Adaptive Cascaded High-Resolution Source Localization Based on Collaboration of Multi-UAVs

Effective information fusion is very important in hybrid source localization. In this paper, the performance analysis of conventional joint direction of arrival(DOA) and time difference of arrival(TDOA) system is derived and it is shown that this hybrid system may inferior to the single system when the ratio of angular measurements error to distance measurements error exceeds a threshold. To avoid this problem, an effective DOA/TDOA adaptive cascaded(DTAC) technique is presented. The rotation feature of UAVs and spatial filtering technique are applied to gain the signal-to-noise ratio(SNR), which leads to more accurate estimation of time delay by using DOAs. Nevertheless, the time delay estimation precision is still limited by the sampling frequency, which is constrained by the finite load of UAV. To break through the limitation, an enhanced self-delay-compensation(SDC) method is proposed, which aims at detecting the overlooked time delay within the sampling interval by adding a tiny time delay. Finally, the position of the source is estimated by the Chan algorithm. Compared to DOA-only algorithm, TDOA-only algorithm and joint DOA/TDOA(JDT) algorithm, the proposed method shows better localization accuracy regardless of different SNRs and sampling frequencies. Numerical simulations are presented to validate the effectiveness and robustness of the proposed algorithm.

Robust Source Localization in Shallow Water Based on Vector Optimization

Owing to the multipath effect, the source localization in shallow water has been an area of active interest. However, most methods for source localization in shallow water are sensitive to the assumed model of the underwater environment and have poor robustness against the underwater channel uncertainty, which limit their further application in practical engineering. In this paper, a new method of source localization in shallow water, based on vector optimization concept, is described, which is highly robust against environmental factors affecting the localization, such as the channel depth, the bottom reflection coefficients, and so on. Through constructing the uncertainty set of the source vector errors and extracting the multi-path sound rays from the sea surface and bottom, the proposed method can accurately localize one or more sources in shallow water dominated by multipath propagation. It turns out that the natural formulation of our approach involves minimization of two quadratic functions subject to infinitely many nonconvex quadratic constraints. It shows that this problem （originally intractable） can be reformulated in a convex form as the so-called second-order cone program （SOCP） and solved efficiently by using the well-established interior point method, such as the sottware tool, SeDuMi. Computer simulations show better performance of the proposed method as compared with existing algorithms and establish a theoretical foundation for the practical engineering application.

Recognizing and monitoring infectious sources of schistosomiasis by developing deep learning models with high-resolution remote sensing images

Background China is progressing towards the goal of schistosomiasis elimination,but there are still some problems,such as difficult management of infection source and snail control.This study aimed to develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine,which is an intermediate source of Schistosoma japonicum infection,and to evaluate the effectiveness of the models for real-world application.Methods The dataset of livestock bovine’s spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services.The high-resolution remote sensing images were further divided into training data,test data,and validation data for model development.Two recognition models based on deep learning methods(ENVINet5 and Mask R-CNN)were developed with reference to the training datasets.The performance of the developed models was evaluated by the performance metrics of precision,recall,and F1-score.Results A total of 50 typical image areas were selected,1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model.For the ENVINet5 model,a total of 1598 records of bovine distribution were recognized.The model precision and recall were 81.9%and 80.2%,respectively.The F1 score was 0.81.For the Mask R-CNN mode,1679 records of bovine objectives were identified.The model precision and recall were 87.3%and 85.2%,respectively.The F1 score was 0.87.When applying the developed models to real-world schistosomiasis-endemic regions,there were 63 bovine objectives in the original image,53 records were extracted using the ENVINet5 model,and 57 records were extracted using the Mask R-CNN model.The successful recognition ratios were 84.1%and 90.5%for the respectively developed models.Conclusion The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples.The Mask R-CNN model has a good framework design and runs highly efficiently.The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock,which could enable precise control of schistosomiasis.

