Ocean bottom profiling with ambient noise: a model for the passive fathometer

A model is presented for the complete passive fathometer response to ocean surface noise, interfering discrete noise sources, and locally uncorrelated noise in an ideal waveguide. The leading order term of the ocean surface noise contribution produces the cross-correlation of vertical multipaths and yields the depth of sub-bottom reflectors. Discrete noise incident on the array via multipaths give multiple peaks in the fathometer response. These peaks may obscure the sub-bottom reflections but can be attenuated with use of minimum variance distortionless response (MVDR) steering vectors. The seabed critical angle introduces discontinuities in the spatial distribution of distant surface noise and may introduce spurious peaks in the passive fathometer response. These peaks can be attenuated by beamforming within a bandwidth limited by the array geometry and critical angle.     

Coherent averaging of the passive fathometer response using short correlation time

The passive fathometer algorithm was applied to data from two drifting array experiments in the Mediterranean, Boundary 2003 and 2004. The passive fathometer response was computed with correlation times from 0.34 to 90 s and, for correlation times less than a few seconds, the observed signal-to-noise ratio (SNR) agrees with a 1D model of SNR of the passive fathometer response in an ideal waveguide. In the 2004 experiment, the fathometer response showed the array depth varied periodically with an amplitude of 1 m and a period of 7 s consistent with wave driven motion of the array. This introduced a destructive interference, which prevents the SNR growing with increasing correlation time. A peak-tracking algorithm applied to the fathometer response of experimental data was used to remove this motion allowing the coherent passive fathometer response to be averaged over several minutes without destructive interference. Multirate adaptive beamforming, using 90 s correlation time to form adaptive steer vectors which were applied to 0.34 s data snapshots, increases the SNR of the passive fathometer response.     

Passive fathometer processing

Ocean acoustic noise can be processed efficiently to extract Green's function information between two receivers. By using noise array-processing techniques, it has been demonstrated that a passive array can be used as a fathometer [Siderius, et al., J. Acoust. Soc. Am. 120, 1315-1323 (2006)]. Here, this approach is derived in both frequency and time domains and the output corresponds to the reflection sequence. From this reflection sequence, it is possible to extract seabed layering. In the ocean waveguide, most of the energy is horizontally propagating, whereas the bottom information is contained in the vertically propagating noise. Extracting the seabed information requires a dense array, since the resolution of the bottom layer is about half the array spacing. If velocity sensors are used instead of pressure sensors, the array spacing requirement can be relaxed and simulations show that just one vertical velocity sensor is sufficient.     

Time and direction of arrival detection and filtering for imaging in strongly scattering random media

We study detection and imaging of small reflectors in heavy clutter, using an array of transducers that emits and receives sound waves. Heavy clutter means that multiple scattering of the waves in the heterogeneous host medium is strong and overwhelms the arrivals from the small reflectors. Building on the adaptive time-frequency filter of [Borcea et al, SIIMS 2011;4(3)], we propose a robust method for detecting the direction of arrival of the direct echoes from the small reflectors, and suppressing the unwanted clutter backscatter. This improves the resolution of imaging. We illustrate the performance of the method with realistic numerical simulations in a non-destructive testing setup.     

FEEDFORWARD ADAPTIVE CONTROL OF FLEXURAL VIBRATION IN A BEAM USING WAVE AMPLITUDES

This paper concerns the real-time estimation of wave amplitudes and their subsequent use as a cost function in adaptive active control of bending vibrations in a beam. The amplitude of the wave propagating downstream from the control location is estimated by filtering the outputs of an array of sensors. Minimizing this wave amplitude has significant advantages over the more conventional approach in which velocity at some point is minimized. Expressions for the ideal frequency responses of the wave filters are found for the case of an array comprising two sensors in the far field. These filters are non-causal. FIR implementations designed using direct and time-delay methods are described, the latter offering some substantial advantages. Practical performance considerations are discussed, including filter length, frequency range, effects of near fields, group delays, accuracy and cross-sensitivity. Simulations and experimental measurements are performed and compared.     

