基于对象性测度估计和霍夫森林的目标检测方法

实现高效准确的目标检测算法在视频监控、自动导航等诸多领域至关重要的作用。针对现有目标检测算法速度不高且鲁棒性差的缺点,提出了一种基于对象性测度估计和霍夫森林的快速目标检测方法。首先,基于自下而上的视觉注意机制,采用对象性测度估计,提取图像中的物体候选集;然后,在由物体候选集确定的感兴趣区域内进行霍夫森林目标检测,确定目标中心位置;最后,结合目标中心所在的对象性测度估计候选框的尺度信息,确定目标大小。实现结果表明,该方法在提高霍夫森林目标检测算法检测准确度的同时,大大提升了检测速率。     

混响和空间噪声环境下的鲁棒时延估计方法

针对混响和空间噪声,本文提出一种基于三麦克风特征值分解的时延估计算法.该算法将混响和空间噪声下的时延估计构造成一个双入三出(DITO)系统的信道盲辨识问题,通过对房间冲激响应进行盲辨识来去除混响的影响,通过双初值初始化来分离声源与空间噪声的时延信息, 从而提高了实际环境下时延估计算法的性能.仿真实验结果表明,在混响和空间噪声环境下,本文算法能有效地进行时延估计.     

采用精确时延模型基于路径的缓冲器插入时延优化

提出了一种基于路径的缓冲器插入时延优化算法 ,算法采用高阶模型估计连线时延 ,用基于查表的非线性时延模型估计门延迟 .在基于路径的时延分析基础上 ,提出了缓冲器插入的时延优化启发式算法 .工业测试实例实验表明 ,该算法能够有效地优化电路时延 ,满足时延约束     

采用精确时延模型基于路径的缓冲器插入时延优化

提出了一种基于路径的缓冲器插入时延优化算法,算法采用高阶模型估计连线时延,用基于查表的非线性时延模型估计门延迟.在基于路径的时延分析基础上,提出了缓冲器插入的时延优化启发式算法.工业测试实例实验表明,该算法能够有效地优化电路时延,满足时延约束.     

分布式雷达盲源分离干扰抑制算法

针对大功率干扰下的分布式多站雷达探测能力下降的问题,本文提出了一种新的基于盲源分离的干扰抑制方法。该方法对多部雷达接收信号进行信号级和数据级的联合处理,包括干扰相对时延估计及补偿-盲源分离-多组合配对定位三个步骤。首先分别以不同接收回波信号为参考,采用相关法估计各站点干扰信号相对时延,并进行补偿使干扰成分得到校准。然后针对校准后的信号,采用盲源分离算法,实现干扰信号和目标回波信号分离。最后,利用多组合配对定位方法,剔除由于盲源分离得到的虚假目标定位点,从而得到真实目标位置信息。最后本文通过仿真实验证明了该算法的有效性。      

DS—CDMA系统中基于CMOE准则的DOA估计

针对DS—CDMA系统的多用户环境,提出了一种有效的DOA估计算法。首先基于CMOE准则实现各路径的盲分离,即通过抑制多址干扰来提取感兴趣信息;然后采用矩阵点除算法或Ls拟合法从分离的信息中求解DOA信息。算法避免了特征值分解这类复杂运算,同时也不需要估计信源个数并自动实现了路径配对,仿真实验验证了算法的有效性。     

基于两级变参数滤波时延校正的声源定向

在人机交互、视频会议、军事国防等众多领域中,基于麦克风阵列的声源定位系统已经受到了人们的广泛关注。在空间噪声和混响的环境中,时延估计往往会出现很大的偏差,而声源角度的计算又依赖于时延估计的准确性。因此,本文在双阵元模型下提出了一种用于声源定向的时延校正算法,该算法采用一个权值系数可变的两级滤波器对GCC-PHAT-ργ估计出的时延点进行校正,有效地让偏差较大的时延点回归到正确的时延群当中,从而避免了错误时延值对进一步角度定向的影响。实验结果表明,本文提出的算法在不删除时延异常点的前提下,在误差均值和均方根误差等方面都表现出了很好的性能,而且对每组数据进行角度定向的时间都很短。理论分析与实验结果表明该方法不仅有效的提高了角度估计的估计精度,而且当说话人以正常走路的速度移动时,该算法可对说话人的方向进行及时的跟踪。      

一种新颖的时延与到达角联合估计算法

本文提出了一种新颖,有效的时延与到达角联合估计算法.算法在频域空间建立了关于到达角向量和时延向量的可分维数据结构.利用PRO-ESPRIT算法获得了到达角的精确估计,同时借助子阵矩阵束的广义特征向量实现了不同时延向量的分离快速估计,并提出了基于ESPRIT的时延快速估计方法.仿真实验显示了本文算法计算量小,性能优良.     

