Optimum filter for detection of a target in nonoverlapping scene noise

A filter function is derived for input signals containing a target that is spatially disjoint (that is, nonoverlapping) with the input scene noise. The optimization metric is the ratio of the square of the expected value of the correlation peak to the expected value of the output signal energy. In this model the effects of the nonwhiteness of the scene noise, the nonstationarity of the scene noise that is due to the limited size of the input scene, the nonoverlapping of the target and the scene noise, and the unknown variations of the target illumination are considered. We show that, for the nonoverlapping target and the scene noise, the target window and the scene-noise window strongly influence the optimum filter function.     

Performance of minimum-mean-square-error filters for spatially nonoverlapping target and input-scene noise

Using computer simulations, we investigate the performance of a minimum-mean-square-error filter for input-scene noise that is spatially nonoverlapping (disjoint) with a target for a limited set of images. Different input-scene-noise statistics are used to test the filter performance. We show that in the presence of spatially nonoverlapping target and input-scene noise, the output of the minimummean- square-error filter has a well-defined correlation peak, small sidelobes, and a high peak-to-correlationenergy ratio compared with other widely used filters such as the classical matched filter, the phase-only filter, and the inverse filter. We also test the robustness of the minimum-mean-square-error filter to errors in noise statistics used in the filter design. We show that, for the images tested here, the performance of the minimum-mean-square-error filter is not sensitive to errors in noise statistics and the filter can detect the target even if a considerable error exists. The discrimination capability and the illumination sensitivity of the minimum-mean-square-error filter are also tested.     

Performance of an optimum receiver designed for pattern recognition with nonoverlapping target and scene noise

The design of an optimum receiver for pattern recognition is based on multiple-alternative hypothesis testing with unknown parameters for detecting and locating a noisy target or a noise-free target in scene noise that is spatially nonoverlapping with this target. The optimum receiver designed for a noise-free target has the interesting property of detecting, without error, a noise-free target that has unknown illumination by using operations that are independent of the scene-noise statistics. We investigate the performance of the optimum receiver designed for nonoverlapping target and scene noise in terms of rotation and scale sensitivity of the input targets and discrimination against similar objects. Because it is not possible in practical systems to have a completely noise-free target, we examine how the performance of the optimum receiver designed for a noise-free target is affected when there is some overlapping noise on the target. The application of the optimum receiver to binary character recognition is described. Computer simulation results are provided.     

用数据矩阵分解确定多噪声源的频率和位置

本文提出利用均匀线阵接收的数据构造一种矩阵进行奇异值分解，以对频率、方位两参数进行分离估计，用频率谱估计出声源频率，用方位谱估计出声源方位角。并在此基础上改变变阵列中心位置确定噪声源位置，计算机模拟和声学实验证明了上述方法的可行性。     

Maximum likelihood for target location in the presence of substitutive noise

We consider the optimal likelihood algorithm for the estimation of a target location when the images are corrupted by substitutive noise. We show the relationship between the optimal algorithm and the sliced orthogonal nonlinear generalized (SONG) correlation. The SONG correlation is based on the application of a linear correlation to corresponding binary slices of both the input scene and the reference object with appropriate weight factors. For a particular case, we show that the optimal strategy is a function of only the number of pixels for which the gray values in the noisy image match the ones of the reference image when the substitutive noise is uniformly distributed. This is exactly what a particular definition of the SONG correlation does.     

Azimuth-invariant bistatic multichannel synthetic aperture radar for moving target detection and location

Ground moving target indication (GMTI) is one of the most important applications of the bistatic synthetic aperture radar (SAR) system as well as the monostatic system. An algorithm for moving target detection and location is presented with an azimuth-invariant bistatic multichannel SAR, which consists of one transmitter (channel) and multireceivers (multichannel). The algorithm is based on the discussion of the particularities of the bistatic SAR configuration including coherence improvement and clutter characteristics. Then, the corresponding compensating methods including two-dimensional range-azimuth prefiltering and bistatic differential range correction are proposed to solve these particularities. It is shown that using the compensating methods, the stationary clutter can be suppressed and the moving parameters of ground targets can be estimated accurately. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.     

Optimal facility location with multi-purpose trip making

We address the optimal location problem for two different types of service, designated as type-A and type-B, where some users may obtain both types of service in multi-purpose trips. We consider three user groups: (i) users of only the type-A service; (ii) users of only the type-B service; and (iii) users of both services in a single trip. We seek to locate three types of facilities: (i) type-A; (ii) type-B; and (iii) joint facilities that offer both services. We formulate a p-median-based model that minimizes the total travel distance and use it to investigate the effect of multi-purpose trip-makers on optimal facility types and locations. Examples are used to show that services tend to cluster in joint facilities, even when the proportion of multi-purpose behavior is small.     

