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Cooperative interception with fast multiple model adaptive estimation 被引量:1
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作者 Shao-bo Wang Yang Guo +2 位作者 Shi-cheng Wang Zhi-guo Liu Shuai Zhang 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2021年第6期1905-1917,共13页
For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For ... For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang For the case that two pursuers intercept an evasive target,the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target,which performs a bang-bang evasive maneuver with a random switching time.Combined Fast multiple model adaptive estimation(Fast MMAE)algorithm,the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration.Introduced the detection error model related to the line-of-sight(LOS)separation angle of two interceptors,an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance.Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion,Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately.The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation. 展开更多
关键词 Cooperative guidance Optimal control Fast multiple model adaptive estimation (fast MMAE) Bang-bang maneuver Switch time Detection configuration estimation error
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A new relative efficiency in parameter estimation for linear model
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作者 YANG Hu CHEN Zhu-liang 《Journal of Chongqing University》 CAS 2007年第2期141-145,共5页
A new relative efficiency of parameter estimation for generalized Gauss-Markov linear model was proposed. Its lower bound was also derived. Its properties were explored in comparison with three currently very popular ... A new relative efficiency of parameter estimation for generalized Gauss-Markov linear model was proposed. Its lower bound was also derived. Its properties were explored in comparison with three currently very popular relative efficiencies. The new relative efficiency not only reflects sensitively the error and loss caused by the substitution of the least square estimator for the best linear unbiased estimator, but also overcomes the disadvantage of weak dependence on the design matrix. 展开更多
关键词 linear model narameter estimation relative efficiency
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Quantitative inverse modeling of nitrogen content from hyperion data under stress of exhausted coal mining sites 被引量:4
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作者 LU Xia HU Zhen-qi GUO Li 《Mining Science and Technology》 EI CAS 2009年第1期31-35,共5页
Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun ... Monitoring and evaluating the nutritional status of vegetation under stress from exhausted coal mining sites by hyper-spectral remote sensing is important in future ecological restoration engineering. The Wangpingcun coal mine, located in the Mentougou district of Beijing, was chosen as a case study. The ecological damage was analyzed by 3S technology, field investigation and from chemical data. The derivative spectra of the diagnostic absorption bands are derived from the spectra measured in the field and used as characteristic spectral variables. A correlation analysis was conducted for the nitrogen content of the vegetation samples and the fast derivative spectrum and the estimation model of nitrogen content established by a multiple stepwise linear regression method. The spatial distribution of nitrogen content was extracted by a parameter mapping method from the Hyperion data which revealed the distribution of the nitrogen content. In addition, the estimation model was evaluated for two evaluation indicators which are important for the precision of the model. Experimental results indicate that by linear regression and parameter mapping, the estimation model precision was Very high. The coefficient of determination, R2, was 0.795 and the standard deviation of residual (SDR) 0.19. The nitrogen content of most samples was about 1.03% and the nitrogen content in the study site seems inversely proportional to the distance from the piles of coal waste. Therefore, we can conclude that inversely modeling nitrogen content by hyper-spectral remote sensing in exhausted coal mining sites is feasible and our study can be taken as reference in species selection and in subseauent management and maintenance in ecological restoration. 展开更多
关键词 HYPERION nitrogen content estimation model linear regression
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A LARGE SAMPLE ESTIMATE IN MEDIAN LINEAR REGRESSION MODEL Ⅰ: NONTRUNCATED CASE 被引量:1
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作者 陈希孺 《Acta Mathematica Scientia》 SCIE CSCD 1990年第4期412-421,共10页
This paper uses a grouping-adjusting procedure to the data from a median linear regression model, and estimtes the regression coefficients by the method of weighted least squares. This method simplifies computation an... This paper uses a grouping-adjusting procedure to the data from a median linear regression model, and estimtes the regression coefficients by the method of weighted least squares. This method simplifies computation and in the meantime, preserves the same asymptotic normal distribution for the estimator, as in the ordinary minimum L_1-norm estimates. 展开更多
关键词 A LARGE SAMPLE ESTIMATE IN MEDIAN LINEAR REGRESSION model NONTRUNCATED CASE
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Mapping spatial variation in acorn production from airborne hyperspectral imagery 被引量:1
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作者 Kenshi SAKAI 《Forestry Studies in China》 CAS 2010年第2期49-54,共6页
Masting is a well-marked variation in yields of oak forests. In Japan, this phenomenon is also related to wildlife management and oak regeneration practices. This study demonstrates the capability of integrating remot... Masting is a well-marked variation in yields of oak forests. In Japan, this phenomenon is also related to wildlife management and oak regeneration practices. This study demonstrates the capability of integrating remote sensing techniques into map- ping spatial variation of acorn production. The hyperspectral images in 72 wavelengths (407-898 nm) were acquired over the study area ten times over a period of three years (2003-2005) during the early growing season of Quercus serrata using the Airborne Im- aging Spectrometer Application (AISA) Eagle System. With the canopy spectral reflectance values of 22 sample trees extracted from the images, yield estimation models were developed via multiple linear regression (MLR) analyses. Using the object-oriented classi- fication approach in eCognition, canopies representative of individual oak trees (Q. serrata) were identified from the corresponding hyperspectral imagery and combined with the fitted estimation models developed, acorn yield over the entire forest were estimated and visualized into maps. Three estimation models, obtained for June 27 in 2003, July 13 in 2004 and June 21 in 2005, showed good performance in acorn yield estimation both for the training and validation datasets, all with R2 〉 0.4, p 〈 0.05 and RRMSE 〈 1 (the relative root mean square of error). The present study shows the potential of airborne hyperspectral imagery not only in estimating acorn yields during early growing seasons, but also in identifying Q. serrata from other image objects, based on which of the spatial distribution patterns of acorn production over large areas could be mapped. The yield map can provide within-stand abundance and valuable information for the size and spatial synchrony of acorn production. 展开更多
关键词 yield map estimation model classification map ACORN spatial synchrony hyperspectral imagery MASTING
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