基于非線性最小二乘的機(jī)載氣象雷達(dá)回波譜矩估計(jì)方法
發(fā)布時(shí)間:2018-10-22 17:15
【摘要】:機(jī)載氣象雷達(dá)無法檢測雷達(dá)回波信噪比(signal-to-noise ratio,SNR)很低的晴空湍流和干性風(fēng)切變。提出了一種參數(shù)化的機(jī)載氣象雷達(dá)回波譜矩估計(jì)方法,該方法利用非線性最小二乘(nonlinear least-squares,NLS)方法擬合回波的自相關(guān)序列估計(jì)譜矩。引入循環(huán)優(yōu)化思想來解決多個(gè)高斯譜回波混合時(shí)的譜矩估計(jì)問題。給出了將譜矩估計(jì)的二維搜索問題轉(zhuǎn)化為兩個(gè)一維搜索的快速算法。理論和仿真實(shí)驗(yàn)與分析表明,提出的方法適用于信噪比較低的情況。
[Abstract]:Airborne weather radar can not detect radar echo signal to noise ratio (signal-to-noise ratio,SNR) low clear air turbulence and dry wind shear. A parameterized method for estimating the echo spectral moments of airborne meteorological radar is proposed. The nonlinear least square (nonlinear least-squares,NLS) method is used to fit the autocorrelation sequence estimation of the spectral moments of the echo. The idea of cyclic optimization is introduced to solve the problem of estimation of spectral moments when several Gao Si spectral echoes are mixed. In this paper, a fast algorithm for converting the two-dimensional search problem of spectral moment estimation into two one-dimensional search algorithms is presented. Theoretical and simulation experiments and analysis show that the proposed method is suitable for the case of low signal-to-noise ratio (SNR).
【作者單位】: 天津大學(xué)電子信息工程學(xué)院;中國民航大學(xué)智能信號(hào)與圖像處理天津市重點(diǎn)實(shí)驗(yàn)室;
【基金】:國家自然科學(xué)基金(61071194) 中央高;鹬袊窈酱髮W(xué)專項(xiàng)(ZXH2012D006)資助課題
【分類號(hào)】:TN959.4
[Abstract]:Airborne weather radar can not detect radar echo signal to noise ratio (signal-to-noise ratio,SNR) low clear air turbulence and dry wind shear. A parameterized method for estimating the echo spectral moments of airborne meteorological radar is proposed. The nonlinear least square (nonlinear least-squares,NLS) method is used to fit the autocorrelation sequence estimation of the spectral moments of the echo. The idea of cyclic optimization is introduced to solve the problem of estimation of spectral moments when several Gao Si spectral echoes are mixed. In this paper, a fast algorithm for converting the two-dimensional search problem of spectral moment estimation into two one-dimensional search algorithms is presented. Theoretical and simulation experiments and analysis show that the proposed method is suitable for the case of low signal-to-noise ratio (SNR).
【作者單位】: 天津大學(xué)電子信息工程學(xué)院;中國民航大學(xué)智能信號(hào)與圖像處理天津市重點(diǎn)實(shí)驗(yàn)室;
【基金】:國家自然科學(xué)基金(61071194) 中央高;鹬袊窈酱髮W(xué)專項(xiàng)(ZXH2012D006)資助課題
【分類號(hào)】:TN959.4
【共引文獻(xiàn)】
相關(guān)博士學(xué)位論文 前1條
1 劉智慧;復(fù)雜噪聲中二維諧波參數(shù)估計(jì)的子空間方法研究[D];中國地質(zhì)大學(xué);2013年
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