基于神经网络的联合智能滤波在导航系统中的应用

针对INS/ GPS/CNS组合导航系统的特点,运用神经网络理论代替传统卡尔曼滤波器,利用INS/ GPS、INS/CNS两个局部滤波器的输出值,通过综合滤波器进行线性最优估计,且进行了计算机仿真.仿真结果表明,该系统具有较高的导航精度,改善了系统的稳定性和容错性,而且与以往滤波器比较,系统的实时性、鲁棒性也有所改善.     

联邦滤波器在船舶组合导航系统中的应用

本文设计了一个基于融合-重置结构的联邦滤波器,应用于船舶组合导航系统.与传统的集中式滤波器相比,联邦滤波器结构简单,计算量少,容错性强.仿真结果表明,该联邦滤波器用在组合导航系统中是可行的,能够满足系统的精度要求.     

组合导航系统模拟器中的卡尔曼滤波设计

组合导航系统模拟器是飞行训练模拟系统的关键部件,在分别设计了惯性导航系统模拟器以及卫星导航模拟器的基础上,为了提高模拟器的真实性,针对如何实现两个系统最优组合,为其它系统提供准确可靠的导航数据的问题,参照现代飞机组合导航系统的组成结构及工作原理,设计了组合导航卡尔曼滤波器,建立了松组合和紧组合两种组合导航方式的方程和量测方程,并与纯惯性导航系统的结果进行对比分析,证明了所设计的组合导航系统卡尔曼滤波器的有效性.     

基于陀螺/星敏感器的微小卫星姿态确定方法研究

在热备份的余度配置陀螺与星敏感器的组合定姿中,典型的三轴正交陀螺与星敏感器姿态确定算法受到限制;现以某微小卫星姿控系统为对象,设计了热备份的四陀螺系统与星敏感器组合定姿方法;数据处理时,利用最小二乘法将四陀螺测量系统构建为一个虚拟三轴正交陀螺,再将虚拟陀螺与星敏感器组成卡尔曼滤波器;该方法和典型的三正交陀螺与星敏感器组合定姿结构相同,实现简单,且在一陀螺发生故障时,能在不改变滤波器结构的情况下实现对故障陀螺的屏蔽;仿真验证了该方法的有效性。     

基于强跟踪滤波器的MIMU/GPS组合导航系统

研究微型惯导系统优化导航,在实际工程应用中设计强跟踪滤波器的MIMU/GPS组合导航系统,为验证整个组合导航系统的正确性和可靠性,采用软件无线电平台,进行了系统硬件架构和算法设计,使得整个系统具有较强的灵活性和可扩展能力.系统组合方式采用伪距、伪距率紧密组合.滤波器部分引入对突变状态具有较强鲁棒性和跟踪能力的强跟踪滤波器,对系统进行了最优估计和反馈校正.进行车载仿真试验,结果表明,整个系统组合效果显著,跟踪精度满足了设计要求.     

GPS/INS组合导航系统设计及实现方案

将两种或多种导航系统(或传感器)组合起来成为一个综合系统,其导航性能比单一的系统好,因此组合导航系统目前已成为导航系统的发展方向之一。现代控制理论的成就,特别是最优估计理论的数据处理方法,为组合导航系统提供了理论基础。介绍了GPS/INS组合导航系统的经典组合方式和采用卡尔曼组合滤波器的组合方式。重点对采用卡尔曼滤波的软件组合方式进行分析和推导,将全组合滤波法和分布式组合滤波法进行了较全面的比较。     

多导航传感器的数据融合处理方法研究

在舰船导航过程中为克服单一模型的卡尔曼滤波器对真实系统状态参数发生变化时造成滤波误差过大甚至发散的现象,将多模自适应控制用于导航数据融合处理方法中,设计了组合导航系统的多模型自适应卡尔曼滤波器,通过数字仿真将单一模型的INS/GPS/Doppler组合导航系统与多模自适应控制的组合导航系统的性能进行了比较,表明了多模自适应控制在组合导航系统中可以改善系统的瞬态响应和覆盖大范围的参数不确定性,提高了组合系统的导航精度.     

自适应联邦卡尔曼滤波在机器人组合导航系统中的应用研究

利用里程计(OD)与全球定位系统(GPS)辅助捷联惯性导航系统(SINS)构成一种高可靠性的组合导航系统.推导并建立了局部滤波器的数学模型,并针对联邦滤波器在载体发生异常扰动时滤波精度较低的问题,设计了基于SINS/GPS/OD组合导航系统的自适应联邦滤波器,有效补偿了系统异常扰动或动力学模型误差.仿真模拟了机器人的全航线运行轨迹进行验证,仿真结果表明,SINS/GPS/OD组合导航系统的自适应联邦卡尔曼滤波算法与相同组合导航系统的非自适应联邦卡尔曼滤波算法相比,在保障机器人导航定位可靠性及容错能力的前提下,能有效抑制异常扰动的影响,导航精度得到进一步改善.     

