Adaptive Regularized Particle Filter for Synchronization of Chaotic Colpitts Circuits in an AWGN Channel

For chaotic trajectories, when the system parameters are fixed, they are generally confined in a bounded state space. In this paper, we propose an adaptive regularized particle filter (RPF), which makes the best of this inherent characteristic, for identical synchronization of chaotic Colpitts circuits combating additive white Gaussian noise (AWGN) channel distortion. This proposed filter incorporates RPF that resamples from a continuous approximation of the posterior density to avoid sample impoverishment and then utilizes the revised Kullback–Leibler distance (KLD) sampling to adaptively select the number of particles used. Compared with the existing particle filters (PFs) with fixed large number of particles, this proposed adaptive RPF propagates less number of particles with similar performance and thus provides a much more efficient solution for this problem.     

Improved auxiliary particle filter‐based synchronization of chaotic Colpitts circuit and its application to secure communication

In this paper, we propose a synchronization scheme based on an improved auxiliary particle filter (IAPF) for chaotic Colpitts circuit and conduct an experimental study on the synchronization performance with application to secure communications. Specifically, with the synchronization scheme, when the chaotic signals generated by an analog Colpitts circuit are transmitted through a nonideal channel, the distorted signals are processed digitally by the novelly designed IAPF at the receiver, in order to obtain the synchronized signals of the transmitter circuit. Experimental results indicate that synchronization can be achieved over both the additive white Gaussian noise channel and the multipath fading channel with low signal‐to‐noise ratio, even if there exist severe circuit parameter mismatches between the transmitter and the receiver. Furthermore, a chaos‐masking secure communication system is constructed and verified over both the additive white Gaussian noise channel and the multipath fading channel, and the bit error rate is evaluated versus different signal‐to‐noise ratios and symbol periods. It is shown that the achievable bit error rate can reach the order of magnitude of 10 ^{− 4} without error correction coding techniques. In addition, security analysis demonstrates that the proposed chaotic secure communication system is resistant to the brute‐force attack. Copyright © 2013 John Wiley & Sons, Ltd.     

Cooperative localization and tracking in wireless sensor networks

Cooperative localization has attracted great attention in recent years. However, in some scenarios, localization precision is challenging and does not meet the application requirements. In this paper, Kalman and Particle filters (KF and PF) are considered for cooperative localization scenarios purpose. We propose to apply these techniques to cooperative localization approaches that we investigated in previous papers: Evolved Variational Message Passing algorithm (E‐VMP) and Cooperative Robust Geometric Positioning Algorithm (C‐RGPA). The main added value of distributed tracking filters is to guarantee dynamic versions of these two algorithms. The proposed techniques are evaluated and compared by means of real heterogeneous measurements carried out using ZigBee and OFDM devices and where location‐dependent parameters such as RSSI and RTD are exploited. Experiments and realistic simulations reveal that the proposed techniques exhibit better localization accuracy for very low complexity and cost. Moreover, the comparative study shows that distributed particle filter (DPF) provides better performance than KF in terms of positioning accuracy and root‐mean square error.     

基于频率采样技术的FIR数字滤波器优化设计

本文提出了一种FIR数字滤波器满意优化设计方法，将滤波器过渡带样本值作为优化变量，通过设计通带、过渡带和阻带性能指标满意度函数和综合满意度函数，构造出满意优化模型，并用本文提出的新量子遗传算法搜索满意解，FIR高通和带阻数字滤波器的设计结果表明，采用满意优化方法设计的FIR滤波器的性能优于传统方法。     

基于颜色的粒子滤波算法的改进与全硬件实现

传统基于颜色的粒子滤波算法在硬件实现中存在着跟踪效果不理想、实时性差等问题.该文结合硬件电路需要对基于颜色的粒子滤波算法进行了改进,在传统SR重采样算法的基础上将剩余粒子撒向目标点附近,以提高其在硬件环境下跟踪的准确性与稳定性.文中给出了改进算法的全硬件实现的电路架构,并在FPGA上完成了目标跟踪系统的实现.实验表明提...     

Design Methodology for Domain Specific Parameterizable Particle Filter Realizations

This paper presents a reconfigurable particle filter design methodology for a real-time bearings-only tracking application. The methodology provides the capability of selecting a single particle filter from multiple particle filter realizations with maximum resource sharing. The autonomous buffer controller mechanism for the architecture ensures correct operation of the particle filters. Parameter adaptation and algorithm reconfiguration can be accomplished with negligible reconfiguration overhead through buffer controllers and a set of switches for transforming dataflow structures such that any desired particle filter can be implemented. Two target particle filters, sample importance resample filter (SIRF) and Gaussian particle filter (GPF), are realized using field programmable gate array (FPGA) based on the proposed methodology. However, the architecture can be extended for a wide range of particle filters with different sets of dynamics. This paper successfully demonstrates that implementation of a domain specific processor for particle filters is feasible with performance that is much higher than that of commercially available digital signal processors (DSPs).     

