SPACEBORNE SAR REAL-TIME ECHO SIMULATION PLATFORM BASED ON VPX

To perform the ground test of a spaceborne Synthetic Aperture Radar(SAR) system, an echo simulator with the characteristics of multimode, multi-assemblage, and real time is proposed in this paper. A hardware platform of the real-time echo simulator based on the VPX bus is designed. With this platform, real-time multi-point echo generation and scenario targets echo generation can be achieved by the real-time signal processing in Field Programmable Gate Array(FPGA), utilizing the parameters calculated by the industry computers. Furthermore, this platform can output different signals if it is expanded to multi-channels, making it possible for the assignment of echo generation and test in different spaceborne SAR modes. The test results with the actual SAR system show that this platform can satisfy the system requirements and is now used in practice.

Investigation of three-pulse photon echo in thick crystal using finite-difference time-domain method

This paper investigates the phenomenon of three-pulse photon echo in thick rare-earth ions doped crystal whose thickness is far larger than 0.002 cm which is adopted in previous works.The influence of thickness on the three-pulse photon echo＇s amplitude and efficiency is analyzed with the Maxwell-Bloch equations solved by finite-difference timedomain method.We demonstrate that the amplitude of three-pulse echo will increase with the increasing of thickness and the optimum thickness to generate three-pulse photon echo is 0.3 cm for Tm^（3＋）：YAG when the attenuation of the input pulse is taken into account.Meanwhile,we find the expression 0.09 exp（α＇L）,which is previously employed to describe the relationship between echo＇s efficiency and thickness,should be modified as 1.3 · 0.09 exp（2.4 ·α＇L） with the propagation of echo considered.

Study on Echo Time-Delay Estimation of Pulsed Laser Fuze

Pulse laser range detector is to measure the distance by estimating the time delay between the emitting pulse and echo pulse.In this paper,a mathematical model for the target echo signal of laser fuze has been established;in accordance with this model,the formulas for echo time-delay estimation and for amplitude estimation based on least squares criterion have been deduced.It is argued and simulated that the resolution of echo time-delay estimation could be improved through multi-reference correlation approach.Experiments illustrate that the approach enables pulsed laser fuze to perform high-precision ranging under a low signal-to-noise ratio condition.

Impacts of space-time-frequency synchronization errors onwide-band target echo characteristics of bistatic/multistatic radar

Bistatic/multistatic radar has great potential advantages over its monostatic counterpart. However, the separation of a transmitter and a receiver leads to difficulties in locating the target position accurately and guaranteeing space-timefrequency synchronization of the transmitter and the receiver.The error model of space-time-frequency synchronization in a motion platform of bistatic/multistatic radar is studied. The relationship between the space synchronization error and the transmitter platform position, receiver platform position, moving state, and beam pointing error, is analyzed. The effect of space synchronization error on target echo power is studied. The target scattering characteristics are restructured by many separate scattering centers of the target in high frequency regions. Based on the scattering centers model of the radar target, this radar target echo model and the simulation method are discussed. The algorithm of bistatic/multistatic radar target echo accurately reflects the scattering characteristics of the radar target, pulse modulation speciality of radar transmitting signals, and spacetime-frequency synchronization error characteristics between the transmitter station and the receiver station. The simulation of bistatic radar is completed in computer, and the results of the simulation validate the feasibility of the method.

A Prediction Method Based on Improved Echo State Network for COVID-19 Nonlinear Time Series

This paper proposes a prediction method based on improved Echo State Network for COVID-19 nonlinear time series, which improves the Echo State Network from the reservoir topology and the output weight matrix, and adopt the ABC (Artificial Bee Colony) algorithm based on crossover and crowding strategy to optimize the parameters. Finally, the proposed method is simulated and the results show that it has stronger prediction ability for COVID-19 nonlinear time series.

