基于粒子滤波的RFID室内节点定位跟踪研究

为了解决复杂室内环境下的RFID动态节点定位跟踪问题,文中建立了动态节点的运动模型和信号测量模型。仿真采用基于信号RSSI定位方法,结合运用等边三角形定位算法。由于室内射频信号具有较高的噪声污染,因此首先对采集的信号运用粒子滤波技术进行滤波处理,然后运用高斯粒子滤波算法对室内移动的RFID进行了定位跟踪预测。仿真结果表明该算法可以有效地对室内动态节点进行定位跟踪,精度较高,稳定性好,结果进一步说明高斯粒子滤波能有效地抑制室内射频噪声。     

Mobile target tracking algorithm for wireless camera sensor networks with adjustable monitoring direction of nodes

Wireless camera sensor networks (WCSNs) possess a powerful physical environment monitoring capability. Camera nodes with adjustable monitoring directions further improve their flexibility. This study focuses on tracking multiple mobile targets to investigate the node scheduling and target location evaluation strategy of WCSNs on the basis of rotating nodes. By referring to existing research, this study improves the camera node monitoring and rotation model and proposes three network performance evaluation indicators. The proposed algorithm schedules nodes and their monitoring directions by using the unutilized energy of the nodes and the number of monitored targets. It also predicts the moving trends of the targets and selects active nodes by using the locations and linear speeds of the targets. Experimental results show that the proposed algorithm has a high target tracking accuracy. Compared with traditional target tracking algorithms, the proposed algorithm can effectively reduce the number of active nodes, balance the energy consumption between nodes, and prolong network lifetime.     

一种波达方向估计的快速算法

提出一种波达方向估计的快速算法.为了估计到信号子空间,该方法只需要多级维纳滤波器的前向递推,不需要估计样本协方差矩阵和对其作特征值分解,也不需要多级维纳滤波器的后向递推.从而使得该方法具有小运算量和低复杂度的特点,易于实时处理.由于不需要估计样本协方差矩阵,所以该方法可以应用在小样本和快时变的信号环境中.仿真结果证明了该方法的有效性.     

Subspace-based direction-of-arrival estimation using nonparametricstatistics

The problem of subspace estimation using multivariate nonparametric statistics is addressed. We introduce new high-resolution direction-of-arrival (DOA) estimation methods that have almost optimal performance in nominal conditions and are robust in the face of heavy-tailed noise. The extensions of the techniques for the case of coherent sources are considered as well. The proposed techniques are based on spatial sign and rank concepts. We show that spatial sign and rank covariance matrices can be used to obtain convergent estimates of the signal and noise subspaces. In the proofs, the noise is assumed to be spherically symmetric. Moreover, we illustrate how the number of signals may be determined using the proposed covariance matrix estimates and a robust estimator of variance. The performance of the algorithms is studied using simulations in a variety of noise conditions including noise that is not spherically symmetric. The results show that the algorithms perform near optimally in the case of Gaussian noise and highly reliably if the noise is non-Gaussian     

Dynamic clustering for acoustic target tracking in wireless sensor networks

We devise and evaluate a fully decentralized, light-weight, dynamic clustering algorithm for target tracking. Instead of assuming the same role for all the sensors, we envision a hierarchical sensor network that is composed of 1) a static backbone of sparsely placed high-capability sensors which assume the role of a cluster head (CH) upon triggered by certain signal events and 2) moderately to densely populated low-end sensors whose function is to provide sensor information to CHs upon request. A cluster is formed and a CH becomes active, when the acoustic signal strength detected by the CH exceeds a predetermined threshold. The active CH then broadcasts an information solicitation packet, asking sensors in its vicinity to join the cluster and provide their sensing information. We address and devise solution approaches (with the use of Voronoi diagram) to realize dynamic clustering: (I1) how CHs operate with one another to ensure that only one CH (preferably the CH that is closes to the target) is active with high probability, (I2) when the active CH solicits for sensor information, instead of having all the sensors in its vicinity reply, only a sufficient number of sensors respond with nonredundant, essential information to determine the target location, and (I3) both the packets that sensors send to their CHs and packets that CHs report to subscribers do not incur significant collision. Through both probabilistic analysis and ns-2 simulation, we use with the use of Voronoi diagram, the CH that is usually closes to the target is (implicitly) selected as the leader and that the proposed dynamic clustering algorithm effectively eliminates contention among sensors and renders more accurate estimates of target locations as a result of better quality data collected and less collision incurred.     

Fast algorithm for minimum-norm direction-of-arrival estimation

The original minimum-norm direction-of-arrival estimator, proposed by Kumaresan and Tufts, employs the noise-subspace projection matrix, calculated by the eigendecomposition of spatial covariance matrix. The present authors propose a novel noneigenvector fast algorithm, which calculates the required minimum-norm function using the special power basis instead of eigenvector basis. The proposed algorithm provides a substantial saving as compared with computational loads of the eigendecomposition-based minimum-norm algorithm in cases when the number of multiple sources is much lower than the number of array sensors. Some computer simulation results, verifying the high performance and accuracy of the proposed algorithm, are presented     

Robust spatial time-frequency distribution matrix estimation with application to direction-of-arrival estimation

We consider the problem of estimating spatial time-frequency distribution (STFD) matrices in the presence of impulsive noise. STFD matrices are widely used in sensor array processing for direction-of-arrival estimation and blind source separation of non-stationary sources. Conventional methods fail when the noise is non-Gaussian or impulsive. We propose robust techniques for STFD estimation which are based on pre-processing, robust position based estimation and robust covariance based estimation. The proposed methods are compared in terms of direction-of-arrival estimation performance.     

