计算机在测风气象雷达中的应用

阐述了应用计算机对测风气象雷达进行故障自动测试，以提高雷达的可靠性和可维性。应用计算机对探测数据进行自动处理和对雷达进行控制，以提高雷达的探测精度和计算精度，计算速度，满足气象部门快速探测的要求。     

大气波导对岸基警戒雷达影响研究

通过分析2009年～2011年的大气波导环境数据,从理论上阐述了岸基雷达产生超视距探测的必要条件,对岸基雷达超视距探测现象进行了分类.首先,比较了两种典型的对流层内雷达波传播衰减计算方法,得出基于分阶傅里叶算法和抛物线方程法的混合模型算法更适合计算大气波导环境中雷达波能量的空间分布;然后,使用该模型计算了两类超视距现象在探测距离、测距精度、测向精度及探测效果方面的差异;最后,提出了利用雷达超视距探测的建议.     

基于定位设备的雷达精度评估系统设计

针对常规地面雷达主要参数精度指标要求，考虑到目前广泛使用的多种定位设备不同的数据接口，设计了一种雷达精度评估系统。该系统通过整合多种定位设备的数据接口关系，对多种类别定位数据利用人机交互方式提取并进行归一化处理，形成统一的精度评估数据文件；再采用基于数据文件的数据处理方式，利用GJB 74A—1998规定的雷达精度等指标计算方法，得到雷达各主要参数的精度指标和比较直观的显示结果，不仅方便了雷达系统误差校准，而且为更好地验证、比较数据处理算法的精度提供了有效手段。     

多波段共面天线的研究

跟踪测量雷达因其精度要求,波束宽度很窄。为实现雷达自引导功能,本文介绍了一种跟踪测量雷达的多频段共面的天线技术,重点对共面天线设计、组合馈源设计以及双频段自引导概率计算进行了论述,并给出了一些设计实例和仿真计算结果。结果表明:多频段天线的应用完全可用一部雷达取代两部或两部以上的雷达。     

用于MSSR系统的测量精度和分辨力分析计算

介绍了一种用于MSSR系统测量精度和分辨力的分析方法，详细阐述了某单脉冲SSR雷达的精度和分辨力的计算方法，并给出了一些具体的计算结果。     

噪声对Chirp-Z变换的LFMCW系统测距算法的影响

本文介绍了用Chirp-Z变换提高液位测量精度的算法原理,然后仿真出线性调频连续波雷达(LFMCW)在快速傅里叶变换(FFT)和线性调频Z变换(CZT)给回波信号加一定噪声后的测距精度,同时分析并比较了两种测距方法对测距精度造成的影响。理论计算和数字仿真结果表明,Chirp-Z算法可显著提高计算效率和液面雷达的测距精度。     

基于高精度运动信息的ISAR分辨率评估方法

ISAR分辨率评估是空间目标成像雷达精度鉴定的重要内容.该文针对ISAR分辨率评估中的基准计算与方法设计两个关键问题进行了详细分析,进而提出了基于空间目标高精度轨道与遥测姿态等运动信息的ISAR方位向定标方法.在此基础上,建立了一种新的ISAR分辨率评估方法.利用某雷达精度鉴定试验中对不同空间目标的实测成像数据,验证了该文方法的合理性与有效性.     

基于高精度运动信息的ISAR分辨率评估方法

ISAR分辨率评估是空间目标成像雷达精度鉴定的重要内容。该文针对ISAR分辨率评估中的基准计算与方法设计两个关键问题进行了详细分析,进而提出了基于空间目标高精度轨道与遥测姿态等运动信息的ISAR方位向定标方法。在此基础上,建立了一种新的ISAR分辨率评估方法。利用某雷达精度鉴定试验中对不同空间目标的实测成像数据,验证了该文方法的合理性与有效性。     

火控跟踪雷达系统精度分析

对于控制武器的高精度跟踪雷达,影响测角、测距精度的因素很多,分析计算复杂,本文从实际工程设计考虑,提出了影响雷达精度的主要因素和一套分析计算方法。通过对某雷达的精度系统性的分析计算,明确了控制雷达精度与雷达参数设计的关系。     