基于稳定同位素的干旱半干旱区SPAC水分运移过程研究进展

土壤-植物-大气连续体(SPAC)是生态水文学的重点研究对象,其水分运移过程对于干旱半干旱区生态植被建设和水资源综合管理具有重要意义。氢氧稳定同位素较高的灵敏性和准确度有助于揭示这一过程。介绍了氢氧稳定同位素在土壤-大气界面、土壤-地下水界面、土壤-植物界面和植物-大气界面水分补给传输过程中的应用,包括土壤水分来源和蒸发;水分补给入渗机制和滞留时间;植物水分来源和水力再分配;蒸散发分割和叶片吸水的相关研究,同时明确了氢氧稳定同位素技术在应用过程中存在的一些不确定性以及未来亟需加强的方面,以期为利用稳定同位素技术对生态水文过程的研究提供参考依据。

On electro-acoustic characteristics of a marine broadband sparker for seismic exploration

The construction of major marine infrastructure projects and the exploration and development of deep-sea mineral resources require fine imaging of seabed strata and structures.The highresolution marine seismic exploration based on a high broadband sparker source is an important approach to reveal seabed stratum and reservoir structure,and identify geohazard.To optimize the performance of sparker seismic source,we investigated the electro-acoustic characteristics of spark discharge under conditions of different charging voltages and electrode numbers.Results show that the sound source level increased with the increase of the charging voltage,whereas the main frequency decreased when the charging voltage increases.In addition,it was found that the charging capacitance had more obvious influence on the main frequency than the sound source level did.Although the load energy decreased with increasing electrode number,the sound source level still increased but the main frequency decreased.Meanwhile,the primary to bubble(P/B)ratio increased with the increase of the electrode number.To gain a deeper insight into the electro-acoustic characteristics,we investigate the relationship between sound source level and power peak,from which a good correlation was observed.A more practical statistical analysis on the rise rate of current was processed,and a perfect logarithmic function was derived.Furthermore,we found that the main frequency was most possibly subjected to the electrical energy,especially the charging energy per electrode.The results indicate that the charging energy per electrode less than 10 J could increase the main frequency to above 300 Hz.At last,the main frequency could be reduced to 20 Hz when the charging energy of a single-electrode discharge was enhanced to over 4 kJ.This study shall be helpful in developing a sparker seismic source and improving the performance for marine engineering exploration and geohazard assessment.

Development of a soil-plant-atmosphere continuum model (HDS-SPAC) based on hybrid dual-source approach and its verification in wheat field

HDS-SPAC,a new soil-plant-atmosphere continuum(SPAC) model,is developed for simulating water and heat transfer in SPAC.The model adopts a recently proposed hybrid dual source approach for soil evaporation and plant transpiration partitioning.For the above-ground part,a layer approach is used to partition available energy and calculate aerodynamic resistances,while a patch approach is used to derive sensible heat and latent heat fluxes from the two sources(soil and vegetation).For the below-ground part,soil water and heat dynamics are described by the mixed form of Richards equation,and the soil heat conductivity equation,respectively.These two parts are coupled through ground heat flux for energy transfer,root-zone water potential-dependent stomatal resistance,and surface soil water potential-dependent evaporation for water transfer.Evaporation is calculated from the water potential gradient at soil-atmosphere interface and aerodynamic resistance,and transpiration is determined using a Jarvis-type function linking soil water availability and atmospheric conditions.Some other processes,such as canopy interception and deep percolation,are also considered in the HDS-SPAC model.The hybrid dual-source approach allows HDS-SPAC to simulate heat and water transfer in an ecosystem with a large range of vegetation cover change temporally or spatially.The model was tested with observations at a wheat field in North China Plain over a time of three months covering both wet and dry conditions.The fractional crop covers change from 30% to over 90%.The results indicated that the HDS-SPAC model can estimate actual evaporation and transpiration partitioning and soil water content and temperature over the whole range of tested vegetation coverage.