异步DS-CDMA系统中基于矩阵点除算法的DOA估计

针对异步DS-CDMA系统中的多用户环境,本文提出了一种低复杂度的DOA估计算法——矩阵点除算法。该算法通过对感兴趣信息的逐次分离,实现了DOA的逐路径估计。算法具有两方面显著优势:(1)克服了传统的DOA估计算法在路径总数大于天线阵元数时不能工作这一缺陷:(2)避免了计算复杂的特征值分解运算,大大降低了算法复杂度。仿真实验验证了算法的有效性。     

多径信号到达角和时延高分辨联合估计算法

本文提出了一种新的高分辨高精度的多径信号到达角和时延联合估计算法.该方法通过对多径信号与参考信号进行相关处理,再根据PRO-ESPRIT算法的思想,实现了DOA(Direction-Of-Arrival)估计;并对相关延迟向量进行变换,从互功率谱相位中提取时延信息,完成了高分辨的TOA(Time-Of-Arrival)估计.最后,本文推导了频域模型下到达角和时延联合估计的Cramer-Rao下界.并将通过仿真对本算法的性能进行了评估.     

Estimation of multipath parameters in wireless communications

In a parametric multipath propagation model, a source is received by an antenna array via a number of rays, each described by an arrival angle, a delay, and a fading parameter. Unlike the fading, the angles and delays are stationary over long time intervals. This fact is exploited in a new subspace-based high-resolution method for simultaneous estimation of the angle/delay parameters from multiple estimates of the channel impulse response. A computationally expensive optimization search can be avoided by using an ESPRIT-like algorithm. Finally, we investigate certain resolution issues that take the fact that the source is bandlimited into account     

均匀圆阵中盲联合角度和时延估计方法

提出了均匀圆阵中一种盲联合角度和时延的估计方法（BJADE）。对阵列天线输出的过采样样本的Fourier变换后信号进行分析，表明此信号具有三线性模型特征。该算法先利用三线性交替最小二乘（TALS）算法估计出方向矩阵和时延矩阵，然后利用时延矩阵的Vandermonde特征、基于最小二乘方法进行时延估计；利用方向矩阵结构特点和基于最小二乘方法进行二维角度估计。仿真结果说明BJADE方法具有较好角度和时延估计性能，且在过载情况下仍有较好的性能。该方法无须信道冲激响应，是一种盲、健壮的联合处理方法。     

2D DOA estimation for noncircular sources using L-shaped sparse array

We present an algorithm for two-dimensional (2D) direction-of-arrival (DOA) estimation of noncircular sources using an L-shaped sparse array. An L-shaped sparse array consisting of two co-prime arrays is firstly introduced. Then, the fourth-order-cumulants (FOCs) of received data are used to construct a FOC matrix (FOCM), by which we can get the estimations of elevation angles. With the estimated elevation angles, the azimuth angles can be estimated by a low-complexity signal separation algorithm. During the procedure used for estimating azimuth angles, no any eigenvalue decomposition (EVD), peak search and pair-matching procedure need to be implemented. Although the aperture is extended significantly, the computation complexity of proposed algorithm still is acceptable. Compared with some analogous algorithms, our approach shows more attractive estimation performance. A lot of simulation results prove the advantages of proposed DOA estimation technology.     

异步带限DS-CDMA系统在多径衰落信道下的子空间时延序贯估计算法

该文提出了适合于异步DS-CDMA系统在多径衰落信道下的子空间时延序贯估计算法,称为MUSIC-SEA算法。该算法引入了序贯估计思想,将已估时延信息融入后续时延估计过程中,整个时延估计过程为:首先估计噪声子空间,然后依次对每个时延进行粗略估计和精确搜索。给出了MUSIC-SEA算法的迭代执行方法,并进行了性能分析和计算机仿真。结果表明,MUSIC-SEA算法能有效除去多径间的相互影响,提高时延正确估计概率和时延估计精度。     

一种新的基于参数信道模型的MIMO信道估计算法

针对频率选择性块衰落MIMO信道,该文提出一种改进的基于参数信道模型的信道估计方法。该方法首先通过修正后的TST-MUSIC算法估计多径的传播时延和角度。由时延和角度信息,得到一种基于参数信道模型的信道估计方法。仿真结果表明此种方法可以有效地减少参数估计的维数,其性能要远远优于非参数的最小二乘估计器。     