Assessment the Optimal Effect of Time of Repetition: Extrinsic Pulse Parameter on Gd-DTPA Enhanced, Spin-Echo T1-Weighted MR Images under Low Magnetic Field Strength

The contrast agent concentration, the time of repetition (TR) and magnetic field strength are significant parameters that influence for the accurate signal intensity (SI) in quantitative Magnetic Resonance Imaging (MRI). Therefore, this study was conducted to investigate and refine the dependence and the optimal effect of Time of Repetition (TR) on the relationship between signal intensity and Gd-DTPA (Gadolinium-diethylene-triaminepenta-acetic acid) concentration, after applying two-dimensional (2D) Spin Echo (SE) pulse sequence under low-field MRI. In addition to that, the optimal concentration of Gd-DTPA at given sequence parameters at low-field MRI was also evaluated. A water-filled phantom was constructed for a range of Gd-DTPA concentrations (0 - 6 mmol/L) and the mean signal intensities (SIs) were assessed in the defined region of interest on T1-weighted images with different TR values (40 - 2000 ms). The generated signal-concentration curves for Gd-DTPA revealed that increasing TR was associated with the increase of the overall SIs and the maximum relationship between SI to concentration. Moreover, the required Gd-DTPA concentration to produce the maximum SI was associated to decrease with the increase of TR. In addition to this, the application of beyond 100 ms TR values in this study with relatively higher concentrations (beyond 1 - 2 mmol/L) has resulted predominantly non-linear patterns in the signal-concentration curves and it appears the saturation or decay of the SIs due to T2 effect. From these results, it can be suggested that the selection of relatively lower Gd-DTPA concentration ( mmol/L) with less than 800 ms (<800 ms) TR values can produce a better linear relationship between the concertation and SIs in T1-weighted SE low field contrast-enhanced MRI. Furthermore, this study also outlined the significance and necessity of the optimization of TR in SE sequence in low field MRI prior to a particular examination.

基于Echoview声学数据后处理系统的背景噪声扣除方法

基于2012年2～3月南海中部鱼类资源声学调查资料,利用Echoview系统中虚拟变量模块的功能,探讨扣除背景噪声对声学映像、单脉冲回声信号图、海里面积散射系数（NASC）和体积反向散射强度（Sv）的影响.结果显示,背景噪声对120kHz数据的干扰明显强于38kHz;随着水深逐渐增加,扣除背景噪声后,120kHz声学映像变化亦比38kHz更加明显;扣除背景噪声时,换能器表面1 m处的Sv值在不断改变过程中,相同水层中不同频率数据的NASC和Sv的变化差异明显,其差异程度因具体水层而异,相同频率数据在不同水层的NASC和Sv的变化差异亦明显.分析认为,扣除背景噪声非常必要;本研究的方法能够较好地排除背景噪声,是提高资源评估准确度的有效手段.

基于互信息和Just-in-Time优化的回声状态网络

为了提高回声状态网络(ESN)的适应性,提出基于互信息(MI)和Just-in-Time(JIT)的优化方法,对ESN的输入伸缩参数以及输出层进行优化,所得网络称为MI-JIT-ESN.ESN的优化方法分为两部分:一是基于网络输入与输出之间的互信息,对网络的多个输入伸缩参数进行调整;二是基于JIT优化的局部输出层,对ESN的隐层输出数据进行局部重新建模,从而提升ESN输出层的回归拟合精度.将MI-JIT-ESN应用于青霉素补料分批发酵过程建模.结果显示,MI-JIT优化方法能提高模型的适应性,并优于其他比较方法.

超短回波时间序列在肺功能成像的应用进展

近几年来,超短回波时间(ultrashort echo time,UTE)序列弥补了先前的空白,在肺实质结构的评估方面逐步应用,适于新生儿和儿童肺部疾病形态学变化的纵向随访。但MRI的突出优势之一是功能成像,通过将UTE序列与肺功能MRI(包括超极化气体、灌注和氧增强造影)相结合,进行定量功能测定,利用固有配准图像显示支气管扩张、粘液堵塞、肺纤维化和空气潴留后的肺部功能,对改善限制性和阻塞性肺部疾病的诊断和预后具有潜在价值。本文综述了UTE序列肺部结构及功能成像的研究进展,揭示了该序列的技术原理和应用优势,旨在为未来进一步探索UTE序列在肺部疾病的应用提供参考。

时间依赖扩散MRI在胶质瘤中的研究进展

时间依赖扩散MRI(TDD-MRI)是一种新型扩散加权成像(DWI)技术,主要通过振荡梯度自旋回波(OGSE)序列并与多种数字模型结合来获得细胞密度、细胞直径(d)、细胞内体积分数(Vin)和细胞外扩散系数(Dex)等参数。其可用于胶质瘤的组织学分级预测、基因学与微观结构评估、疗效评估、鉴别诊断等。简要介绍TDD-MRI的基本原理,并对其在胶质瘤术前评估和疗效监测中的研究进展作一综述。

