弹道目标进动周期特征提取新方法

中段弹道目标识别一直是反导作战中的技术难点,而弹道目标微动产生的微多普勒信号为雷达识别弹头和诱饵提供了一种新的途径。针对弹道目标的进动特性,建立了锥体弹头的进动微多普勒模型,引入了时频重排平滑伪Wigner-
Ville分布（RSPWVD）对锥体弹头的微多普勒信号进行了提取,仿真比较了Wigner-Ville分布（WVD）、平滑伪Wigner-Ville分布（SPWVD）和RSPWVD的提取结果,证明了RSPWVD在提取弹道目标微多普勒信号中的优越性,提出了一种基于微多普勒时频图的弹道目标进动周期特征提取新方法。仿真结果表明该方法具有很好的估计精度和抗噪性。     

基于“标准-3”动能拦截弹的顺轨拦截方法研究

提出了针对大气层外机动目标的顺轨拦截方法,能够大幅度降低目标与拦截器之间的相对速度,缓和拦截器的过载需求,避免脱靶现象。采用“标准-3”拦截弹的公开参数建立数学模型,对大气层外机动弹头的顺轨拦截过程进行了仿真研究,仿真综合考虑了助推器和拦截器的质量变化、末制导初始对准误差、导引头的测量误差和盲区、动力学系统的响应延迟和过载约束。结果表明,在处于速度劣势的情况下,拦截器能够对机动目标进行精准碰撞,验证了顺轨拦截方法的工程实践意义。     

城市建筑材质—地表温度关系的多源遥感研究

利用PROBA CHRIS遥感影像对北京城市建筑材质和自然地表进行基于光谱先验知识的分层分类提取,并与Landsat5 TM热红外数据反演得到的北京城市地表温度叠加,采用统计学方法定量分析了主要建筑材质、自然地类与地表温度的关系,并重点就不同建筑材质对城市热岛的影响及其表面特性所起作用进行了分析。结果表明：北京城区中的砖瓦房表面温度最高,比其他材质高0.3K~4.0K,比自然地类高5.1K~7.8K;金属结构表面温度略低;混凝土、水泥和沥青的平均温度相当,他们是城市热环境异常的主要来源之一;另外,城市中的玻璃幕墙能够有效地降低其表面温度,比其它材质低3.3K~4.0K。反照率、热惯量和热传导性是建筑材质影响城市地表温度的3个重要表面特性,对于不同材质,它们存在较大差异。     

基于虚拟现实的火炮外弹道仿真方法

针对火炮发射实验具有不可重复性、周期长、人力耗费大、技术要求高等问题,本文提出了火炮外弹道虚拟仿真方法.本文根据火炮射击过程特点,分析火炮质点外弹道方程组,建立弹丸外弹道运动过程数学模型;结合虚拟现实技术及Unity3D引擎,采用3ds Max建立火炮和弹丸实体模型,以C#作为开发语言对弹道进行计算,控制弹丸运动,实现对火炮发射过程的仿真模拟;通过仿真实验数据与弹道表数值分析比较表明,本方法不仅在视觉上能够较好的展现火炮发射和弹丸的飞行状态,同时误差控制在可接受范围内,为火炮外弹道的研究提供了便利.     

水声多诱饵对抗环境鱼雷导引方法

针对声诱饵对抗环境下,鱼雷常规的弹道导引方法难以兼顾对多个目标进行识别与打击要求,提出了多诱饵环境鱼雷导引方法基本框架,并基于人工势场提出多目标导引方法.该方法把目标似真概率和导引方向结合起来,使各目标在准确度未确定情况下对弹道的影响作用均能得以体现.首先依据各目标的概率确定牵引目标并计算出牵引关注度;进而,改进人工势场法的排斥因素,提出了吸引关注度概念,计算其他目标的吸引关注度及导引关注度;最后在机动能力限定下确定出鱼雷的角速度.静态靶桩仿真和运动目标仿真实验结果表明,该方法在保证对似真概率最大的目标进行打击的同时,能尽可能兼顾对多目标的探测识别,能显著提高水声多诱饵环境下目标打击的准确性.     