车载GPS／DR／地图匹配组合导航系统的自适应联合卡尔曼滤波模型

首次设计了实现车载ＧＰＳ／ＤＲ／地图匹配组合导航系统最优综合的联合卡尔曼滤波器,给出了滤波算法,并提出一种自适应联合卡尔曼滤波器结构及其算法。理论分析及计算机仿真结果均表明,应用该自适应联合卡尔曼滤波器可大大提高车载ＧＰＳ／ＤＲ／地图匹配组合导航系统的定位精度及容错能力。     

模糊自适应Kalman滤波器在无人机导航中的应用

针对具有不确定动态模型参数的GPS／INS组合导航系统，基于传统Kalman滤波器之上，介绍了一种模糊自适应Kalman滤波器，讨论了GPS／INS组合系统中模型参数不确定性的问题，给出了一种利用模糊自适应滤波方法进行数据融合的无人机定位误差修正方法；仿真结果表明，模糊自适应卡尔曼滤波器对非线性GPS／INS组合系统是很有效的，提高了定位精度。     

Current state and future directions of multirate filter banks and their applications

This paper provides an overview of the basic concepts, current state and future directions of uniform and nonuniform multirate filter banks and their applications. Research in the areas of multidimensional filter banks, and wavelet transforms, as a direct extension to the topic is still proceeding at a rapid rate. Different design techniques and algorithms that are currently of interest are investigated from hardware complexity and reconstructed signals' quality points of view. Important similarities and differences between different filters categories are noted, which lead to a discussion of important issues that need to be resolved. Distortions and quantization effects present in the filter banks are reviewed and some solutions for controlling different types of distortions are introduced. The problem of designing QMF banks that can provide good frequency resolution while allowing for exact or near perfect reconstruction of the signal is quite challenging, because so many dissimilar types of distortion must be minimized and/or eliminated in the same design context. Recently, the perfect reconstruction cosine-modulated filter bank and filter banks with block sampling have emerged as an attractive choice of filter bank with respect to implementation complexities and design cost. New trends and future directions including selective multirate filter banks, filter banks with nonuniform decimation ratio, filter banks with discrete coefficients, multidimensional filter banks, nonlinear filter banks and data dependent decompositions are presented. Finally, some selected applications of multirate filter banks are described; namely transmultiplexers, speech and image coding, analog voice privacy systems and wavelets based signal and image compression.     

Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

In this paper, we design time–frequency localized three-band biorthogonal linear phase wavelet filter bank for epileptic seizure electroencephalograph (EEG) signal classification. Time–frequency localized analysis and synthesis low-pass filters (LPF) are designed using convex semidefinite programming (SDP) by transforming a nonconvex problem into a convex SDP using semidefinite relaxation technique. Three-band parameterized lattice biorthogonal linear phase perfect reconstruction filter bank (BOLPPRFB) is chosen and nonlinear least squares algorithm is used to determine its parameters values that generate the designed analysis and synthesis LPF such that the band-pass and high-pass filters are also well localized in time and frequency domain. The designed analysis and synthesis three-band wavelet filter banks are compared with the standard two-band filter banks like Daubechies maximally regular filter banks, Cohen–Daubechies–Feauveau (CDF) biorthogonal filter banks and orthogonal time–frequency localized filter banks. Kruskal–Wallis statistical test is employed to measure the statistical significance of the subband features obtained from the various two and three-band filter banks for epileptic seizure EEG signal classification. The results show that the designed three-band analysis and synthesis filter banks both outperform two-band filter banks in the classification of seizure and seizure-free EEG signals. The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.     

A new approach to design triplet halfband filter banks based on balanced-uncertainty optimization

This paper presents a novel approach to design a class of triplet halfband filter banks (THFB) based on optimized time–frequency localization. First, an Euler–Frobenius polynomial (EFP) is introduced to design a class of halfband polynomial. The vanishing moments and perfect reconstruction conditions are imposed on EFP to obtain maximally flat halfband filter. The resultant halfband filter is optimized using a balanced-uncertainty (BU) metric in order to have balance between time and frequency spread. Next, this optimized halfband filter is used in three-step lifting scheme to obtain analysis and synthesis wavelet filters which have balance between time and frequency localization. The proposed method provides three degrees of freedom that results in flexible design of filter bank. It is observed that the proposed filter bank gives more regularity and better frequency selectivity as compared to existing filter banks. These designed filters are then used for human chromosome image compression application. The performance of the designed filter bank is compared in terms of PSNR using different bit-rates with well-known existing filter banks in order to validate the experimental results.     

滤波器组框架理论及其在图信号处理中的应用

滤波器组框架理论是应用数学、信号处理、图像处理和数字通信等领域的重要问题之一,对滤波器组框架的分析和设计问题进行研究有着重要的科学意义和应用前景.近年来,随着高维非规则化数据信息大量涌现,很多学者开始研究图信号处理的滤波器组方法.因此对滤波器组框架理论及其在图信号处理中的应用进行了综述研究.首先对传统滤波器组框架理论的基础知识进行概述,总结滤波器组框架分析与设计方法;然后重点介绍两类图信号处理架构以及图滤波器组的最新研究成果;最后对未来的研究进行展望.     

