Adaptive processing using real weights based on a direct data domain least squares approach

In traditional, adaptive signal processing algorithms one change both the amplitude and phase of the weight vectors associated with an array at each of the antenna elements. The use of complex weights offers greater control over the array response at the expense of system complexity. However, it is easier if one requires only amplitude variation with a fixed phase for all the weight vectors associated with all the antenna elements. Because one uses only real arithmetic operations to find the amplitude of the weights connected to the antenna, the computational complexity is reduced considerably. Hence, this paper addresses the use of real weights in an adaptive system. In this paper we describe a new direct data domain least squares (D/sup 3/LS) method using real weights, which utilizes only a single snapshot of the data for adaptive processing. This technique may be useful for real time implementation of the D/sup 3/LS method on a chip.     

Super gain beamformer (N/sup 3/) for source power and bearing estimation

An improved super gain beamformer is presented for evaluating the source powers and bearings of the received signals at a sensor array. The processor gain is not limited to conventional bounds and is able to detect extremely weak signals.     

用禁忌搜索实现DOA估计

为解决DOA参数估计搜索算法中局部极值和实时性等问题,从现代优化理论的角度出发,选用比遗传算法、模拟退火法更易利用问题特殊信息的禁忌搜索算法来求解DOA的极大似然估计.理论分析和仿真结果表明:该方法不仅能获得全局最优解;而且在获得与AP算法相当测向精度和测向分辨率的情况下,有更低的计算量;对相干信号,其性能比AP算法有较大的提高.     

基于对数螺旋阵的波达方向估计

系统渡达方向(DOA)的估计能力受天线阵的几何结构影响很大.提出了一种新的二维天线阵列流形--对数螺旋阵,该阵列流形具有天线单元数少、天线孔径大、分辨力高的特点.通过粒子群优化方法(PSO)确定了无栅瓣的阵结构参数,计算了此阵的天线方向图并与矩形阵、圆环阵做了比较,利用MUSIC方法进行了二维空间谱估计,仿真结果表明:利用该对数螺旋多天线阵可以实现高分辨二维DOA估计.     

Super gain beamformer (N/sup 2/) for source power and bearing estimation

A technique for evaluating the source powers and bearings of the received signals at a sensor array is presented. The processor gain is not limited to conventional bounds and is able to detect extremely weak signals.     

Electromagnetic modeling for design and loss estimation of resonant integrated spiral planar power passives (ISP/sup 3/)

Over the past few years, the electromagnetic integration of multiple passive components into a single integrated planar power passive module has been shown viable, not only for resonant structures, but recently also for nonresonant applications. In this paper, the development of an electromagnetic model for a resonant integrated spiral planar power passive (ISP/sup 3/) structure is presented. For the design of the required passive component values to be integrated, a comprehensive electromagnetic model based on energy storage is presented. The overall structure losses including winding, core and dielectric losses are also estimated through the development of a partly one-dimensional electromagnetic field approximation. Finally, these electromagnetic models for design and loss estimation are compared to experimental results for three different prototypes of a particular design. The results show agreement to well within 10% of component and loss values in almost all cases.     

基于改进多信号分类算法的波达方向估计

针对传统波达方向估计算法在低信噪比条件下性能表现不佳的问题,本文提出了一种基于改进多信号分类的波达方向估计算法。本文首先对多信号分类算法的不足进行分析,并采用时间平滑技术构建相关矩阵,然后采用相关矩阵建立空间谱函数达到波达方向估计,最后采用仿真实验对算法的性能进行测试。结果表明,本文算法可以快速准确的估计出多个信号的波达方向,降低了波达方向估计误差,而且性能远远优于其它改进多信号分类算法。     

Direction of arrival estimation based on phase differences usingneural fuzzy network