雷达发展中的几个主要问题

本文扼要地叙述了雷达发展中的几个主要问题。在增远作用距离方面,重点讨论了理想接收机的定义,提出了理想度系数的概念,即实际接收机输出的信噪比和理想接收机输出信噪比的此较,作为评价一切雷达接收系统的标准;计算了理想雷达的极限接收能力;讨论了实现理想接收机的主要困难;指出雷达体制发展的基本方向是高占空系数雷达体制、最佳信息处理雷达体制和多波束分集体制。 在提高抗干扰能力方面,综合分析了各种干扰的性质和目标的特性,提出了抗干扰的三种体制:抑止干扰体制,测定干扰体制及反侦察体制。定义了抗干扰度,作为评价各种抗干扰方法的标准,对现有各种抗干扰的方法作了简要分析。干扰现阶段是向综合干扰发展,所以雷达也必须具有综合抗干扰能力。扰干扰体制的发展是多波段,快速变频,匹配滤波的联合应用,和目标特性的综合分析。而各种体制的适当结合,同时使用,就可以使雷达具有极好的扰干扰能力。 在提高测定座标精度方面,讨论了测角误差的分析和综合,提出了总误差的定义,作为评价雷达精度的标准。计算了雷达的理想精度。论述了提高精度的几个方面及最佳传输函数的含义。对现有各种改进伺服系统方法作了简评。指出提高精度方向是采用新体制,测定目标偏离雷达轴线的瞬时位置和改进伺服系统。     

Multiple classifiers applied to multisource remote sensing data

The combination of multisource remote sensing and geographic data is believed to offer improved accuracies in land cover classification. For such classification, the conventional parametric statistical classifiers, which have been applied successfully in remote sensing for the last two decades, are not appropriate, since a convenient multivariate statistical model does not exist for the data. In this paper, several single and multiple classifiers, that are appropriate for the classification of multisource remote sensing and geographic data are considered. The focus is on multiple classifiers: bagging algorithms, boosting algorithms, and consensus-theoretic classifiers. These multiple classifiers have different characteristics. The performance of the algorithms in terms of accuracies is compared for two multisource remote sensing and geographic datasets. In the experiments, the multiple classifiers outperform the single classifiers in terms of overall accuracies.     

双频激光测长的气象测试精度

使用双频激光干涉仪测长时，必须对测量环境的气象条件进行修正，才能得到准确的测量结果。分析了由于采用不同精度的气象参数测试仪器给测量结果带来的影响。提出了根据使用的双频激光干涉仪精度，合理地选择相应精度气象参数测试仪器的原则和方法。     

单站外辐射源定位误差分析与仿真优化

建立了外辐射源单站定位的几何模型,给出了测量目标参数(方位角、到达时间差、基线距离、多普勒频移)的主要方法,分析了影响目标参数观测精度的相关因素。比较两种典型定位算法的几何定位精度,并利用子集优选策略改善算法性能,在不同观测精度和位置关系的条件下,进行仿真实验。实验结果表明,各算法的定位精度与目标观测精度和几何位置有关,而对于改善后的定位算法,使得大部分区域内的目标定位精度提高了50%,并减少了目标定位盲区。     

Hybrid consensus theoretic classification

Hybrid classification methods based on consensus from several data sources are considered. Each data source is at first treated separately and modeled using statistical methods. Then weighting mechanisms are used to control the influence of each data source in the combined classification. The weights are optimized in order to improve the combined classification accuracies. Both linear and nonlinear optimization methods are considered and used in classification of two multisource remote sensing and geographic data sets. A nonlinear method which utilizes a neural network gives excellent experimental results. The hybrid statistical/neural method outperforms all other methods in terms of test accuracies in the experiments     

基于光谱维小波特征的混合像元投影迭代分解

混合像元线性分解是高光谱遥感应用的关键技术之一.本文利用小波变换多分辨率分析的特点,提出了一种以小波低频系数为特征的混合像元投影迭代分解的方法.首先利用离散二进小波提取了高光谱影像特征,再基于影像特征,用投影迭代方法自动确定出端元光谱,并以限制性的最小二乘方法估计出混合像元的组分.实验结果表明,本文方法能够较大的提高遥感影像混合像元的分解精度.     