一种结合粒子滤波和张量子空间的目标跟踪算法

由于传统的子空间方法易于丢失图像目标的二维特性,为此本文提出了一种新颖的自适应目标跟踪算法,通过张量的方式建立目标的外观模型——张量子空间,利用在线学习的方法更新其外观模型,同时,利用目标仿射运动的先验信息,通过粒子滤波自适应地跟踪运动目标,并将获得的最优目标观测作为新数据反馈回子空间更新.此外,为了保证子空间更新能获得精确且紧致的目标子空间表达,引入动态部分函数滤除样本野点.实验结果表明,本文提出的自适应目标跟踪方法具有较强的鲁棒性,对于存在姿态变化、短时遮挡和光照变化等情况下均可有效地跟踪目标.     

Joint tracking algorithm using particle filter and mean shift with target model updating

Roughly, visual tracking algorithms can be divided into two main classes: deterministic tracking and stochastic tracking. Mean shift and particle filter are their typical representatives, respectively. Recently,a hybrid tracker, seamlessly integrating the respective advantages of mean shift and particle filter (MSPF)has achieved impressive success in robust tracking. The pivot of MSPF is to sample fewer particles using particle filter and then those particles are shifted to their respective local maximum of target searching space by mean shift. MSPF not only can greatly reduce the number of particles that particle filter required, but can remedy the deficiency of mean shift. Unfortunately, due to its inherent principle, MSPF is restricted to those applications with little changes of the target model. To make MSPF more flexible and robust, an adaptive target model is extended to MSPF in this paper. Experimental results show that MSPF with target model updating can robustly track the target through the whole sequences regardless of the change of target model.     

Wide-field-of-view narrow-band spectral filters based on photonic crystal nanocavities

We describe a novel approach to implementing wide-field-of-view narrow-band spectral filters, using an array of resonant nanocavities consisting of periodic defects in a two-dimensional three-material photonic-crystal nanostructure. We analyze the transmissivity of this type of filter for a range of wavelengths and in-plane incidence angles as a function of the defect's refractive index, the number of layers in the photonic-crystal reflectors, and the period of the defects and find that this structure diminishes the angular sensitivity of the resonance condition relative to that of a standard multilayer filter.     

An adaptive threshold filter for ultrasound signal rejection

The threshold filter is a frequently used technique in ultrasound B-scan to reject the small echoes contributed from backscattering that blur the tissue interface and reduce the image contrast. Note that using the threshold based on one value would simultaneously destroy local waveform features of the reflection echoes with amplitudes larger than threshold value. To resolve this problem, we developed an adaptive threshold filter based on the noise-assisted empirical mode decomposition (EMD). Computer simulations at 7.5 MHz using a single-element transducer with a bandwidth of 60% and a pulselength of 0.5 μs were carried out to explore the feasibility of the algorithm. Image measurements on the carotid artery using a 7.5 MHz, 128 elements, 1D linear array transducer with the same characteristics as those in simulations were used to verify the performance of the algorithm in practice. Compared to the result from the conventional threshold technique, the adaptive threshold filter is able to successfully suppress the smaller backscattering signals without changing the local waveform features of the preserved significant echoes due to refection.     

基于双层金属光栅的中波红外多通道滤光片结构

提出一种多通道平面窄带滤光片阵列结构,该结构由双层金属光栅及其两侧的分布式布拉格反射器（DBRs）组成。所设计的多通道滤光片中心波长范围超过200 nm,每一个通道的中心波长可以通过调节光栅狭缝宽度来调节,从而实现多通道窄带滤光阵列。该结果为中波红外多通道窄带滤光片的设计提供了一条新的路径。     

非均匀随机散射介质层的多次散射和热辐射的分层迭代解

为纳入矢量辐射传输方程的多次散射，将非均匀平行分层分布的随机散射介质划分成多个薄 层，利用各薄层的低阶Mueller矩阵解推导出整层的高阶散射迭代解.用这一方法计算了具有 占空比、粒子大小和温度廓线非均匀分布的平行分层随机密集球形粒子积雪层的极化热辐射 .数值结果与一层均匀随机散射层的离散坐标-特征值方法作了比较，讨论了多次散射和热辐 射与散射层各特征参数的关系，与积雪层微波遥感数据进行了对比. 关键词： VRT方程 平行分层 高阶散射解 迭代解     

一种基于特征提取的相关跟踪算法

介绍了一种能稳定快速跟踪复杂背景下目标的算法,该算法在传统相关跟踪算法的基础上进行改进.当目标进入红外(电视)摄像机视场时,视频信号中包含有目标信息和背景信息,信号处理器先将此信号进行数字化处理,形成具有一定灰度等级的数字化图像阵列,然后采用边缘检测、阈值分割等算法对包含有目标信息的图像进行边缘处理,提取出具有特征的目...     