Automated estimation of white Gaussian noise level in a spectrum with or without spike noise using a spectral shifting technique

Various tasks, for example, the determination of signal-to-noise ratios, require the estimation of noise levels in a spectrum. This is generally accomplished by calculating the standard deviation of manually chosen points in a region of the spectrum that has a flat baseline and is otherwise devoid of artifacts and signal peaks. However, an automated procedure has the advantage of being faster and operator-independent. In principle, automated noise estimation in a single spectrum can be carried out by taking that spectrum, shifting a copy thereof by one channel, and subtracting the shifted spectrum from the original spectrum. This leads to an addition of independent noise and a reduction of slowly varying features such as baselines and signal peaks; hence, noise can be more readily determined from the difference spectrum. We demonstrate this technique and a spike-discrimination variant on white Gaussian noise, in the presence and absence of spike noise, and show that highly accurate results can be obtained on a series of simulated Raman spectra and consistent results obtained on real-world Raman spectra. Furthermore, the method can be easily adapted to accommodate heteroscedastic noise.     

粒子滤波算法在静止目标定位时的数学建模

粒子滤波算法在目标定位中主要用于目标跟踪,对静止目标定位的应用研究鲜有报道,尤其是针对具体的无线电移动监测车,已知数据只有车的位置坐标和目标示向度情况,数学模型的建立还没有文献可供参考。在熟悉粒子滤波机理的基础上,参考粒子滤波在目标跟踪时建立数学模型的方法,结合无线电移动监测车对静止目标定位的实际需要,建立粒子滤波算法在静止目标定位时的数学模型,模型中融合分类和择优的措施以提高定位精度。最后在LabVIEW平台下对所建立的模型进行仿真实验,结果表明所建立的模型准确可行。     

Hazard perception as a function of target location and the field of view

A typical hazard perception test presents participants with a single-screen view of the road ahead. This study assessed how increasing this field of view would affect hazard perception abilities. Drivers were shown video clips of driving situations containing at least one hazard either on a single screen, or with the addition of side views on two separate but adjacent screens that extended the perceived worldview to approximately 180°. Mirror information was also included to allow information from behind the vehicle to be attended. Participants were instructed to press a button as soon as they saw a hazard. Faster response times were found for hazards that appeared in the centre of the central screen, than in the periphery of the central screen, with hazards that first appeared in the lateral screens responded to slowest. Additionally, responses to the hazards were faster and were more likely to occur in the three-, as compared to the single-screen condition. These results suggest that providing participants with a wider field of view, which includes more environmental cues that are related to the relevant hazardous situation increases their ability to detect hazards, and some limited support to that providing them with a wider view increases this ability even when all hazard-relevant information appear only in the central screen. A number of reasons for the three-screen advantage are discussed. This study suggests that even responses to central hazards may be under-estimated in a typical single-screen hazard perception test, and that improvements can be made for new hazard perception tests, by including visual information from the side and from behind the driver. This new methodology not only allows testing hazard perception skills in a potentially more immersive and realistic environment, but also enables to create hazard perception clips that cannot be realised in a typical single-screen test.     

Comparison of two methods of location of a target in devices with multi-element radiation detectors

Expressions for the statistical characteristics of devices with multi-element radiation detectors that make use of methods of target location through a determination of the centroids of the target and through scanning of the target are derived. A comparison of the precision of these methods is presented. __________ Translated from Izmeritel’naya Tekhnika, No. 12, pp. 31–33, December, 2005.     

Performance estimation for maximum-likelihood detection forchannels with transition noise

Transition noise is known to be a major cause of errors for high density magnetic recording. This noise is signal dependent and can be modeled as multiplicative noise in a linear channel model. A maximum-likelihood algorithm was considered for detection of signals in such noise. In this work, the performance of the detector, based on this algorithm, is compared to the traditional Viterbi algorithm (VA) and a modified Viterbi algorithm (MVA) by computer simulations. Results show an improvement of up to 5 dB In signal-to-noise-ratio (SNR) under typical conditions with a reasonable complexity     

Optimal position estimation for the automatic alignment of a high-energy laser

The alignment of high-energy laser beams for potential fusion experiments demands high precision and accuracy by the underlying positioning algorithms whether it be for actuator control or for monitoring the beam line for potential anomalies. The feasibility of employing on-line optimal position estimators in the form of model-based processors to achieve the desired results is examined. We discuss the modeling, the development, the implementation, and the processing of model-based processors applied to both simulated and actual beamline data.     

