An Adjoint-Free CNOP–4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation

This paper proposes a hybrid method, called CNOP–4 DVar, for the identification of sensitive areas in targeted observations, which takes the advantages of both the conditional nonlinear optimal perturbation(CNOP) and four-dimensional variational assimilation(4 DVar) methods. The proposed CNOP–4 DVar method is capable of capturing the most sensitive initial perturbation(IP), which causes the greatest perturbation growth at the time of verification;it can also identify sensitive areas by evaluating their assimilation effects for eliminating the most sensitive IP. To alleviate the dependence of the CNOP–4 DVar method on the adjoint model, which is inherited from the adjoint-based approach, we utilized two adjointfree methods, NLS-CNOP and NLS-4 DVar, to solve the CNOP and 4 DVar sub-problems, respectively. A comprehensive performance evaluation for the proposed CNOP–4 DVar method and its comparison with the CNOP and CNOP–ensemble transform Kalman filter(ETKF) methods based on 10 000 observing system simulation experiments on the shallow-water equation model are also provided. The experimental results show that the proposed CNOP–4 DVar method performs better than the CNOP–ETKF method and substantially better than the CNOP method.

METHOD OF MULTI-TARGET TRACKING IN WIDE AREA SURVEILLANCE AIRBORNE RADAR SYSTEM BASING ON CLUSTERING ANALYSIS

This paper proposed a robust method based on the definition of Mahalanobis distance to track ground moving target. The feature and the geometry of airborne ground moving target tracking systems are studied at first. Based on this feature, the assignment relation of time-nearby target is calculated via Mahalanobis distance, and then the corresponding transformation formula is deduced. The simulation results show the correctness and effectiveness of the proposed method.

Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model

With the Regional Ocean Modeling System(ROMS),this paper investigates the sensitive areas in targeted observation for predicting the Kuroshio large meander(LM)path using the conditional nonlinear optimal perturbation approach.To identify the sensitive areas,the optimal initial errors(OIEs)featuring the largest nonlinear evolution in the LM prediction are first calculated;the resulting OIEs are localized mainly in the upper 2500 m over the LM upstream region,and their spatial structure has certain similarities with that of the optimal triggering perturbation.Based on this spatial structure,the sensitive areas are successfully identified,located southeast of Kyushu in the region(29°–32°N,131°–134°E).A series of sensitivity experiments indicate that both the positions and the spatial structure of initial errors have important effects on the LM prediction,verifying the validity of the sensitive areas.Then,the effect of targeted observation in the sensitive areas is evaluated through observing system simulation experiments.When targeted observation is implemented in the identified sensitive areas,the prediction errors are effectively reduced,and the prediction skill of the LM event is improved significantly.This provides scientific guidance for ocean observations related to enhancing the prediction skill of the LM event.

Average Damage Caused by Multiple Weapons against an Area Target of Normally Distributed Elements

This paper investigates the effect of launching multiple weapons against an area target of normally distributed elements. We provide an analytical form of the average damage fraction and then apply it to obtain optimal aimpoints. To facilitate the computational efforts in practice, we also consider optimizations over given constrained patterns of aimpoints. Finally, we derive scaling laws for optimal aimpoints and optimal damage fraction with respect to the radius of the area target.

Exploring sensitive area in the tropical Indian Ocean for El Niño prediction: implication for targeted observation

Based on initial errors of sea temperature in the tropical Indian Ocean that are most likely to induce spring predictability barrier(SPB)for the El Niño prediction,the sensitive area of sea temperature in the tropical Indian Ocean for El Niño prediction starting from January is identified using the CESM1.0.3(Community Earth System Model),a fully coupled global climate model.The sensitive area locates mainly in the subsurface of eastern Indian Ocean.The effectiveness of applying targeted observation in the sensitive area is also evaluated in an attempt to improve the El Niño prediction skill.The results of sensitivity experiments indicate that if initial errors exist only in the tropical Indian Ocean,applying targeted observation in the sensitive area in the Indian Ocean can significantly improve the El Niño prediction.In particular,for SPB-related El Niño events,when initial errors of sea temperature exist both in the tropical Indian Ocean and the Pacific Ocean,which is much closer to the realistic predictions,if targeted observations are conducted in the sensitive area of tropical Pacific,the prediction skills of SPB-related El Niño events can be improved by 20.3%in general.Moreover,if targeted observations are conducted in the sensitive area of tropical Indian Ocean in addition,the improvement of prediction skill can be increased by 25.2%.Considering the volume of sensitive area in the tropical Indian Ocean is about 1/3 of that in the tropical Pacific Ocean,the prediction skill improvement per cubic kilometer in the sensitive area of tropical Indian Ocean is competitive to that of the tropical Pacific Ocean.Additional to the sensitive area of the tropical Pacific Ocean,sensitive area of the tropical Indian Ocean is also a very effective and cost-saving area for the application of targeted observations to improve El Niño forecast skills.

