third law of thermodynamics and indicate how the thermodynamic anomalies of the free damped particle can be reconciled with the third law. Particular attention is paid to the transition from the harmonic oscillator to the free particle when the limit of the oscillator frequency to zero is taken.     

基于时频差的正交容积卡尔曼滤波跟踪算法

针对基于时频差测量的无源跟踪中面临的非线性估计问题, 提出一种正交容积卡尔曼滤波跟踪算法. 该算法在容积卡尔曼滤波算法的基础上, 通过引入特定正交矩阵改进容积采样方法, 在高维状态估计下减小因采样产生的误差, 在没有增加计算量的前提下, 有效提高收敛速度及跟踪精度. 仿真结果表明, 在基于到达时差和到达频差的联合无源跟踪问题中, 与扩展卡尔曼滤波及容积卡尔曼滤波算法相比, 本文所提算法在跟踪性能上有明显提升.