高分辨连续光源石墨炉原子吸收光谱法测定食品中铅、镉和铬含量

使用高分辨连续光源石墨炉原子吸收光谱法对谷类、蔬菜、饮品、海产品和乳制品五类共22种常见食品中的重金属元素铅、镉和铬进行了研究。建立了样品预处理、样品消解和定量分析的实验方法,得到了良好的分析精密度(RSD=1.3%～4.9%)和回收率(95.1%～104.6%)。结果表明,茶叶中的铅和贝类中的铬含量远远大于其他食品,小米、韭菜和贝类中的镉含量较高。本研究为食品中重金属的检测建立了可靠的定量分析方法,为推动食品质量安全相关标准的制定提供了实验依据;同时,根据测定结果得出的食品中重金属含量的分布情况,对提高消费者的食品安全意识能够起到积极的引导作用。

连续光源原子吸收光谱法的研究进展及应用

经过几十年的研究和发展,连续光源原子吸收光谱法(Continuum source atomic ab-sorption spectrometry,CS AAS)在光源、分光系统、检测器、背景校正、软件的研究等方面已取得突破,并且已有商品化仪器。本文主要综述了近几十年来国外对连续光源原子吸收光谱法的研究发展历史及连续光源原子吸收光谱法在非金属(硫和卤素)测定、固体进样技术等方面的应用。

微波消解-连续光源原子吸收法快速顺序测定枸杞果中的6种金属元素

建立一种微波消解-连续光源原子吸收法快速测定枸杞果中金属元素的新方法。通过微波消解快速处理样品,用连续光源原子吸收法同时顺序测定枸杞果中的铁、锌、铜、锰、镉、铅6种金属元素,并对仪器使用条件、金属元素含量、精密度、检出限、回收率等进行研究。结果表明:方法检出限为0.006 07 0～0.04975μg/L,RSD为1.5%～5.0%,回收率为86.68%～111.7%。该法用于枸杞中6种金属元素的同时顺序测定,具有快速、简便、成本低廉等特点,分析结果令人满意。

浊点萃取-高分辨连续光源石墨炉原子吸收光谱法测定环境水样中的痕量铅

比较了三种不同的分离富集方法——共沉淀法、离子交换法和浊点萃取法对水样中痕量铅的富集效果,其中,浊点萃取法水样用量少、富集因子大、操作简便,故选取浊点萃取法对环境水样中的铅进行富集。采用浊点萃取-高分辨连续光源石墨炉原子吸收光谱法测定了采自北京市通惠河水样中的痕量铅。结果表明,该测定方法的检出限为0.08μg.L-1,相对标准偏差为1.3%～4.5%(n=6),加标回收率为93%～108%,样品溶液的富集因子为29。通惠河13个采样点水样中铅含量均符合国家规定的地表水水质Ⅰ类水标准,且从通州区至朝阳区呈现铅含量逐渐减少的趋势。

高分辨连续光源原子吸收光谱法对土壤中磷的测定

磷元素在适宜的空气-乙炔火焰中可形成PO双原子分子,PO分子的部分吸收谱线具有原子谱线的轮廓和强度。该文主要研究了利用连续光源原子吸收光谱法,在空气-乙炔火焰条件下测定PO分子的吸光度值,从而测定土壤样品中的磷元素。实验研究了测定过程中可能存在的光谱干扰和化学干扰、乙炔/空气流速比、燃烧器高度对PO双原子分子吸光度的影响,以及不同消解方式对测定结果的影响。在优化的实验条件下,PO246.40nm的检出限为20mg/L。通过对土壤标准物质中磷元素含量的测定比对证明,连续光源原子吸收光谱法是一种测定土壤中磷元素含量的简单、快速的方法。

高分辨连续光源原子吸收光谱法测定植物中的磷

利用连续光源原子吸收光谱法,通过测定磷元素在乙炔-空气火焰条件下形成的PO双原子分子的吸光度,从而确定植物样品中磷含量。实验研究了乙炔-空气比例和燃烧器高度对PO分子吸光度的影响及其他共存元素的光谱干扰和化学干扰。通过对植物标准物质中磷的测定比对证明:利用连续光源原子吸收光谱法,在乙炔-空气火焰条件下以PO分子测定植物样品中的磷是一种简单、快速、有效的方法。