Identification of the sensitive area for targeted observation to improve vertical thermal structure prediction in summer in the Yellow Sea

The sensitive area of targeted observations for short-term(7 d)prediction of vertical thermal structure(VTS)in summer in the Yellow Sea was investigated.We applied the Conditional Nonlinear Optimal Perturbation(CNOP)method and an adjoint-free algorithm with the Regional Ocean Modeling System(ROMS).We used vertical integration of CNOP-type temperature errors to locate the sensitive areas,where reduction of initial errors is expected to yield the greatest improvement in VTS prediction for the selected verification area.The identified sensitive areas were northeast−southwest orientated northeast to the verification area,which were possibly related to the southwestward background currents.Then,we performed a series of sensitivity experiments to evaluate the effectiveness of the identified sensitive areas.Results show that initial errors in the identified sensitive areas had the greatest negative effect on VTS prediction in the verification area compared to errors in other areas(e.g.,the verification area and areas to its east and northeast).Moreover,removal of initial errors through deploying simulated observations in the identified sensitive areas led to more refined prediction than correction of initial conditions in the verification area itself.Our results suggest that implementation of targeted observation in the CNOP-based sensitive areas is an effective method to improve short-term prediction of VTS in summer in the Yellow Sea.

A quantitative method for calculating irradiation area of laser target designator

In laser-guided bomb attacking process,the target indication from the laser target designator is the premise for the bomb to hit the target accurately.Considering the lack of quantitative study of the irradiation area of the laser target designator,this paper,based on the existing aircraft motion model and the laser transmission model,uses two aircraft as respectively the carrier of the laser-guided bomb and the carrier of the laser designator and proposes a method to calculate the global irradiation area of the airborne laser designator.By using the proposed algorithm,the global irradiation area when attacking a large flat target or a large spherical target is simulated respectively.Finally,according to the simulation results,the influences of different factors on the shapes of the irradiation area are discussed in detail.

Land Use Regionalization in Poor Counties in Mountainous Areas Based on Targeted Poverty Alleviation

Land use regionalization is a strategic measure for the rational use,management and protection of land resources based on local conditions.Based on the needs of targeted poverty alleviation and rural revitalization strategy and the analysis on the natural and socioeconomic conditions,characteristics of land resources,and the current status of land use in Luquan County,corresponding regionalization indices were selected from four aspects:economic environment conditions,socioeconomic conditions,land resources and land use structure,and poverty alleviation and development level,a scientific and feasible index system for land use regionalization was constructed,and land use in Luquan County was regionalized by using systematic cluster analysis method.The results show that the 16 townships(towns)of Luquan County were divided into four land use regions,poverty alleviation region for development of new town and characteristic industries in the southwest(I),agricultural development and ecological poverty alleviation region in central mountainous area(II),poverty alleviation region for development of characteristic agriculture and tourism towns in eastern plateau mountainous area(III),and poverty alleviation region for development of characteristic industries and protection of land economy in the northern alpine valley area(IV).In addition,suggestions were put forward for the rational use of land in each region.