结合高斯噪声的回声状态网络模型及其时间序列预测性能

为了模拟回声状态网络模型在时间序列预测实例中的影响因素,在回声状态网络模型的储备池层引入高斯噪声,构建结合高斯噪声的回声状态网络模型;利用公式推导分析所提模型的非线性性质;采用股票序列数据与Logistic混沌序列数据进行实验验证和对比分析。结果表明,本文所提模型的预测效果优于回声状态网络模型、压缩感知回声状态网络模型和反向传播神经网络模型,股票收盘价预测、Logistic混沌序列预测的平均绝对误差均最小,分别为1.33×10^(-3)、5.21×10^(-4)。

Extraction of Echo Characteristics of Underwater Target Based on Cepstrum Method

The analysis and characteristic extraction of target echo characteristics are important in underwater target detection and recognition. Rigid acoustic scattering components are generally used as major echo contributors with relatively stable characteristic information. Previous studies focus on echo characteristics from a single angle, thereby limiting the amount of extracted characteristic information. This paper aims to establish a full-angle rigid echo components model and overcome the difficulty of the extraction of time delay characteristics of narrow-band acoustic scattering echoes. On the basis of the analysis of the target echo highlight model, the echo characteristics of rigid acoustic scattering components are extracted in the cepstrum domain, and a wavelet process is proposed to enhance the effect of time delay estimation. Experimental data indicate that the extracted time delay characteristics accord with the rigid echo characteristics of underwater target, thereby validating the effectiveness of the cepstrum method.

Characteristic Analysis of Underwater Acoustic Scattering Echoes in the Wavelet Transform Domain

Underwater acoustic scattering echoes have time–space structures and are aliasing in time and frequency domains. Different series of echoes properties are not identified when incident angle is unknown. This article investigates variations in target echoes of monostatic sonar to address this problem. The mother wavelet with similar structures has been proposed on the basis of preprocessing signal waveform using matched filter, and the theoretical expressions between delay factor and incident angle are derived in the wavelet domain. Analysis of simulation data and experimental results in free-field pool show that this method can effectively separate geometrical scattering components of target echoes. The time delay estimation obtained from geometrical echoes at a single angle is consistent with target geometrical features, which provides a basis for object recognition without angle information. The findings provide valuable insights for analyzing elastic scattering echoes in actual ocean environment.

Adaptive and optimal detection of elastic object scattering with single-channel monostatic iterative time reversal

In active sonar operation, the presence of background reverberation and the low signal-to-noise ratio hinder the detection of targets. This paper investigates the application of single-channel monostatic iterative time reversal to mitigate the difficulties by exploiting the resonances of the target. Theoretical analysis indicates that the iterative process will adaptively lead echoes to converge to a narrowband signal corresponding to a scattering object＇s dominant resonance mode, thus optimising the return level. The experiments in detection of targets in free field and near a planar interface have been performed. The results illustrate the feasibility of the method.

Novel Real-Time System for Traffic Flow Classification and Prediction

Traffic flow prediction has been applied into many wireless communication applications(e.g., smart city, Internet of Things). With the development of wireless communication technologies and artificial intelligence, how to design a system for real-time traffic flow prediction and receive high accuracy of prediction are urgent problems for both researchers and equipment suppliers. This paper presents a novel real-time system for traffic flow prediction. Different from the single algorithm for traffic flow prediction, our novel system firstly utilizes dynamic time wrapping to judge whether traffic flow data has regularity,realizing traffic flow data classification. After traffic flow data classification, we respectively make use of XGBoost and wavelet transform-echo state network to predict traffic flow data according to their regularity. Moreover, in order to realize real-time classification and prediction, we apply Spark/Hadoop computing platform to process large amounts of traffic data. Numerical results show that the proposed novel system has better performance and higher accuracy than other schemes.