一种快速自适应噪声谱估计方法

提出了一种快速自适应的噪声谱估计方法。该方法在Doblinger和Cohen的噪声谱估计方法基础上,提出了改进算法,修正了带噪语音子带中语音存在的判断门限和噪声谱更新公式,估计的噪声谱既能快速适应背景噪声变化,又能保证准确性。实验结果表明,结合文中噪声谱估计方法构成的语音增强系统能有效抑制带噪语音中平稳和非平稳噪声,对于噪声突变的情况也适用。     

多级真空机组噪声源定位研究

机器噪声源定位是机器低噪声设计的基础.本文以真空行业广为使用的罗茨真空机组为对象,并在机组的周围对应各主要部位布置测点,利用声压法并逐级定位的方法,采用手持式精密噪声分析仪对各测点进行噪声测试分析,从而定位与排列噪声源,确定各主要部位对机组噪声贡献大小.在噪声贡献较大部位处再次细化并进行噪声测量,从而确定该部位各结构的噪声贡献大小并找出优势频率辐射产生的原因,为进一步进行多级真空机组噪声源机理研究和低噪声设计提供依据.     

Optimal suppression of quantization noise with pseudoperiodic multilevel phase gratings

A comprehensive two-step approach to design staircase-type multilevel diffractive phase elements (DPEs) that generate arbitrary desired diffraction patterns with the highest possible accuracy is presented. First a preliminary periodic grating with an unconstrained phase delay and an optimized nonuniform amplitude profile is designed by means of a customized iterative Fourier-transform algorithm. Then this preliminary grating is subjected to a phase quantization in which strict periodicity is forgone in favour of the best possible preservation of the shape of the power spectrum yielding a final phase only DPE with only rudimentary periodicity. An arbitrarily high similarity between the diffraction patterns of the final DPE and the preliminary grating can be achieved independently of the number D of discrete phase delay levels as long as D > or = 3. The signal-to-noise ratio of the final DPE is close to the theoretical upper limit. These properties are confirmed in computer simulations and demonstrated in optical experiments. Pseudoperiodic DPEs may have applications in optical computing, optical communication and networking, optical authentication, or coherent laser coupling.     

Minimum-mean-square-error filters for detecting a noisy target in background noise

A minimum-mean-square-error filter is proposed to detect a noisy target in spatially nonoverlapping background noise. In this model, both the background noise that is spatially nonoverlapping with the target and the noise that is additive to the target and the input image are considered. The criterion used to design the filter is to minimize the mean-square-error between the filter output and a delta function located at the target position in the presence of the noise. Computer-simulation results for a number of noisy input images are presented, and the performance of the filter is determined. We also test the filter discrimination against undesired objects and tolerance to target distortions, such as rotation and scaling.     

匹配滤波器中参考目标位置对相关峰位置的影响

针对利用光学相关器识别运动多目标的精确定位问题,提出了参考图像目标置中的匹配滤波器设计方法.该方法根据场景图像中目标位置、匹配滤波器中参考目标位置和相关峰位置之间的关系,采用将目标放置在参考图像中心以克服单一目标和运动多目标识别过程中相关峰的不确定偏移.实验结果表明,在范德卢格特型光电混合相关器中,采用该方法设计匹配滤波器可以使相关峰位置与目标位置一一对应,并且能够直观的实时显示出被识别目标在场景图像中的位置,提高了运动目标的定位准确性和跟踪稳定性.     

Waveform estimation with jitter noise using stochastic up and downmethod

Jitter noise exists, especially, when sampling high-frequency waveforms. This paper aims to address this problem through a stochastic method. By studying the stochastic up and down method in detail, we propose a “ratio indicator”, which can supplement the basic stochastic up and down method. Simulation results show that the proposed method gives good estimates with known error bounds     

Robust estimation of magnetic Barkhausen noise based on a numerical approach

This paper deals with a multifeature numerical instrument for nondestructive testing of ferromagnetic materials, based on the Barkhausen noise. Starting from traditional instruments based on the root mean square value of the band-pass filtered measured signal, the proposed method is based on the simultaneous analysis of the excitation voltage, the excitation current, and the induced signal. A good repeatability improvement is achieved by monitoring the excitation impedance, while synchronizing the rms evaluation to the excitation current signal increases the robustness with respect to the environmental electromagnetic noise. Moreover, experimental results encourage the use of shape-based features to better characterize the Barkhausen signal.