本文選題：信號(hào)處理　切入點(diǎn)：小波閾值去噪　出處：《電子與信息學(xué)報(bào)》2016年05期

【摘要】：為了解決二階互模糊函數(shù)對(duì)相關(guān)噪聲處理的局限性問題,以及基于四階累積量的聯(lián)合估計(jì)算法的運(yùn)算量大的問題,該文利用小波閾值去噪方法結(jié)合非圓信號(hào)的特性,提出一種新的時(shí)頻差聯(lián)合估計(jì)算法。該方法首先對(duì)接收信號(hào)進(jìn)行小波閾值去噪,然后構(gòu)造共軛模糊函數(shù),最后再進(jìn)行2維搜索,得到時(shí)差和頻差參數(shù)。仿真實(shí)驗(yàn)給出不同信噪比下的參數(shù)估計(jì)結(jié)果,得出這種算法能抑制相關(guān)噪聲,又能相對(duì)降低運(yùn)算復(fù)雜度,并且在較低信噪比下也能做出準(zhǔn)確估計(jì)。
[Abstract]:In order to solve the problem of the limitation of the second order mutual ambiguity function to the correlation noise processing, and the large computation of the joint estimation algorithm based on the fourth order cumulant, the wavelet threshold denoising method is used to combine the characteristics of the non-circular signal.A new joint time-frequency difference estimation algorithm is proposed.The received signal is de-noised by wavelet threshold, then conjugate ambiguity function is constructed, and then 2-D search is carried out to obtain the parameters of time difference and frequency difference.The simulation results show that the proposed algorithm can suppress the correlation noise and reduce the computational complexity, and it can also estimate the parameters accurately at lower signal-to-noise ratio (SNR).
【作者單位】： 北京工業(yè)大學(xué)電子信息與控制工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(61171137) 北京市教委科研發(fā)展計(jì)劃(KM201210005001)~~
【分類號(hào)】：TN911.23

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本文編號(hào)：1724166