基于APF的二元WSN运动目标跟踪算法

针对传感节点计算、通信及资源受限的特点,引入二元WSN模型,提出了一种基于辅助粒子滤波(APF)的集中式算法,以实现运动目标的实时跟踪。由于每个二元传感器只对目标是否进入其感知区域做出反应(向数据融合中心报告0或1),粒子滤波算法的复杂运算集中在融合中心完成,因此节点结构简单、通信代价低廉,有助于延长监测网络的生存周期。仿真实验结果表明,该算法对随机部署和规则部署的两种方案,均具有良好的跟踪性能,能满足一般机动目标实时跟踪的应用要求。     

CCII based more tunable voltage-mode all-pass filters and their quadrature oscillator applications

In this paper, two new voltage-mode (VM) first-order all-pass filters using single active element namely second-generation current conveyor (CCII) and a grounding capacitor are proposed. The first proposed filter employs a dual output CCII (DO-CCII) and the other one uses a modified minus type CCII (MCCII−). One of the main advantages of both configurations is their high input impedances; thus, both can be easily cascaded with other VM circuits. Additionally, the use of a grounded capacitor in both circuits provides suitability for integrated circuit (IC) fabrication process. However, both of the proposed circuits need a single passive component matching constraint. Non-ideality analysis is performed for the proposed circuits. Moreover, two quadrature oscillator applications of the proposed filters are given. The behavior of the filters is verified by SPICE simulations. Also, experimental tests using commercially available ICs (AD844s) are achieved for the second proposed configuration.     

雷达/红外复合导引头信息融合算法

毫米波雷达/ 红外成像复合制导已成为当前多模复合制导技术的研究热点。从毫米波雷达/ 红外成像复合导引头系统的特点及其工程应用出发,建立了一种基于联邦滤波(FF)的分布式雷达/ 红外复合导引头信息融合算法。首先,针对扩展卡尔曼滤波存在线性化误差以及雷达测量噪声非高斯的特点,采用粒子滤波算法(PF)设计雷达子滤波器;针对红外传感器不能测量目标距离的特点,采用伪线性卡尔曼滤波算法(PLKF)设计红外子滤波器。然后通过主滤波器进行信息融合,并对两个子滤波器进行信息分配和重置。仿真结果表明,该信息融合算法能够有效地提高雷达/红外复合导引头系统的目标跟踪精度及系统的稳定性。     

非均匀稀疏采样环境的改进高斯粒子滤波方法

粒子滤波（PF）技术的研究一直是非线性滤波领域的热点和难点问题,针对非均匀稀疏采样环境下传感器观测的滤波估计问题,提出了一种结合目标运动特性的改进型高斯粒子滤波方法。在该方法中,首先深入分析了传统粒子滤波不能有效对非均匀稀疏采样观测数据进行有效处理的原因,通过引入目标观测、目标观测的有效时间间隔、目标速度等目标特性,综合改善高斯粒子滤波器在时间更新阶段预测粒子和预测协方差估计的准确性,从而提高观测更新阶段重要性密度函数的估计精度,实现对目标状态的精确估计。实验结果表明,对于一维非线性非高斯例子,提出方法要稍好于传统的PF、辅助粒子滤波（APF）和高斯粒子滤波（GPF）;而对于实际的非均匀稀疏采样观测样本,提出方法要远好于PF、APF和GPF,能够有效对目标进行状态估计。      

一种用于DS-CDMA基站的全数字非相干延迟锁相环

本文根据直接序列扩频码分多址(DS-CDMA)系统上行链路伪随机码跟踪的特点,给出并分析一种全数字非相干延迟锁相环 (DLL),该DLL采用了二元鉴相和数字序贯滤波的实现结构。文中推导了多用户环境下环路的数学模型及鉴相误差统计特性,给出了跟踪性能的计算机仿真结果。研究结果表明,本文给出的DLL能以小的复杂度实现良好的跟踪性能,具有较高的应用价值。     

EKF、PF在目标跟踪中的研究

介绍两种目标跟踪算法—扩展卡尔曼滤波器（Extended Kalman Filter,EKF）、粒子滤波器（Particle filter,PF）。EKF利用泰勒级数方法,将非线性问题转化到线性空间,再利用卡尔曼滤波器进行滤波,并达到一阶估计精度。PF是一种采用蒙特卡罗采样的贝叶斯滤波方法,它将复杂的目标状态分布表示为一组加权值,通过寻找在粒子滤波分布中最大权值的粒子来确定目标最可能所处的状态分布,已成为复杂环境下进行目标跟踪的最好的方法。文中通过仿真实验,对二者的性能进行了仿真比较,结果证明在复杂的非高斯非线性环境中,PF的性能明显优于EKF,但计算复杂,耗时长。     

基于遗传算法的FIR可变分数延迟滤波器设计

分数延迟滤波器广泛用于语音处理,回声消除,多速率信号处理等方面.文中设计的FIR可变分数延迟滤波器用于解决全数字接收机的时钟同步问题.首先用传统的加权最小平方误差方法设计出滤波器参数,然后通过遗传算法对参数进行优化并通过matlab仿真验证算法的有效性,仿真结果表明所设计的滤波器有很好的幅度特性和相位延迟特性.     