The Long-Lived Photon Echo Response Locking Effect in the Presence of External Non-Resonant Laser Pulses with a Different Spatial Orientation

The correlation of the inhomogeneous broadening of the resonance transition at different time intervals and the efficiency of long-lived photon echo response locking by the action of standing waves of non-resonant laser pulses are considered. It is shown that the long-lived photon echo response locking effect may be observed even at the angles of the relative orientation of the non-resonant standing wave laser pulses of less than one degree, due to the change in the correlation coefficient of inhomogeneous broadening at time intervals between the first and the second and after the third resonant laser pulses.

Comparative Analysis of Two Short-time Strong Precipitation Processes

By means of conceptual model prediction, two short-time strong precipitation processes in Xiamen on June 12th and 14th, 2008 were analyzed from the aspects of real precipitation, weather situation, physical parameter and radar echo. The results showed that two short-time strong precipitation processes had complete different weather backgrounds, so physical quantities which could reflect atmospheric thermal and dynamic characteristic were different, as well as the characteristic and evolution process of radar echo, and it revealed that two short-time strong precipitation processes in Xiamen had various formation mechanisms and evolution processes. Therefore, many data should be combined to grasp different vantage points in precipitation forecast.

四川两次极端暴雨强降水特征及与雷达回波和闪电关系分析

选取了2020年8月四川两次历史性极端暴雨过程,根据量级和持续时间对强降水进行划分,分析其时空分布特征及与雷达回波和闪电的关系。结果表明:短时强降水主要发生在22时—次日03时,降水强度为30~<50 mm/h的站次最多,区域集中在盆地西部。随着降水量级的增加,站点对应的闪电密度均增大,小时平均回波、最强回波、最弱回波均呈增强的趋势。随着降水持续时间的增加,站点对应的负地闪平均强度增强。第一次过程强降水站次与闪电频次的高值中心具有良好的对应关系。第二次过程随着降水量级增大,对应的回波均方根误差减小,而第一次过程则相反。

偏置剪枝叠式自编码回声状态网络的时序预测

针对大多数模型对时间序列预测数据的预测准确率较低,为提升时间序列的预测精度,提出一种基于Biased Drop-weight的偏置剪枝叠式自编码回声状态网络(BD-AE-SGESN)的深度模型。以叠式ESN为多层深度网络框架,提出一种生成式AE算法生成每一层的输入权值,利用BD算法根据输入权重激活值进行剪枝。对比实验结果表明,该模型能够有效提升预测准确率,在3个不同的数据上,相比其它模型有着较小的预测误差和较高的稳定度。

磁共振成像三维双回波稳态联合三维短时反转恢复快速自旋回波成像序列对臂丛神经损伤的诊断价值

目的 探讨磁共振神经成像(magnetic resonance neuroimaging,MRN)三维双回波稳态(3D dual-echo steady state,3D-DESS)序列联合三维短时反转恢复快速自旋回波成像(3D short time inversion recovery spin echo imaging,3D-STIRSPACE)序列在臂丛神经损伤(brachial plexus injury,BPI)诊断的应用价值。方法 回顾性分析59例疑似BPI患者的MRN资料,所有患者均行3D-DESS和3D-STIR-SPACE序列扫描。分析BPI的MRN图像特征,比较各序列图像对臂丛神经的显示情况、臂丛神经背景组织抑制评分和图像对比度噪声比(contrast to noise ratio,CNR);对比3D-DESS序列、3D-STIR-SPACE序列及其联合应用对BPI的诊断效能。结果 3D-DESS序列扫描显示损伤神经呈稍高信号,增强扫描显示损伤神经呈等信号;3DSTIR-SPACE序列扫描显示损伤神经呈高信号,增强扫描显示损伤神经及周围软组织信号增高。3D-STIR-SPACE序列的臂丛神经的神经显示评分、背景组织抑制评分和CNR均高于3D-DESS序列(P<0.05)。不同序列及联合应用诊断BPI的敏感度、准确度比较,差异具有统计学意义(P<0.05)。联合应用3D-DESS和3D-STIR-SPACE序列诊断的敏感度、准确度均高于3D-DESS序列(P<0.05)。结论 MRN是临床诊断BPI的重要影像学手段,3D-STIR-SPACE序列可较好抑制周围背景信号、清晰显示臂丛神经。联合应用3D-DESS和3D-STIR-SPACE序列扫描可提高3D-DESS诊断BPI的敏感度与准确度。