【摘要】：在測量數(shù)據(jù)處理過程中,我們在進(jìn)行常規(guī)的方差-協(xié)方差擬合推估時,通常假定隨機(jī)信號具有各向同性的隨機(jī)過程,在進(jìn)行運算的過程中不考慮隨機(jī)信號與觀測噪聲之間的相關(guān)性,然而現(xiàn)實中隨機(jī)信號的各向異性具有普遍性,即隨機(jī)信號和觀測噪聲之間也存在著相關(guān)聯(lián)系。如果在進(jìn)行擬合推估的過程中不考慮其相關(guān)性,其運算結(jié)果則不是最優(yōu)的。為了求取最佳估值,本文在考慮隨機(jī)信號和觀測噪聲以及已測點信號與未測點信號之間的相關(guān)性前提下,選取最小二乘擬合推估法為研究模型來求解參數(shù)X和Y的估值,并采用觀測噪聲和隨機(jī)信號的方差-協(xié)方差估計來確定隨機(jī)模型。在求得解析式后,本文采用最小范數(shù)二次無偏估計法來協(xié)調(diào)擬合推估模型中觀測噪聲和隨機(jī)信號之間的權(quán)比,隨后運用MATLAB軟件進(jìn)行模型的擬合推估,分別對比觀測值互相獨立下和參數(shù)相關(guān)下的擬合結(jié)果,分析其差異性,說明該算法的實用性和優(yōu)越性。
[Abstract]:In the process of measuring data processing, we usually assume that the random signal has isotropic stochastic process when we estimate the normal variance-covariance fitting. The correlation between random signal and observation noise is not considered in the course of operation, but the anisotropy of random signal is universal in reality, that is, there is a correlation between random signal and observation noise. If the correlation is not considered in the process of fitting estimation, the result is not optimal. In order to obtain the best estimation, considering the correlation between the random signal and the observed noise, and the correlation between the measured point signal and the unmeasured point signal, the least square fitting estimation method is selected as the research model to solve the estimation of the parameters X and Y. The random model is determined by variance-covariance estimation of observation noise and random signal. After the analytical formula is obtained, the least norm quadratic unbiased estimation method is used to coordinate the fitting and estimation of the weight ratio between the observed noise and the random signal in the model, and then the fitting estimation of the model is carried out by using MATLAB software. By comparing the fitting results under the condition of independent observation and parameter correlation, the difference of the algorithm is analyzed, and the practicability and superiority of the algorithm are proved.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：P207

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本文編號：2392871