Genetic model and exploration target area of geothermal resources in Hongtang Area, Xiamen, China

The geothermal resources in Fujian Province are mainly hydrothermal resources of medium-low temperature.To better understand the whole process and conditions of heat control in the middle and deep crust,this study focuses on the analysis of heat accumulation model in Hongtang Area of Xiamen,and the main conditions of the model such as faults and sags are explored and interpreted in detail by using gravity and wide-field electromagnetic methods.4 main faults(F33,F2,F12 and HT-F1)and 10 secondary faults(HT-F2,HT-F3,HT-F4,HT-F5,HT-F6,HT-F7,HT-F8,HT-F9,HT-F10 and HT-F11)were inferred,and the distribution range of sags was delineated.The convective geothermal system is composed of four components:Heat source,geothermal reservoir,heat-conductive fault and heat retaining cover,which form a quaternary heat accumulation model.According to the model,the intersection of the main faults F12,HTF1 and F33 can be delineated as the primary target area of geothermal exploration,while the intersection of the secondary faults(F12 and HT-F6;F12 and HT-F2;HT-F9,HT-F10 and F12;F12 and HT-F11;F33 and HT-F3;HT-F8 and HT-F3;HT-F2,HT-F10 and HT-F1)can be delineated as the secondary target area.Borehole DR01,which is located in the primary target area,shows that the water temperature increases from fast to slow in the depth range of 0–500 m,and stays at 36℃below 500 m.The reliability of the heat accumulation model and the target area was tested via geothermal boreholes,which is of great significance to the exploitation and utilization of geothermal resources in Hongtang Area of Xiamen.

Delineation of Prospecting Prospect Area Based on Maximum Entropy Model

Taking the Dapingzhang copper-polymetallic deposit in Yunnan Province, China as the research object, the maximum entropy model was used to extract the mining information, and the mineral resource prediction model was established by using the exploration data of the deposit and related regions in this area, so as to determine the prospecting prospect area in the study area. In this paper, the Jacknife analysis module of maximum entropy model is used to quantitatively rank the importance of 39 geochemical element variables, and finally obtain the prospecting prospect map of the study area. The research results show that the Dapingzhang mining area has the potential to find hidden ore in the deep and surrounding areas, and the northern and southern ends and western sides of the rock ore control structural belt in the eastern region of the mining area have good prospecting prospects. The research results provide an important basis for the deployment of follow-up exploration work in the study area, and the maximum entropy model has a good application effect in mineral resources exploration.

经CT扫描探讨正常喉的活动度的研究

目的通过对喉部活动度进行测量,进一步精确勾画喉外扩靶区,以实现肿瘤精确放疗提高放疗效果。方法选取51例肿瘤患者为研究对象,通过CT测量喉部在四个方向最大活动度,通过spss23.0对实验所得数据进行统计分析。结果51位研究对象平均前联合向上最大移动范围为(13.04±6.72)mm,前联合向下最大移动范围为(1.53±2.41)mm,前联合向左最大移动范围为(1.44±1.74)mm,前联合向右最大移动范围为(1.35±2.27)mm,前联合向前最大移动范围为(3.81±2.74)mm,前联合向后最大移动范围为(0.75±1.59)mm,左侧甲状软骨板最大外移为(0.70±1.21)mm,左侧甲状软骨板最大内移为(1.86±2.85)mm,右侧甲状软骨板最大外移为(0.70±1.35)mm,右侧甲状软骨板最大内移为(1.42±1.71)mm,杓前角最大间距为(14.15±3.51)mm。以第一次测量为准确测量值,第二次、第三次测量值与第一次测量值差值绝对值为误差值,比较两次测量误差值。两次测量误差间差异无统计学意义(P>0.05)。≤60岁研究对象与>60岁研究对象的喉部活动度无显著性差异(P>0.05)。男性杓前角最大间距为(15.32±4.72)mm,显著高于女性的(12.14±1.61)mm,差异具有统计学意义(P<0.05)。转移的研究对象左侧甲状软骨板最大内移为(2.36±2.11)mm,显著高于未转移的(1.19±1.73)mm,差异具体统计学意义(P<0.05)。性别与前联合向上最大移动范围、杓前角最大间距呈现显著负相关(P<0.05),与左侧甲状软骨板最大外移呈显著正相关(P<0.05);年龄与前联合向上最大移动范围呈显著正相关(P<0.05),与前联合向下最大移动范围、左侧甲状软骨板最大外移呈显著负相关(P<0.05)。皮尔逊相关性分析发现甲状软骨板前联合向左移动度与左侧甲状软骨板最大外移具有显著正相关性(r=0.301,P=0.032);甲状软骨板前联合向右移动度与右侧甲状软骨板最大外移具有显著正相关性(r=0.072,P=0.000)。结论自然吞咽会引起喉部运动,这种运动的具体范围在肿瘤放射治疗中需被注意。