Distributed source modeling and direction-of-arrival estimationtechniques

In direction-of-arrival (DOA) estimation, the direction of a signal is usually assumed to be a point. If the direction of a signal is distributed due to some environmental phenomenon, however, DOA estimation methods based on the point source assumption may result in poor performance. We consider DOA estimation when the signal sources are distributed. Parametric and nonparametric models are proposed, and estimation methods are considered under these models. In addition, the asymptotic distribution of estimation errors is obtained to show the models' statistical properties     

基于聚类思想实现声探测器组网多目标跟踪法

介绍了一种基于聚类思想实现声探测器组网系统多目标跟踪的方法.简略介绍了声探测器组网系统的组成和工作方式,详细介绍了该系统在工程应用中采用的多目标跟踪的设计方法.试验结果证明该方法具有良好的准确性和实时性.     

船载式水声跟踪系统定位原理及误差分析

阐述了水下定位系统的研究意义和基本分类,介绍了船载式水声跟踪系统的定位原理、实现方法,以及优点和不足之处,给出定位计算及姿态修正公式。针对声速、基阵孔径、时延值和姿态角等参数对系统产生的误差,进行理论公式推导和分析,最后给出系统误差公式。结合误差公式和随机误差理论,分析了跟踪系统的定位误差来源,并给出减小误差的基本方法。     

基于非圆信号的二维测向算法

提出了一种基于窄带非圆信号的二维测向算法,利用非圆信号的椭圆协方差矩阵非零特性将阵列有效阵元数和孔径同时扩展,提高多信号检测的能力。进一步通过利用L阵的几何性质和两子阵间的互相关来滤除噪声,提高角度估计精度,并采用快速算法获得信号方位角和俯仰角。最后计算机仿真结果验证了该方法由于利用非圆信号特性比传统测向算法的估计性能更高。     

Off-grid direction-of-arrival estimation for wideband noncircular sources

Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer–Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.     

A conjugate augmented approach to direction-of-arrival estimation

In this paper, we propose a new Direction-of-Arrival (DOA) estimator called Conjugate Augmented MUSIC (CAM). The basic idea of CAM is to use the second-order statistics of the received signals to get the conjugate steering matrix. This, together with the steering matrix, is used to find the fourth-order cumulants. From that the source directions are obtained using the MUSIC-like algorithm. CAM can resolve two times the number of directions when compared to MUSIC-like estimator. Moreover, simulation results show that the estimation capacity, angle resolution, immunity to noise, and the number of required snapshots are all better than MUSIC-like algorithm.     

一种基于循环互相关的非相干源信号方向估计方法

给出了基于循环互相关运算的阵列信号模型,根据该信号模型,运用MUSIC算法得到了对空间非相干源信号方向进行估计的有效方法—CCC-MUSIC算法,定性的分析及仿真实验均说明了所给方法具有较好的抑制噪声和选择信号的能力。该算法将为利用天线阵列提取具有循环平稳特性的源信号方向这一问题提供较好的实现方法。     

A CLOSED-FORM WIDEBAND DIRECTION-OF-ARRIVAL ESTIMATION WITH CHIRPLET-BASED ADAPTIVE SIGNAL DECOMPOSITION ALGORITHM

The Direction-Of-Arrival (DOA) estimation with Coherent Signal Subspace (CSS)is not easy to cxtend from narrowband to wideband case.Time-frequency analysis is a powerfultechnique to deal with time-variant or non-stationary signal. Its combination with CSS exploresa new field in signal processing, especially the wideband DOA estimation. The chirp function isone of the most fundamental functions in nature. Many nature events can be modeled as chirpletfunction, such as radar system or scismic exploring.Hence,the chirplet-based signal decomposi-     

A new nested array for direction-of-arrival estimation

Multidimensional Systems and Signal Processing - In this paper, the problem of direction-of-arrival (DOA) estimation with a new nested array is addressed. It is known that the original two-level...     

Spatial polarimetric time-frequency distributions for direction-of-arrival estimations

Time-frequency distributions (TFDs) are traditionally applied to a single antenna receiver with a single polarization. Recently, spatial time-frequency distributions (STFDs) have been developed for receivers with multiple single-polarized antennas and successfully applied for direction-of-arrival (DOA) estimation of nonstationary signals. In this paper, we consider dual-polarized antenna arrays and extend the STFD to utilize the source polarization properties. The spatial polarimetric time-frequency distributions (SPTFDs) are introduced as a platform for processing polarized nonstationary signals, which are received by an array of dual-polarized double-feed antennas. This paper deals with narrow-band far-field point sources that lie in the plane of the receiver array. The source signals are decomposed into two orthogonal polarization components, such as vertical and horizontal. The ability to incorporate signal polarization empowers the STFDs with an additional degree of freedom, leading to improved signal and noise subspace estimates for direction finding. The polarimetric time-frequency MUSIC (PTF-MUSIC) method for DOA estimation based on the SPTFD platform is developed and shown to outperform the time-frequency, polarimetric, and conventional MUSIC techniques, when applied separately.     

水下目标在被追踪过程中的声反射信号模拟

为模拟水下目标在被追踪过程中的声反射信号,根据鱼雷和目标的运动方程,采用尾追法进行弹道分析,研究鱼雷追踪目标的轨迹,同时根据鱼雷与目标的距离,生成不同自导信号形式,并通过计算得到反射信号的多普勒频偏和信号强度,最终将数字信号转换为模拟信号供实验室测试,或为其他任务提供模拟信号,对水下目标的设计及研制具有重要作用。