本文關(guān)鍵詞：基于Bayesian-MCMC估計(jì)的隱身飛機(jī)RCS模型優(yōu)化　出處：《北京航空航天大學(xué)學(xué)報(bào)》2016年04期 　論文類型：期刊論文

  更多相關(guān)文章： 隱身 雷達(dá)散射截面(RCS) 起伏模型 貝葉斯-蒙特卡羅 擬合優(yōu)度檢驗(yàn)

【摘要】：對(duì)隱身飛機(jī)的雷達(dá)散射截面(RCS)統(tǒng)計(jì)建模時(shí),傳統(tǒng)方法通過直接計(jì)算RCS樣本的統(tǒng)計(jì)特征估計(jì)模型參數(shù),可能會(huì)產(chǎn)生較大的擬合誤差。本文提出采用貝葉斯-蒙特卡羅(Bayesian-MCMC)方法提高起伏模型的參數(shù)估計(jì)精度,從而減小模型的擬合誤差。首先將卡方分布模型和對(duì)數(shù)正態(tài)分布模型進(jìn)行貝葉斯推導(dǎo),得到其特征參數(shù)的后驗(yàn)估計(jì)表達(dá)式。然后采用MCMC算法構(gòu)造后驗(yàn)分布的馬爾可夫鏈,從而計(jì)算特征參數(shù)的估計(jì)值。最后通過比較2種方法的擬合曲線及其誤差可知,本文方法適用于2種起伏模型,模型參數(shù)的估計(jì)誤差比收斂誤差門限值低1~2個(gè)數(shù)量級(jí),2種分布模型的擬合精度均提高50%以上。
[Abstract]:In the statistical modeling of radar cross section (RCS) of stealthy aircraft, the traditional method directly calculates the statistical characteristics of the RCS samples to estimate the model parameters. The Bayesian Monte Carlo Bayesian-MCMC method is proposed to improve the parameter estimation accuracy of the undulating model. In order to reduce the fitting error of the model. Firstly, the chi-square distribution model and the logarithmic normal distribution model are derived by Bayesian method. The posteriori estimation expression of the characteristic parameters is obtained, and then the Markov chain of the posteriori distribution is constructed by using the MCMC algorithm. Finally, by comparing the fitting curves and their errors of the two methods, we can see that this method is suitable for two kinds of undulating models. The estimation error of the model parameters is 1 ~ 2 orders of magnitude lower than the convergence error threshold. The fitting accuracy of the two distribution models is improved by more than 50%.
【作者單位】： 電子科技大學(xué)電子工程學(xué)院;中國電子科學(xué)研究院;
【基金】：國家“863”計(jì)劃(2012AA01A308) 國家“973”計(jì)劃(613206)~~
【分類號(hào)】：TN953;V218
【正文快照】： 網(wǎng)絡(luò)出版地址:www.cnki.net/kcms/detail/11.2625.V.20150917.1650.009.html引用格式:代小霞,曹晨,馮圓.基于Bayesian-MCMC估計(jì)的隱身飛機(jī)RCS模型優(yōu)化[J].北京航空航天大學(xué)學(xué)報(bào),2016,42(4):851-857.DAI X X,CAO C,FENG Y.Optimization on stealth aircraft RCS models using B，

本文編號(hào)：1439479