基于Transformer复杂运动辨识的机动星凸形扩展目标跟踪方法

针对复杂的机动扩展目标跟踪问题,利用Transformer网络设计了一种有效的星凸不规则形状机动扩展目标跟踪方法。首先,该文研究利用alpha-shape算法建立了星凸形状的变化模型,实现了静态场景下的星凸形扩展目标的形状估计。然后,通过对目标状态转移矩阵进行重新设计,结合Transformer网络对机动扩展目标运动状态转移矩阵进行实时估计,实现了对复杂机动目标运动过程的精准跟踪。进一步地,将估计得到的形状轮廓与运动状态进行融合,最终实现了对星凸形机动扩展目标的实时跟踪。最后,通过构造复杂的机动扩展目标跟踪场景,利用多重性能指标测试算法对形状和运动状态的综合估计性能,验证了算法的有效性。

贵州5个产地五倍子蜂蜜组分差异分析

本研究采用非靶向代谢组学方法对贵州5个产地五倍子蜂蜜组分进行分析,探讨不同产地五倍子蜂蜜组分差异。结果共鉴定出100种物质组分,且均检测到核黄素和光色素。聚类结果显示,不同产地五倍子蜂蜜的组分差异明显,贵阳和开阳五倍子蜂蜜聚为一个组别,息烽、桐梓和凤冈五倍子蜂蜜为一个组别。5个产地中筛选出27种差异组分,包括10种氨基酸类和6种有机酸类组分。L-缬氨酸、L-天冬氨酸、L-苯丙氨酸等药效氨基酸在贵阳和开阳产地显著富集(P<0.05)。筛选到myo-肌醇为开阳五倍子蜂蜜标志物,对氨基苯甲酸为桐梓五倍子蜂蜜标志物,磷酸胆碱、L-高苯丙氨酸为凤冈五倍子蜂蜜标志物。本研究可为五倍子蜂蜜真假判别、产地溯源及特色五倍子蜂蜜开发提供参考。

冀北上黄旗地区多金属矿成矿规律与矿产预测

冀北上黄旗地区位于华北地台北缘中段成矿带及兴安太行南段成矿带的相交区域,是华北地区著名的(银)多金属成矿区。本文在综合分析区域成矿地质背景、成矿地质条件、地球物理、地球化学、遥感异常特征及成矿规律的基础上,认为该区具有寻找侵入岩型和陆相火山岩型两大类多金属矿床的有利条件,划分出3条Ⅳ级成矿亚带,圈定成矿远景区10个。其中,A类4处,B类4处,C类2处;并优选出多金属矿找矿靶区7个,A类4个,B类2个,C类1个。

基于毫米波雷达的非视距目标探测和定位方法研究

隐蔽非直视目标探测和定位技术在城市巷战、安防、防暴等领域具有广泛的应用。本文针对L形非视距区域内单目标的探测与定位问题进行研究。首先,对雷达布设位置及可探测区域进行了分析;其次,针对共同可探测区域,设计了多路径联合检测器;最后,基于设计的多径雷达应用系统,利用所提检测定位方法进行实验验证。与现有研究相比,本文的创新点在于:在L形非视距场景下,对宽波束毫米波雷达布设位置及可探测区域进行分析并给出合理建议;其次利用所提多路径联合检测器将不同反射面的多条路径联合使用,提高了检测性能。本文通过实验验证了系统的可靠性及雷达位置对可探测区域的影响,通过仿真与实验探究了所提检测器的性能改善。