A new high-resolution direction of arrival (DOA) estimation technique using a neural fuzzy network based on phase difference (PD) is proposed. The conventional DOA estimation method such as MUSIC and MLE, are computationally intensive and difficult to implement in real time. To attack these problems, neural networks have become popular for DOA estimation. However, the normal neural networks such as the multilayer perceptron (MLP) and radial basis function network (RBFN) usually produce the extra problems of low convergence speed and/or large network size (i.e., the number of network parameters is large). Also, the may to decide the network structure is heuristic. To overcome these defects and take use of neural learning ability, a powerful self-constructing neural fuzzy inference network (SONFIN) is used to develop a new DOA estimation algorithm. By feeding the PDs of the received radar-array signals, the trained SONFIN can give high-resolution DOA estimation. The proposed scheme is thus called PD-SONFIN. This new algorithm avoids the need of empirically determining the network size and parameters in normal neural networks due to the powerful on-line structure and parameter learning ability of SONFIN. The PD-SONFIN can always find itself an economical network size in the fast learning process. Our simulation results show that the performance of the new algorithm is superior to the RBFN in terms of convergence accuracy, estimation accuracy, sensitivity to noise, and network size     

Phase-only adaptive Processing based on a direct data domain least squares approach using the conjugate gradient method

Generally, adaptive antenna arrays operate by changing the complex adaptive weights consisting of both magnitudes and phases applied at each of the antenna elements. However, it is easier to require the adaptive weights have only phase variation with a fixed magnitude at each of the antenna elements. Hence, This work addresses the phase only adaptive systems whose weights have a fixed magnitude through a new phase only adaptive method based on a direct data domain least squares approach (D/sup 3/LS), which utilize only a single snapshot of the data for adaptive processing.     

基于宽频带多基线阵列解模糊的波达角估计算法

针对宽频带电子信号侦测系统测向精度与解相位模糊能力这一矛盾问题,根据多基线测向原理,提出一种基于宽频带多基线阵列解模糊的波达角估计算法,并进行了仿真分析。结果表明,该方法可有效求解宽频带多基线阵列相位模糊,提高对目标在相位差测量精度不高情况下的测向精度。     

Direction-of-arrival estimation via exploitation ofcyclostationary-a combination of temporal and spatial processing

Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or band rates. By exploiting cyclostationarity, i.e. evaluating the cyclic correlations of the received data at certain cycle frequencies, one can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other cochannel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. An approach for exploiting cyclostationarity that is asymptotically exact for either narrowband or broadband sources, unlike previous methods, is proposed. The method also has significant implementational advantages over the earlier techniques. The simulation results indicate a significantly better performance in some environments     

Channel phase calibration based on RARE in mode domain for direction of arrival estimation

Multidimensional Systems and Signal Processing - A novel method is proposed to estimate direction of arrival (DOA) with uniform circular array (UCA) in the presence of phase errors. Inspired by the...     

基于累积量的互耦误差下相干信号DOA估计

在高斯色噪声和阵列互耦误差背景下,针对相干信号源和非相干信号源并存的问题,提出了一种准确估计信号源到达角(DOA)的算法。首先,采用辅助阵元法将互耦误差从阵列流形中分离;然后结合空间平滑技术和四阶累积量构建平滑矩阵,实现对高斯噪声的抑制和对信号的解相干;最后使用ESPRIT算法获得信号源的来波方向。仿真结果表明,文中算法有效解决了阵列互耦和信源相干的影响,在高斯白噪声和高斯色噪声环境下均能精确地估计DOA。     

Spotlight SAR data focusing based on a two-step processing approach

The authors present a new spotlight SAR data-focusing algorithm based on a two-step processing strategy that combines the advantages of two commonly adopted processing approaches: the efficiency of SPECAN algorithms and the precision of stripmap focusing techniques. The first step of the proposed algorithm implements a linear and space-invariant azimuth filtering that is carried out via a deramping-based technique representing a simplified version of the SPECAN approach. This operation allows the authors to perform a bulk azimuth raw data compression and to achieve a pixel spacing smaller than (or equal to) the expected azimuth resolution of the fully focused image. Thus, the azimuth spectral folding phenomenon, typically affecting the spotlight data, is overcome, and the space-variant characteristics of the stripmap system transfer function are preserved. Accordingly, the residual and precise focusing of the SAR data is achieved by applying a conventional stripmap processing procedure requiring a minor modification and implemented in the frequency domain. The extension of the proposed technique to the case of high bandwidth transmitted chirp signals is also discussed. Experiments carried out on real and simulated data confirm the validity of the presented approach, which is mainly focused on spaceborne systems     