Track-before-detect algorithm for maneuvering infrared weak multiple targets via particle filter

We present a particle filter （PF）-based algorithm to detect and track maneuvering infrared weak multiple targets at different signal-to-noise ratios for the scenes with the multiple targets number unknown and vary- ing. A detecting filter and a tracking filter based on sequential likelihood ratio （LR） testing with fixed sample size are designed, respectively, for capturing new target and tracking confirmed targets. The algorithm is optimized with selectively particles sampling and adaptive process noise. Targets birth and death time are accurately estimated according to the change degree of the LR along with the corresponding state amended through PF backward recursion. Simulation results show that it is positive to detect and track maneuvering infrared weak multiple targets with the appearance and disappearance of more than one, which also achieves a significant improvement in state estimation especially for the time targets which appear and disappear.     

基于AGPF的滚动轴承性能衰退趋势预测

针对粒子滤波算法中粒子退化和计算复杂度问题,提出了一种自适应遗传粒子滤波(AGPF)算法。该算法采用遗传算法代替传统粒子滤波中的重采样方法,并根据粒子数与滤波误差方差之间的关系,自适应调节滤波过程中的粒子数。通过预测滚动轴承的性能衰退趋势,对该方法进行验证,结果表明,AGPF算法能够在保证预测精度的条件下,减少滤波粒子数,更加适用于滚动轴承的性能衰退趋势预测。     

一种基于忆阻交叉阵列的自适应三高斯模型及其在图像增强中的应用

在视觉图像处理中,可用三高斯模型来模拟视网膜神经节细胞的感受野,这可以在一定程度上对图像信息,比如图像的边缘、细节等信息进行增强.但是在对大量的图像进行处理时,为了达到比较理想的效果,就需要人为地来改变模型中的相关参数,这是一个十分耗时的过程.基于此,本文提出一种基于忆阻交叉阵列的自适应三高斯模型.这种模型是在传统三高斯模型的基础上,根据所需处理图像的局部特征,利用忆阻交叉阵列的特性动态地改变模型参数,以达到对局部图像最优增强的目的,从而使整幅图像的增强效果更好.首先,根据图像的局部亮度信息来确定忆阻器所需施加的脉冲电压的极性以及宽度;然后,根据所得忆阻值得到对应模型中参数的值;最后,可以得到局部增强模板,从而实现增强.本文分别选取了彩色和灰度图像进行了测试,定性和定量实验结果均表明,这种改进的三高斯模型不仅能够对图像边缘进行有效的增强,而且还可以极大地提高图像的对比度和清晰度,为忆阻器在图像处理方面的应用提供了新方向.     

基于改进雁群PSO算法的模糊自适应扩展卡尔曼滤波的SLAM算法

针对扩展卡尔曼滤波同时定位与地图创建算法中难以建立准确的先验噪声模型的问题, 提出一种基于改进雁群粒子群算法的模糊自适应卡尔曼滤波算法. 利用分数阶微积分改进粒子进化速度, 利用混沌来改进粒子的初始化和发生早熟时的处理. 改进后的雁群粒子群算法在收敛速度与避免早熟方面有了很大改进, 并将改进的雁群粒子群算法用于模糊自适应扩展卡尔曼滤波同时定位与地图创建算法的训练, 并与用雁群粒子群算法训练的模糊自适应扩展卡尔曼滤波同时定位与地图创建算法进行对比, 其在定位与构图方面有很大的提高. 关键词： 同时定位与地图创建 雁群粒子群算法 分数阶微积分 混沌     

Sequential Bayesian geoacoustic inversion for mobile and compact source-receiver configuration