基于侧喷流控制的运载器弹道建模与仿真

直接侧向力技术已在大气层外动能拦截器和大气层内防空导弹中得到成功应用。运载火箭的飞行弹道跨越大气层,可以尝试采用直接侧向力对其进行控制。在介绍直接侧向力控制技术原理的基础上,建立了采用直接侧向力进行姿态控制的运载火箭弹道的简化模型（不考虑风干扰和弹体滚转）,运用Matlab／Simulink软件进行了计算机数字仿真,并与传统的摆动喷管控制方式进行了对比,给出了第一级弹道的仿真结果。得出了直接侧向力控制作用下的弹道能够满足运载器总体设计要求的结论。     

弹头初始再入点空间约束范围的研究

现在高速再入弹头通常具有末制导系统,在再人弹道设计过程中,再入弹头需要满足速度要求,并且在末端可能还需要满足一定的再人角限制,在实际飞行过程中,满足以上条件得出的最优制导律还要满足过载要求.这就使得弹头再入范围有一定的限制,尤其在起始时刻要满足过载要求,超过这个范围将使得弹头需用过载超过可用过载,从而达不到理想的最优制导过程.推导出满足以上条件最优制导律的弹头再入点的空间范围.仿真结果表明:满足以上空间范围的再入弹头按照最优制导律飞行,起始点过载满足要求.为设计弹道提供了一个再入时刻的范围参考.     

远程高速弹丸目标运动及红外辐射特性研究与应用

针对光学测量装备在远程高速弹丸目标跟踪测量过程中存在的跟踪测量难题,对弹丸目标的运动特性、红外辐射特性进行了研究分析,采用计算机仿真飞行弹道曲线、飞行表面温度随时间的变化曲线,得到给定条件下目标辐射度随时间的变化曲线,获得了满足试验测量需求的弹丸目标特性;通过仿真测量和半实物仿真测量等方式将研究成果应用于试验工程,在弹丸测量方案制定、装备跟踪性能评估等方面发挥重要作用,提高了试验成功率;研究成果可推广应用于其他类型目标的测试测量试验,具有较好的实用价值.     

基于Landsat ETM+遥感数据的组分温度反演方法研究

地表温度在干旱监测和模拟地表热通量中有重要作用。在干旱半干旱地区,双源能量平衡模型(TSEB)通常用于计算地表的热通量。以黑河中游典型灌区为研究区域,选取4个时相的Landsat-7 ETM+遥感影像,通过植被指数与TSEB模型结合的方法反演土壤表面温度和植被冠层温度,并重点讨论土壤表面温度和植被冠层温度的分解算法。结果表明:土壤表面温度和植被冠层温度具有较好的时空一致性;土壤表面温度与植被冠层温度的反演精度通过地表净辐射与地表热通量得到了间接验证。地表净辐射与地表热通量的计算值与观测值相关性好,相关系数大于0.92。地表净辐射与地表热通量的线性回归分析表明拟合精度高。通过地表温度分解的方法获得的土壤表面温度和植被冠层温度,对监测典型区域的干旱和模拟地表热通量是可行的。     

J2项摄动影响下的大气层外弹道规划改进算法

针对只限制飞行器始/终点位置和飞行时间两项约束条件的大气层外弹道规划问题,提出了一种考虑地球J_2项引力摄动的Lambert改进制导算法.根据经典Lambert制导理论确定中心力场假设条件下满足约束条件的标准弹道轨迹,然后与考虑地球扁率条件下的实际弹道轨迹相对比,得到基于轨道参数的弹道偏差解析解.通过设计一种计及J_2项引力摄动的虚拟目标点预测模型并补偿摄动偏差,将引力摄动影响下的轨道规划问题重新转化到二体理论Lambert制导下讨论.与现有的摄动修正方法相比较,考虑6个独立变量影响的预测模型修正算法能够全面完整地反应出轨道参数对于轨道偏差的影响.同时,基于椭圆轨道参数的预测模型具有鲁棒性强、计算精度高以及计算速度快等优点.     

Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model

Soil moisture plays an important role in surface energy balances, regional runoff, potential drought and crop yield. Early detection of potential drought or flood is important for the local government and people to take actions to protect their crop. Traditionally measurement of soil moisture is a time‐consuming job and only limited samples could be collected. Many problems would be results from extending those point measurements to 2D space, especially for a regional area with heterogeneous soil characteristics. The emergency of remote‐sensing technology makes it possible to rapidly monitor soil moisture on a regional scale. Thermal inertia represents the ability of a material to conduct and store heat, and in the context of planetary science, it is a measure of the subsurface's ability to store heat during the day and reradiate it during the night. One major application of thermal inertia is to monitor soil moisture. In this paper, a thermal inertia model was developed to be suitable in situations whether or not the satellite overpass time coincides with the local maximum and minimum temperature time. Besides, the sensibilities of thermal inertia with surface albedo and the surface temperature difference were discussed. It shows that the surface temperature difference has more effects on the thermal inertia than the surface albedo. When the temperature difference is less than 10 Kelvin degrees, 1 Kelvin degree error of temperature difference will lead to a big fluctuation of thermal inertia. When the temperature difference is more than 10 Kelvin degrees, 1 Kelvin degree error of temperature difference will cause a small change of thermal inertia. The temperature difference should be larger than 10 Kelvin degrees when the thermal inertia model is selected to derive soil moisture or other applications. Based on this thermal inertia model, the soil moisture map was obtained for North China Plain. It shows that the averaged difference between the soil moisture values derived from MODIS data and in situ measured soil moisture data is 4.32%. This model is promising for monitoring soil moisture on a large regional scale.     

Two-dimensional model variability in thermal inertia surveys

Calibration of thermal inertia surveys requires the production of a numerical model where thermal inertia is expressed as a function of the diurnal ground surface temperature range and albedo. The model is calculated for a given set of local meteorological and surface conditions which must be assumed constant over the whole of the surveyed area. This paper reports the results of an investigation which estimates the magnitudes of thermal inertia errors as a function of the departure of the local conditions from those assumed. The parameters under investigation are wind speed, average air temperature, air-temperature fluctuations, surface roughness, slope, and changes in the thermal inertia profile.     

Combining thermal inertia and a diurnal temperature difference cycle model to estimate thermal inertia from MSG-SEVIRI data

Thermal inertia is an important parameter in geological and agricultural applications. In this study, we present a method that combines models of thermal inertia and the diurnal temperature difference cycle to estimate the thermal inertia from Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) data. This method can directly derive thermal inertia from MSG-SEVIRI brightness temperatures without the need to include the land surface temperature and emissivity. Two important parameters (the time of the maximum temperature and the diurnal temperature difference) that were input into the thermal inertia model were obtained by fitting the diurnal temperature difference cycle model to the diurnal cycle of land surface temperatures. The spatial distribution of thermal inertia shows that high thermal inertia values occur over vegetated areas, whereas low thermal inertia values occur over bare areas. The uncertainty in thermal inertia is investigated in terms of the uncertainties in the surface albedo, the time of the maximum temperature, and the diurnal temperature difference. The results indicate that the uncertainty in thermal inertia over vegetated areas is greater than that over bare areas. The consistency of the thermal inertia model is evaluated by analysing the difference in thermal inertia values on two consecutive days. The root mean square error of the thermal inertia differences under nearly identical surface and atmospheric conditions on two consecutive days is considered to be the error of the thermal inertia model.     

基于信息增量的弹道目标协同跟踪方法

针对反导传感器网络中弹道目标的协同跟踪问题,提出了一种基于信息增量的弹道目标协同跟踪方法。分析了多传感器对弹道目标的协同跟踪问题,并建立了自由段弹道目标分段匀加速模型。在此基础上,对自由段弹道目标跟踪过程中,利用跟踪滤波的协方差阵信息获得每个传感器对目标的信息增量,并以信息增量最大为准则选择传感器对弹道目标进行跟踪,从而实现对弹道目标的有效跟踪。仿真结果表明：所提的方法能够及时动态地选择性能最佳的传感器对弹道目标进行跟踪,提高弹道目标整体的跟踪性能,实现对弹道目标的协同跟踪。     

证据理论与模糊函数相结合的弹道目标识别

以稳健性为原则,选定物理意义明确、提取难度较低、类别可分性强、特征值起伏度小的若干种特征进行弹道中段目标群的识别研究。通过建立各类特征的模糊隶属度函数,完成相应不同证据体的基本概率赋值。再利用重新定义的证据理论冲突系数,对冲突或较低可信度证据进行修正。最后,尝试将模糊函数与改进证据理论相结合的算法应用于弹道中段的目标识别,仿真结果表明该无监督模式识别方法能够可靠地识别出真实弹头,也更具有良好的泛化能力。     

Estimating surface temperatures from satellite thermal infrared data—A simple formulation for the atmospheric effect

In recent years the availability of high spatial resolution thermal infrared data from satellites has prompted the use of energy budget models relating satellite-derived surface temperatures to surface moisture, near-surface thermal inertia, energy exchange with the atmosphere, etc. However, correction of the high spatial resolution satellite data for atmospheric water vapor effects can represent a substantial computational burden unless simplifying assumptions are utilized. A simple formulation is developed and its applicability tested by application to standard meteorological soundings at a time near the overpass of an NOAA operational satellite. It appears that reasonable estimates of surface temperature (±2–3°C) are readily obtained for areas of order 100–300 km².     