改进高阶容积粒子滤波的系统状态估计算法

传统粒子滤波（PF）直接采用状态转移先验分布作为重要性密度函数来近似后验概率密度函数,使得后验概率密度函数未包含量测信息。针对此问题,提出了一种改进高阶容积粒子滤波(CPF)的系统状态估计算法。算法采用七阶正交容积卡尔曼滤波（7th-CQKF）对PF的粒子进行传递,使得先验分布更新阶段融入最新量测信息;通过7th-CQKF设计重要性密度函数,提高对状态后验概率密度的逼近程度;通过反比例函数计算粒子权重,突出大噪声粒子与小噪声粒子权重差别,提高粒子有效性。仿真结果表明,改进高阶容积粒子滤波的估计精度高于容积粒子滤波（CPF）。     

OFDM系统采样钟补偿算法及其FPGA实现

利用数字内插滤波器完成全数字域采样钟同步已广泛应用于OFDM数字接收机中.文中利用两个Farrow结构的内插滤波器,同时提高工作时钟对过采样信号进行数字域内插,完成接收端和发送端之间的采样时钟的完全匹配,并且根据硬件器件的特性和算法结构,逐级进行模块变量定点处理.基于实测数据的分析表明,该FPGA数字域采样钟补偿算法不仅有稳定的性能,而且其模块化设计也有利于更高阶算法或多通道系统的实现.     

基于改进粒子滤波的GPS接收机自主完好性监测算法

针对基本粒子滤波重采样过程中粒子权值退化和多样性丧失的问题,将遗传算法引入基于神经网络的权值调整粒子滤波算法中,结合了遗传算法全局寻优的收敛性与神经网络局部寻优的快速性优点。将提出的算法与对数似然比方法结合用于GPS接收机自主完好性监测,通过建立一致性检验统计量实现对故障卫星的检测与隔离。通过采集实测数据进行验证,结果表明:该算法可以成功检测和隔离故障卫星,其性能优于基于基本粒子滤波的接收机自主完好性监测,验证了该算法应用于GPS接收机自主完好性监测的可行性和有效性。     

混沌粒子群优化粒子滤波算法

针对基于粒子群优化算法的粒子滤波计算复杂度大,并且容易陷入局部最优,提出了一种新的基于混沌的粒子群优化粒子滤波算法。该算法在粒子群优化的基础上,引入混沌序列,利用混沌运动的遍历性、随机性等特点改善了初始样本的质量,同时利用混沌扰动避免搜索过程陷入局部最优,使算法具有更快的收敛速度和更好的全局搜索能力。最后利用UNGM模型将该算法与标准粒子滤波和粒子群粒子滤波进行仿真对比,并利用纯角度目标跟踪模型验证了算法的有效性。实验结果表明,该算法改善了粒子群优化算法的粒子滤波易陷入局部最优的现象,提高了粒子滤波的精度和速度,具有较高的应用价值。     

采用混合t分布粒子滤波器的视觉跟踪

由于目标数量的变化,观测数据的岐义性和目标间的遮挡,多目标视觉跟踪问题面临多种困难.基于目标分布的有限t分布混合模型提出了一种混合t分布粒子滤波器以实现多目标跟踪.在算法中,每个被跟踪目标指派一个独立的粒子滤波器,显式处理当新目标出现在场景中时对应粒子滤波器的初始化,当被跟踪目标消失时,对应粒子滤波器的删除.混合t分布...     

IIR数字滤波器设计的粒子群优化算法

本文探讨了粒子群优化算法及其性能评估准则，然后重点研究了IIR数字滤波器设计的粒子群优化算法及其实现步骤。最后，通过IIR数字低通、带通滤波器设计两个实例证明了本文算法的有效性。     

粒子群优化算法在FIR数字滤波器设计中的应用

本文针对有限脉冲响应(FIR)数字滤波器的设计实质上是一个多参数优化问题,提出了一种用粒子群优化算法(PSO)设计FIR数字滤波器的方法.首先将滤波器的设计问题转化为滤波器参数的优化问题,然后利用粒子群优化算法对整个参数空间进行高效并行搜索以获得参数的最优化.FIR数字低通、带通滤波器设计实例证明了该方法的有效性和优越性.