氢化物发生-高分辨连续光源原子吸收光谱法测定食品中的汞和砷

使用氢化物发生-高分辨连续光源原子吸收光谱法对谷类、蔬菜、饮品、水产品和乳制品5类共22种常见食品中汞和砷的含量进行检测.建立样品预处理和连续光源原子吸收光谱法定量分析的方法,汞和砷的检出限分别为0.067、0.088 μg/L,加标回收率为97.0％～104.2％和96.4％～105.1％,相对标准偏差为0.8％～4.7％和3.5％～4.9％（n=6）.结果表明：全麦面、咖啡和4种海鲜类样品中的汞含量较高;韭菜、带鱼、贝类和虾中的砷含量较高.

连续光源原子吸收光谱法测定土壤水溶性盐中钙镁

使用连续光源原子吸收光谱仪在不更换元素灯情况下,一次进样测定土壤水溶盐组成中钙、镁离子含量,测定值与标准值的相对偏差小于5%,测定速度显著提高。连续光源原子吸收光谱法可选择元素任一谱线测定,对比30个土壤样品Mg次灵敏线202 nm与主灵敏线285 nm两条谱线测定结果,两者基本一致。高浓度时Mg次灵敏线202 nm的标准曲线相关性好于主灵敏线285 nm。与传统线光源原子吸收光谱仪相比,连续光源原子吸收光谱仪测试灵敏度显著提高。

高分辨连续光源原子吸收光谱法测定煤中硫

提出一种用HNO3、HClO4和HF消解样品、高分辨连续光源原子吸收光谱法测定硫在富燃空气-乙炔火焰中形成的CS双原子分子的吸收来测定煤中硫的新方法。实验用含硫标准溶液和煤的标准物质优化了仪器条件,并用不同混合酸对煤样的消解方法进行了比较。对可能存在的光谱和化学干扰、有机溶剂对硫的化合物CS吸收的影响进行了研究。结果表明:除了Fe 258.045 nm线与CS 258.056 nm线的波长差小于0.015 nm外,其他元素干扰线与CS线的波长差均大于0.015 nm,因此可以通过仪器的高分辨率使这些干扰线与CS线分开,克服干扰;Fe 258.045谱线虽然不能与CS 258.056 nm谱线完全分离,但是该谱线在富燃乙炔空气火焰中的吸收强度很弱,不能形成真正的干扰;Pb与溶液中的SO42-反应产生Pb-SO4沉淀降低了CS的吸收,可在溶液中加入乙酸铵溶液,使SO42-从PbSO4沉淀中释放出来而消除铅的干扰;HNO3、HClO4对CS的吸收影响不明显;在研究的甲醇、乙醇、乙酸、乙腈和丙酮5种有机溶剂中,只有乙醇对CS吸收有较显著的抑制作用,丙酮和乙腈能显著提高CS的吸收。对于CS 3条吸收线(257.594,258.056,257.961 nm),硫校准曲线的线性范围均为50～1 000 mg/L,检出限分别为34 mg/L,21 mg/L,12 mg/L。本方法用于煤标准物质和煤层样品中硫的测定,测定值与认定值相符,测定结果的相对标准偏差在0.053%～0.082%间(n=5)。

高分辨连续光源石墨炉原子吸收光谱法测定面制食品中的铝

使用微波消解-高分辨连续光源石墨炉原子吸收光谱法测定四种面制食品(挂面、饺子皮、油条和梳打饼干)中铝的含量。样品置于密闭聚四氟乙烯消解罐中经HNO3和H2O2混合溶液完全消解。对微波消解条件、灰化温度和原子化温度进行了优化。确定最佳实验条件为:消解液HNO3和H2O2体积比7∶1,微波功率1 000W,190℃消解40min;最佳灰化温度1 350℃;最佳原子化温度2 400℃;基体改进剂为1g.L-1硝酸镁。标准曲线相关系数为0.999 9,相对标准偏差(RSD)1.7%～2.4%,回收率98.16%～102.67%。本研究建立的面制食品中铝含量的测定方法对于相关食品标准检测方法的制定具有参考价值。