Geoacoustic characterization of wide areas through inversion requires easily deployable configurations including free-drifting platforms, underwater gliders and autonomous vehicles, typically performing repeated transmissions during their course. In this paper, the inverse problem is formulated as sequential Bayesian filtering to take advantage of repeated transmission measurements. Nonlinear Kalman filters implement a random-walk model for geometry and environment and an acoustic propagation code in the measurement model. Data from MREA/BP07 sea trials are tested consisting of multitone and frequency-modulated signals (bands: 0.25-0.8 and 0.8-1.6 kHz) received on a shallow vertical array of four hydrophones 5-m spaced drifting over 0.7-1.6 km range. Space- and time-coherent processing are applied to the respective signal types. Kalman filter outputs are compared to a sequence of global optimizations performed independently on each received signal. For both signal types, the sequential approach is more accurate but also more efficient. Due to frequency diversity, the processing of modulated signals produces a more stable tracking. Although an extended Kalman filter provides comparable estimates of the tracked parameters, the ensemble Kalman filter is necessary to properly assess uncertainty. In spite of mild range dependence and simplified bottom model, all tracked geoacoustic parameters are consistent with high-resolution seismic profiling, core logging P-wave velocity, and previous inversion results with fixed geometries.     

Kalman filter-based microphone array signal processing using the equivalent source model

This paper demonstrates that microphone array signal processing can be implemented by using adaptive model-based filtering approaches. Nearfield and farfield sound propagation models are formulated into state-space forms in light of the Equivalent Source Method (ESM). In the model, the unknown source amplitudes of the virtual sources are adaptively estimated by using Kalman filters (KFs). The nearfield array aimed at noise source identification is based on a Multiple-Input–Multiple-Output (MIMO) state-space model with minimal realization, whereas the farfield array technique aimed at speech quality enhancement is based on a Single-Input–Multiple-Output (SIMO) state-space model. Performance of the nearfield array is evaluated in terms of relative error of the velocity reconstructed on the actual source surface. Numerical simulations for the nearfield array were conducted with a baffled planar piston source. From the error metric, the proposed KF algorithm proved effective in identifying noise sources. Objective simulations and subjective experiments are undertaken to validate the proposed farfield arrays in comparison with two conventional methods. The results of objective tests indicated that the farfield arrays significantly enhanced the speech quality and word recognition rate. The results of subjective tests post-processed with the analysis of variance (ANOVA) and a post-hoc Fisher's least significant difference (LSD) test have shown great promise in the KF-based microphone array signal processing techniques.     

Modified particle filter-based infrared pedestrian tracking

Tracking infrared pedestrian targets is a crucial part in video surveillance. Many factors make this problem decidedly non-linear and non-Gaussian, and the appropriate solution at present is based on the particle filter technique which is powerful and simple to implement. But in many cases, the traditional particle filter tracking algorithm fails to track the targets robustly and accurately. To solve these problems, a modified particle filter algorithm that combines intensity and edge cues is proposed. The algorithm firstly extracts the intensity cue and edge cue of the target based on the visual models which are originally learnt from the first frame and will be updated during the tracking process according to an automatic model updating strategy. Secondly, these two cues are combined into the particle filter framework by an adaptive integration scheme. Furthermore, its performance is evaluated with real-world infrared pedestrian sequences and extensive experimental results show that the presented method can track the infrared pedestrian more effectively and reliably than the traditional particle filter algorithm.     

水中目标窄带噪声识别的听觉外周模型

为解决听觉外周模型特征在具有工程背景的水中目标声信号分类研究中识别率下降问题,提出了一种外周模型Gammatone滤波器组修正方法,获得的窄带噪声特征可明显提高水中目标识别性能。首先,分析了识别率下降原因,发现声学工程应用中多通道数据采集,导致信号频率范围变窄,而引起声信号的时频特征发生变化。其次,根据听觉模型用Gammatone滤波器组模拟人耳基底膜频率分解特性、低频信息包含水中目标噪声信号的重要类别特征,对原有的听觉模型特征进行插值,对滤波器组的通道数与中心频率进行适应性修正,得到目标噪声在较窄频带的27维特征,修正后的模型能够更精细地反映出目标时频特性。最后,采用神经网络分类器进行实验。结果表明,修正后的听觉模型保留了原较宽频带特征的主要信息,而且进一步提高了对实际目标的分类能力,识别率由原来的82.59%提高到88.80%。本文提出根据工程应用平台的有效接收频带优化听觉外周模型Gammatone滤波器组的设计,采用阵元级的多通道数据进行分析,侧重于工程应用,解决了多通道数据采集中,由于频带变窄,导致信号的特征信息量下降,进而引起声特征识别性能下降的问题,修正后的听觉模型特征,有效地提高水中目标辐射噪声的识别效果。本文对从事无源声呐目标识别、有源声呐目标识别、带宽受限的多通道声数据采集的时频特性分析研究人员具有一定的参考价值。