基于MR混合现实的足球机器人目标跟踪仿真

机器人跟踪足球时,由于目标具有较强的运动随机性,且较小的目标尺度增大了跟踪框的自适应跟踪难度,目标跟踪时会将很多背景信息包含在内,导致目标模型的更新错误。为此,提出基于MR混合现实的足球机器人目标跟踪方法。构建MR混合现实平台,令足球机器人在虚拟现实场景下完成人机交互,在保证目标跟踪安全性的同时提升目标跟踪性能;采用帧差法获取目标模型,利用投影法对二值图像投影,并对差分图像滤波,以此获取足球机器人在目标模板区域及候选目标区域中的直方图。基于此,更新足球机器人目标模型,实现基于MR混合现实的足球机器人目标跟踪。实验结果表明,当跟踪误差阈值为0.8mm时,研究方法的目标跟踪准确率和成功率均可达95%以上,平均耗时为55.17ms。当足球目标出现遮挡问题时,该方法仍能完成高精度跟踪。

利用局部特征匹配的运动小目标光流估计

基于深度光流估计的动态背景运动小目标检测,为了保证小目标的检测性能,一般采用较少的下采样次数以维持较高的分辨率,但由此带来了较大的计算耗时。特征匹配是深度光流估计的一个核心处理环节,其耗时在光流估计整体耗时中的占比较大,且对下采样次数非常敏感。据此,提出一种基于局部特征匹配的快速光流估计算法:引入目标运动信息,缩小特征匹配的空间范围,减少待处理的数据量;设计分块局部匹配策略,引入批处理机制,避免出现逐点局部匹配策略数据处理耗时过大问题,实现算法加速。在此基础上,在光流估计获取的光流场上,采用CenterNet网络检测运动目标对应的光流异常区域。从光流估计耗时、检测精度等方面开展了实验验证,结果表明:针对运动小目标检测,分块特征匹配光流估计比全局特征匹配光流估计耗时减少约25%,目标检测性能相当。

采动含水层生态功能修复:概念内涵、理论与技术框架

针对我国保水采煤研究现状及煤矿区采损生态修复的技术需求,提出应开展采动含水层生态功能修复研究,并将其纳入绿色开采技术体系中。在充分阐述采动含水层生态功能修复概念与内涵的基础上,构建了以采动含水层失水流动规律及水径流阻隔关键技术为主的理论与技术框架,分析了当前相关研究进展与未来攻关方向。含水层的损伤失水与生态功能退化本质源于采煤引起的岩层运动与裂隙发育,应在充分掌握含水层失水机制与规律的基础上对其开展生态功能修复理论与技术研究。深入揭示含水层失水路径分布与水流动力耗散规律,将失水流量集中分布的采动影响区作为重点修复的靶区,合理运用“边采边修”、“采后再修”等方式实施水流通道封堵与修复。同时,应充分利用采动岩体裂隙自修复机制及其引起的含水层自恢复效应,开展采动含水层生态功能引导修复研究与实践;基于水-气-岩相互作用产生化学沉淀促进导水裂隙自修复的降渗机理,提出了向含水层下方裂隙岩体中灌注可与地下水产生化学沉淀的修复试剂,以诱导沉淀物在裂隙中吸附-固结并封堵通道的含水层生态功能修复技术路径。在此基础上,阐述了利用铁/钙质化学沉淀进行导水裂隙修复降渗的研究现状,提出未来应重点研究形成利于不同类型导水通道高效封堵的化学沉淀诱导生成对策。研究可望为西北部生态脆弱矿区煤炭开采地下水保护与生态修复提供参考。

多视觉传感器协同弱小目标检测

多视觉传感器协同对空实现全区域覆盖的弱小目标检测,在近距离防空领域中具有重要意义。现有的全区域覆盖方法存在覆盖率低、随机性差等问题,弱小目标检测算法存在模型大、定位及分类准确性低等问题。提出了一种高效的对空全区域覆盖算法和轻量级弱小目标检测算法,通过结合最大面积优先法和最小曼哈顿离法改善存在覆盖死角和随机性差等问题。提出密集通道扩展网络(dense and channel expand network,DCENet)模型,基于轻量级稠密拼接和自适应尺寸通道扩展方法,在弱小目标数据集上获得了比原算法更有竞争力的平均精度结果。

松辽盆地中央坳陷及邻区三维地热地质建模与地热资源靶区优选

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