Thermal inertia mapping over the Brahmaputra basin,India using NOAA-AVHRR data and its possible geological applications

Thermal inertia is a volume property and shows the resistance power of the material against changes in its temperature. The thermal inertia of a surficial feature of interest cannot be directly measured. Hence, a proper modelling is required for its estimation. The objective of the project is to develop a technique to generate thermal inertia images using available National Oceanic and Atmospheric Administration (NOAA) satellite data to detect thermal anomalies and oilfield signature over a known producing basin. The Brahmaputra valley in Upper Assam is selected for this study.

NOAA-Advanced Very High Resolution Radiometer (AVHRR) thermal data were converted to temperature, based on the look-up table (LUT) given in the NOAA-AVHRR CD and by using split-window atmospheric attenuation correction models. The thermal inertia imagery is constructed with the help of the albedo imagery generated from the daytime and with the knowledge of the surface temperature change between the daytime and night-time data. The thermal inertia values are computed for all pixels common to both daytime and night-time and the thermal inertia imagery generated for the study area. The thermal inertia of a surface cannot be measured directly; so another model is also used to estimate apparent thermal inertia (ATI). The images from both the models have shown similar results.

The geological map when draped over the ATI image shows good correlation of gross lithology and thermal inertia. The metamorphics/basement and the sediments are well differentiated by their tonal and textural characters. The Mikir massif shows conspicuously brighter signature than the featureless darker signatures of the surrounding valley. Within the valley, the river water exhibits bright tone, whereas the present-day sandbars within the river exhibit darker tone than the alluvial plains of the valley. This is in agreement with the available published data. Major thrusts can be mapped as bright linear tone, and their geometry coincides well with those mapped in the field. Exposed cross faults can also be mapped in Arunachal foothills and faults in Mikir massif. The isoneotectonic map when draped over the ATI image shows that the identified isoneotectonic units can be well differentiated in the image on the basis of tonal characters. The prominent lineaments mapped in Mikir massif can be traced in the valley part also.

The producing and dry structures in the valley show very few signatures on the thermal inertia images, possibly due to poor spectral and spatial resolution of the NOAA data. It is planned to use the developed technique to generate thermal inertia maps using higher spatial and spectral resolution satellite data (e.g. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)), which may provide better oilfield signatures.     

On the analysis of thermal infrared imagery: The limited utility of apparent thermal inertia

A spectral window in the thermal infrared permits observations of surface temperature by satellite radiometry. The Heat Capacity Mapping Mission (HCMM) acquired 10–12 μm data at times of day favorable for estimation of surface thermal properties and the surface energy budget. Two variables, surface wetness, which controls evaporation and hence mean surface temperature, and thermal inertia, which relates the diurnal excursion of surface temperature to ground heat flux, are responsible for most observed temperature variability. These variables may be estimated from the mid night (2:30 a.m.) and early afternoon (1:30 p.m.) data from the HCMM or from the afternoon NOAA satellites. However, the HCMM data product, “apparent thermal inertia,” is potentially misleading in agricultural areas because surface evaporation reduces the amplitude of the soil heat flux compared to the amplitude in dry areas. Thus apparent thermal inertia should not be used in regions having variability in surface moisture.     

Advanced thermal inertia modelling

This paper presents a simple and operational thermal inertia model by using the phase angle information of the diurnal temperature change. The model which is developed in this paper is based on our first-order approximation operational thermal inertia model. We use a second-order approximation for the boundary conditions and a second-order approximation for the surface temperature series expression. The importance of this work is that from our model real thermal inertia (as distinct from apparent thermal inertia) can be computed directly. The model requires only one field measurement parameter for the calculation of real thermal inertia; this is the time of maximum temperature in the daytime and this parameter is easily obtained from a meteorological station. For the regions having vegetative cover, the thermal inertia value is the weighted thermal inertia values of vegetated cover and soil ground.