Level Set Hyperspectral Image Classification Using Best Band Analysis

We present a supervised hyperspectral classification procedure consisting of an initial distance-based segmentation method that uses best band analysis (BBA), followed by a level set enhancement that forces localized region homogeneity. The proposed method is tested on two hyperspectral images of an urban and rural nature. The proposed method is compared to the maximum likelihood (ML) method using BBA. Quantitative results are compared using segmentation and classification accuracies. Results show that both the initial classification using BBA features and the level set enhancement produced high-quality ground cover maps and outperformed the ML method, as well as previous studies by the authors. For example, with the compact airborne spectrographic imager image, the ML method resulted in accuracies les95.5%, whereas the level set segmentation approach resulted in accuracies as high as 99.7%.     

The establishment of reliability model for LED lamps

In order to verify which of the distributions and established methods of reliability model are more suitable for the analysis of the accelerated aging of LED lamp, three established methods (approximate method, analytical method and two-stage method) of reliability model are used to analyze the experimental data under the condition of the Weibull distribution and Lognormal distribution, in this paper. Ten LED lamps are selected for the accelerated aging experiment and the luminous fluxes are measured at an accelerated aging temperature. AIC information criterion is adopted in the evaluation of the models. The results show that the accuracies of the analytical method and the two-stage method are higher than that of the approximation method, with the widths of confidence intervals of unknown parameters of the reliability model being the smallest for the two-stage method. In a comparison between the two types of distributions, the accuracies are nearly identical.     

Precise tracking of remote sensing satellites with the GlobalPositioning System

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the TOPEX/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes     

Multiexpert automatic speech recognition using acoustic and myoelectric signals

Classification accuracy of conventional automatic speech recognition (ASR) systems can decrease dramatically under acoustically noisy conditions. To improve classification accuracy and increase system robustness a multiexpert ASR system is implemented. In this system, acoustic speech information is supplemented with information from facial myoelectric signals (MES). A new method of combining experts, known as the plausibility method, is employed to combine an acoustic ASR expert and a MES ASR expert. The plausibility method of combining multiple experts, which is based on the mathematical framework of evidence theory, is compared to the Borda count and score-based methods of combination. Acoustic and facial MES data were collected from 5 subjects, using a 10-word vocabulary across an 18-dB range of acoustic noise. As expected the performance of an acoustic expert decreases with increasing acoustic noise; classification accuracies of the acoustic ASR expert are as low as 11.5%. The effect of noise is significantly reduced with the addition of the MES ASR expert. Classification accuracies remain above 78.8% across the 18-dB range of acoustic noise, when the plausibility method is used to combine the opinions of multiple experts. In addition, the plausibility method produced classification accuracies higher than any individual expert at all noise levels, as well as the highest classification accuracies, except at the 9-dB noise level. Using the Borda count and score-based multiexpert systems, classification accuracies are improved relative to the acoustic ASR expert but are as low as 51.5% and 59.5%, respectively.     

Myoelectric signal classification for phoneme-based speech recognition

Traditional acoustic speech recognition accuracies have been shown to deteriorate in highly noisy environments. A secondary information source is exploited using surface myoelectric signals (MES) collected from facial articulatory muscles during speech. Words are classified at the phoneme level using a hidden Markov model (HMM) classifier. Acoustic and MES data was collected while the words "zero" through "nine" were spoken. An acoustic expert classified the 18 formative phonemes in low noise levels [signal-to-noise ratio (SNR) of 17.5 dB] with an accuracy of 99%, but deteriorated to approximately 38% under simulations with SNR approaching 0 dB. A fused acoustic-myoelectric multiexpert system, without knowledge of SNR, improved on acoustic classification results at all noise levels. A multiexpert system, incorporating SNR information, obtained accuracies of 99% at low noise levels while maintaining accuracies above 94% during low SNR (0 dB) simulations. Results improve on previous full word MES speech recognition accuracies by almost 10%.