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您的检索式：作者名="ZENG HongCheng"
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| 1 | 基于星载激光雷达GLAS和光学MODIS数据中国森林冠层高度制图显示文摘星载GLAS波形数据精确记录了光斑内所有探测目标的垂直结构信息,在森林结构参数反演方面具有极大的应用潜力,但GLAS激光脚印是不连续分布的离散点且密度较低(中国地区平均约为0.14 point/km2),因此仅利用GLAS数据不能获得高精度的连续植被高度分布.已有研究表明,相对其他光学数据及反演参数,MODIS BRDF参数最能反映植被结构信息.本文利用同时期(2008年2月)的GLAS与MODIS数据,首先采用小波分析方法提取GLAS数据的波形特征参数,通过ASTER GDEM数据计算地形指数,并辅以植被分类数据分三种森林类型分别建立基于波形特征参数和地形指数的树高估算模型;然后,通过神经网络训练建立基于GLAS树高和最佳MODIS BRDF波段组合的树高反演模型,并应用该模型得到中国森林植被平均高度的连续分布图;最后,利用野外实测树高和机载激光雷达数据提取树高分别对反演结果进行验证,结果表明该模型反演精度较高. | 杨婷 王成 李贵才 骆社周 习晓环 高帅 HongCheng ZENG | 2014 | 中国科学:地球科学2014，44，11： | 13 |
| 2 | Forest canopy height mapping over China using GLAS and MODIS data显示文摘The Geoscience Laser Altimeter System(GLAS)accurately detects the vertical structural information of a target within its laser spot and is a promising system for the inversion of structural features and other biophysical parameters of forest ecosystems.Since the GLAS footprints are discontinuously distributed with a relativity low density,continuous vegetation height distributions cannot be mapped with a high accuracy using GLAS data alone.The MODIS BRDF product provides more forest structural information than other optical remote sensing data.This study aimed to map forest canopy heights over China from the GLAS and MODIS BRDF data.Firstly,the waveform characteristic parameters were extracted from the GLAS data by the method of wavelet analysis,and the terrain index was calculated using the ASTER GDEM data.Secondly,the model reducing the topographic influence was constructed from the waveform characteristic parameters and terrain index.Thirdly,the final canopy height estimation model was constructed from the neural network combining the canopy height estimated with the GLAS point and the MODIS BRDF data,and applied to get the continuous canopy height map over China.Finally,the map was validated by the measured data and the airborne Li DAR data,and the validation results indicated that forest canopy heights can be estimated with high accuracy from combined GLAS and MODIS data. | YANG Ting WANG Cheng LI GuiCai LUO SheZhou XI XiaoHuan GAO Shuai ZENG HongCheng | 2015 | Science China Earth Sciences2015，58，1： | 8 |
| 3 | A spawning particle filter for defocused moving target detection in GNSS-based passive radar显示文摘Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately. | ZENG Hongcheng DENG Jiadong WANG Pengbo ZHOU Xinkai YANG Wei CHEN Jie | 2023 | Journal of Systems Engineering and Electronics2023，34，5： | 0 |
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