Metaheuristic algorithms for the design of multiplier-less non-uniform filter banks based on frequency response masking

In this paper, multiplier-less nearly perfect reconstruction tree structured non-uniform filter banks (NUFB) are proposed. When sharp transition width filter banks are to be implemented, the order of the filters and hence the complexity will become very high. The filter banks employ an iterative algorithm which adjusts the cut off frequencies of the prototype filter, to reduce the amplitude distortion. It is found that the proposed design method, in which the prototype filter is designed by the frequency response masking method, gives better results when compared to the earlier reported results, in terms of the number of multipliers when sharp transition width filter banks are needed. To reduce the complexity and power consumption for hardware realization, a design method which makes the NUFB totally multiplier-less is also proposed in this paper. The NUFB is made multiplier-less by converting the continuous filter bank coefficients to finite precision coefficients in the signed power of two space. The filter bank with finite precision coefficients may lead to performance degradation. This calls for the use of suitable optimization techniques. The classical gradient based optimization techniques cannot be deployed here, because the search space consists of only integers. In this context, meta-heuristic algorithm is a good choice as it can be tailor made to suit the problem under consideration. Thus, this design method results in near perfect NUFBs which are simple and multiplier-less and have linear phase and sharp transition width with very low aliasing. Also, different non-uniform bands can be obtained from the tree structured filter bank by rearranging the branches.     

Optimum filter design for quantized multidimensional subband filter bank

This paper provides a rigorous theory for analysis of quantization effects and optimum filter bank design in quantized multidimensional subband filter banks. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. Using polyphase decomposition of the analysis/synthesis filter banks, we derive the exact expression for the output mean square quantization error. Based on the minimization of the output mean square error, the technique for optimal filter design methodology is developed. Numerical design examples for optimum nonseparable paraunitary and biorthogonal filter banks are presented with a quincunx subsampling lattice.     

低复杂度HBCEM FRM多相滤波器组

针对滤波器组的子信道过渡带过窄带来的高计算复杂度问题,首先分析了半带复指数调制FRM滤波器(HBCEM FRM,Half band complex exponential modulation frequency-response masking filter)实现高效性的根本因为,然后采用这种滤波器作原型滤波器并结合...     

Design of two-channel quadrature mirror filter bank using particle swarm optimization

In this paper, a particle swarm optimization (PSO) is used to design the quadrature mirror filter (QMF) banks with linear phase in frequency domain. A unique PSO is developed to optimize filter bank coefficients to match the ideal system response. The three main attributes used in assessing the performance of filter are reconstruction error, mean square error in pass band and mean square error in stop band. The proposed PSO based method produces almost the same result as that of the existing methods. As compared to the existing methods this method is very simple to implement for the QMF bank optimization. To implement the proposed PSO algorithm, a Matlab program is developed and three examples have been presented to illustrate the performance of the proposed method.     

图象压缩双正交小波滤波器的优化设计

为了提高图象压缩效果 ,提出了一种比较新颖的基于图象压缩系统的构造最优双正交小波滤波器的设计方法 ,即在图象编码中 ,从选择小波基的原则出发 ,并以最常用的 Antonini's 9/ 7小波基为参考 ,选择 SPIHT为压缩方法 ,以压缩效果为准则来构造最优的双正交小波基 ,并且采用 L ena为标准训练图象 ;然后以压缩比为参数 ,通过得到最大的峰值信噪比来寻找最优的双正交小波基 ,从而将复杂的多输入 ,两输出问题简化为多输入单输出的最优化问题 ;最后用遗传算法解决这种最优化的问题 ,得到了最优的双正交小波基 .训练和检验的结果表明 ,这种最优的双正交小波基比 Antoninis 9/ 7小波基压缩效果有所提高 .     

Design of nearly perfect reconstructed non-uniform filter bank by constrained equiripple FIR technique

In this paper, an efficient iterative algorithm is proposed for the design of multi-channel nearly perfect reconstructed non-uniform filter bank. The method employs the constrained equiripple FIR technique to design the prototype filter for filter banks with novelty of exploiting a new perfect reconstruction condition of the non-uniform filter banks instead of using complex objective functions. In the proposed algorithm, passband edge frequency (ω_p) is optimized using linear optimization technique such that the filter coefficients values at quadrature frequency are approximately equal to 0.707. Several design examples are included to illustrate the efficacy of this methodology for designing non-uniform filter bank (NUFB). It was found that the proposed methodology performs better as compared to earlier reported results in terms of reconstruction error (RE), number of iteration (NOI) and computation time (CPU time). The proposed algorithm is very simple, linear in nature, and easy to implement.