基于时空估计的冷像校正方法

冷像是影响制冷型红外探测器成像质量的重要因素。虽然可以通过非均匀校正技术进行去除,但当校正后的工作条件发生改变时,冷像的影响又会显现出来。根据冷像产生的机理以及频率特点,提出了一种基于时空估计的冷像校正算法。首先,通过使用小波分解与重构对原始图像进行冷像噪声空间域估计;然后,利用自适应时域低通滤波获得冷像噪声的时间域估计;最后,利用原始图像与获得的冷像估计噪声做差完成校正过程。使用仿真和实际的红外图像序列进行实验,结果表明所提算法能够有效地去除冷像噪声。     

基于数字信道化和空时频分析的多网台跳频信号DOA估计

提出了一种基于数字信道化和空时频分析的多跳频信号DOA(direction of arrival)估计方法,该方法能够在欠定条件下(传感器数目小于信号数目)实现多个信号的精确测向.首先利用多相滤波器组实现数字信道化接收机的设计,然后对各子信道的数据进行时频分析,得到全景时频图;再在时频域提取跳频信号的有效hop,针对每个hop建立一个空时频矩阵;最后运用空时频方法估计每hop的DOA.仿真结果验证了方法的有效性.     

Volume rendering of 3D medical ultrasound data using direct feature mapping

The authors explore the application of volume rendering in medical ultrasonic imaging. Several volume rendering methods have been developed for X-ray computed tomography (X-CT), magnetic resonance imaging (MRI) and positron emission tomography (PET). Limited research has been done on applications of volume rendering techniques in medical ultrasound imaging because of a general lack of adequate equipment for 3D acquisitions. Severe noise sources and other limitations in the imaging system make volume rendering of ultrasonic data a challenge compared to rendering of MRI and X-CT data. Rendering algorithms that rely on an initial classification of the data into different tissue categories have been developed for high quality X-CT and MR-data. So far, there is a lack of general and reliable methods for tissue classification in ultrasonic imaging. The authors focus on volume rendering methods which are not dependent on any classification into different tissue categories. Instead, features are extracted from the original 3D data-set, and projected onto the view plane. The authors found that some of these methods may give clinically useful information which is very difficult to get from ordinary 2D ultrasonic images, and in some cases renderings with very fine structural details. The authors have applied the methods to 3D ultrasound images from fetal examinations. The methods are now in use as clinical tools at the National Center of Fetal Medicine in Trondheim, Norway.     

基于数据时空相关性的智能台区识别技术

在用电信息采集系统中经常因各种原因导致台区档案的不精确,人工识别台区的方法耗时费力且人工成本很高,而专用设备识别方法的设备成本很高,同时也增加了电力人员的工作量。为了解决上述问题,通过分析发现同一台区电能采集设备的电压数据存在时间和空间相关性,在此基础上采用数据挖掘中的分类方法将每个台区的采集设备划分为一类,通过计算待识别的采集设备归属于各个分类的概率判断其台区归属关系。该方法既能保证识别效率又能减少设备成本和人员工作量。仿真结果表明该方法具有较高的识别精度。     

Accurate direction‐of‐arrival estimation of multiple sources using a genetic approach

In this paper, we present an accurate direction‐of‐arrival (DOA) estimation method, which is based on the maximum likelihood (ML) principle and implemented using a modified and refined genetic algorithm (GA). With the newly introduced features—intelligent initialization and the emperor‐selective (EMS) mating scheme, carefully selected crossover and mutation operators and fine‐tuned parameters such as the population size, the probability of crossover and mutation etc., the GA‐ML estimator achieves fast global convergence. A GA operator and parameter standard is suggested for this application, which is independent of the source and array configurations except the number of sources. Simulation results demonstrate that in general scenarios, the proposed estimator is the most efficient in computation and its statistical performance is the best among all popular ML‐based DOA estimation methods. Copyright © 2004 John Wiley & Sons, Ltd.     

基于空间频域算法的白光干涉微位移测量法

为了满足光学及精密机械领域精密测量的要求,提高微位移器位移量的测量精度,在对传统的接触式干涉仪改造的基础上,采用空间频域算法计算出了白光干涉图零级条纹的中心位置,并根据零级条纹中心的移动量得到待测的微位移量.该方法能够测量连续和阶跃变化的位移量.实验以压电陶瓷微位移装置(PZT)为例,测试了其电压一位移曲线,测量重复性达到1 nm.结果表明,该方案稳定有效,不易受噪声和色散的影响,测量重复性好.