WRAN系统中基于自适应内插的信道估计算法

提出了一种基于自适应复系数内插的信道估计算法,改善了无线区域网络（WRAN）系统对抗动态多径时延的能力。WRAN是第一个采用认知无线电技术改善频谱效率的宽带接入标准,系统在下行链路中采用了正交频分复用（OFDM）调制技术,而信道估计技术对于采用相干解调的OFDM系统十分重要。传统的OFDM信道频域响应（CFR）估计算法通常采用实系数频域内插的方式,在对抗WRAN系统长多径时延信道时,不能有效地工作。该文在研究实系数FIR内插变换域响应的基础上,提出了一种复系数内插算法。为了同时适用于短时延信道,提出了一种低复杂度、自适应匹配信道最大多径时延的算法。通过仿真,验证了该算法能够对抗更大的多径时延,提高信道估计的精度,改善系统误码性能。      

基于三阶累积量的多径时延估计

研究多径传输条件下的时延估计问题。利用三阶累积量的一维切片作为高阶统计量,结合相关算法原理,提出一种新的时延估计算法。为提高时延估计精度,对相关数据进行了加权处理。该算法可有效抑制空间相关高斯噪声或对称分布噪声,得到非高斯信号准确的时延估计。算法具有计算量小,易于实现的优点。仿真结果表明了该算法的有效性。     

Adaptive estimation of latency changes in evoked potentials

Changes in latency of evoked potentials (EP) may indicate clinically and diagnostically important changes in the status of the nervous system. A low signal-to-noise ratio of the EP signal makes it difficult to estimate small, transient, time-varying changes in latency, or delays. Here, the authors present an adaptive algorithm that estimates small delay (latency change) values even when EP signal amplitudes are time-varying. When the delay is time invariant, the adaptive algorithm produces an unbiased estimate with delay estimation error less than half of the sampling interval. A lower estimation error variance is obtained when, in a pair of signals, the adaptive algorithm delays the signal with the higher SNR. The adaptive delay estimation algorithm was tested on intra-operative recordings of somatosensory EP, and analysis of those recordings reveals that the anesthetic etomidate produces a step change in the amplitude and latency of the EP signals     

Antenna-Array-Assisted Frequency Offset Estimation and Data Detection in an Uplink Multiuser MIMO-OFDM Interference Network

Due to the popularity of IEEE 802.11a/g/n wireless local area networks, the high-density deployment of access points and their serious mutual interference have become a pressing concern, and made both frequency acquisition and data detection even more difficult. In addition, improving the network coverage and scalability in the mesh mode of IEEE 802.16 wireless metropolitan area network, space and frequency information can provide abundant scheduling information under the configuration. In light of this, this paper presents an antenna-array-assisted algorithm to solve these two problems in a multiuser multiple-input-multiple-output orthogonal frequency division multiplexing interference network. The algorithm begins with the estimation of three channel parameters: frequency offsets, delays and angle selectivity. To make a good use of the array signal characteristics, these three parameters are estimated in a frequency/delay-angle-frequency/delay (FAF) tree structure, in which two frequency/delay estimations and one angle estimation are employed alternatively. One special feature in the FAF tree structure is that temporal filtering or spatial beamforming is invoked between the parameter estimations to decompose signals so as to enhance the estimation accuracy. Thereafter, based on these parameter estimates, a data detection procedure is developed to mitigate both multiple access interference (MAI) and co-channel interference (CCI). Simulations show that the proposed algorithm can provide satisfactory performance even in networks with MAIs and CCIs sharing the same frequency band.     

A low-complexity joint 2D-DOD and 2D-DOA estimation algorithm for MIMO radar with arbitrary arrays

In this article, we study the problem of four-dimensional angles estimation for bistatic multiple-input multiple-output (MIMO) radar with arbitrary arrays, and propose a joint two-dimensional direction of departure (2D-DOD) and two-dimensional direction of arrival (2D-DOA) estimation algorithm. Our algorithm is to extend the propagator method (PM) for angle estimation in MIMO radar. The proposed algorithm does not require peak searching and eigenvalue decomposition of received signal covariance matrix, because of this, it has low computational complexity. And it can achieve automatic pairing of four-dimensional angles. Furthermore, the proposed algorithm has much better angle estimation performance than interpolated estimation method of signal parameters via rotational invariance techniques (ESPRIT), and has very close angle estimation performance to ESPRIT-like algorithm which has higher computational cost than the proposed algorithm. We also analyze the complexity and angle estimation error of the algorithm, and derive the Cramer‐Rao bound (CRB). The simulation results verify the effectiveness and improvement of the proposed algorithm.