蒸馏-高分辨连续光源原子吸收光谱法测定果脯中二氧化硫

硫在富燃空气-乙炔火焰中可以形成CS双原子分子。CS双原子分子的吸收轮廓与原子光谱吸收类似,因此可以利用原子吸收光谱方法进行定量分析。建立了高分辨连续光源原子吸收光谱法分析果脯中二氧化硫含量的方法。果脯中的二氧化硫经酸化、蒸馏、过氧化氢氧化等过程转变为硫酸根,通过连续光源原子吸收光谱法检测。对影响二氧化硫检测灵敏度的乙炔流量、火焰高度等仪器参数进行了优化,并考察了样品中硫酸根、硫代硫酸根等不同形态硫对二氧化硫分析的干扰。优化条件下,在257.961nm波长的检出限为52.4mg·kg^(-1);相对标准偏差小于10%。应用于北京市售果脯样品二氧化硫含量测定,平均回收率在85.7%~115.7%之间。该方法具有准确快速、干扰少等优点,拓宽了原子吸收光谱法的应用范围。

连续光源原子吸收光谱法测定奶粉中钙铁锌

介绍了高分辨率连续光源原子吸收光谱仪(HS-CS-AAS)的特点,并利用HS-CS-AAS测定了奶粉中钙、铁、锌3种元素,同时与国家标准物质(GSV-4)作比较。结果表明,方法的回收率钙为93.0%～100.5%,锌为99.1%～105.8%,铁为80.9%～89.6%;相对标准偏差(n=7)钙为0.10%～3.90%,锌为0.10%～4.10%,铁为0.10%～2.20%。国家标准物质和奶粉中钙铁锌的测定均获得满意结果。

高分辨连续光源原子吸收光谱法测定植物中的硫

硫元素在富燃的乙炔/空气火焰可形成CS双原子分子,在某些特定的波长下,这些CS分子吸收谱线具有原子吸收的轮廓和一定的吸收强度。文章主要研究利用高分辨连续光源原子吸收光谱法,通过测定硫元素在富燃-乙炔/空气火焰条件下形成的CS双原子分子的吸光度值,从而测定植物样品中的硫元素含量。实验对乙炔-空气比例和燃烧器高度等仪器条件进行了优化;实验研究了五种有机溶剂对CS分子吸收产生的影响情况、其他共存元素的光谱干扰和化学干扰以及不同的消解酸种类对测定结果的影响。在优化的条件下,硫在CS257.961nm的检出限为14mg.L-1。通过对植物标准物质中硫含量的测定比对和精密度实验证明,利用连续光源原子吸收光谱法,在富燃-乙炔/空气焰条件下以CS分子测定植物样品中的硫元素是一种简单、快速、有效的方法。

氧化亚氮-乙炔火焰-连续光源原子吸收光谱法测定植物油中的聚二甲基硅氧烷

建立利用氧化亚氮-乙炔火焰-连续光源原子吸收光谱法,以4-甲基-2-戊酮有机溶剂直接进样测定植物油中聚二甲基硅氧烷含量的方法。在优化实验条件下,聚二甲基硅氧烷在4~500 mg/L质量浓度范围内具有良好的线性关系,相关系数r为0.999 3。实验在3个聚二甲基硅氧烷添加水平条件下,平均回收率在95.6%~103.7%之间,6次重复测定的相对标准偏差为2.3%~3.1%。实验获得本方法的检出限为2.05 mg/kg。该方法可满足于植物油中聚二甲基硅氧烷含量的测定。