基于小波閾值去噪和共軛模糊函數(shù)的時頻差聯(lián)合估計算法

竇慧晶; 王千龍; 張雪

doi:10.11999/JEIT150878

基于小波閾值去噪和共軛模糊函數(shù)的時頻差聯(lián)合估計算法

doi: 10.11999/JEIT150878

基金項目:

國家自然科學基金(61171137)，北京市教委科研發(fā)展計劃(KM201210005001)

計量
- 文章訪問數(shù): 1538
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- PDF下載量: 373
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-07-23
- 修回日期: 2015-11-19
- 刊出日期: 2016-05-19

A Joint Estimation Algorithm of TDOA and FDOA Based on Wavelet Threshold De-noising and Conjugate Fuzzy Function

Funds:

The National Natural Science Foundation of China (61171137), Beijing Municipal Education Commission Research and Development Programs (KM201210005001)

摘要

摘要: 為了解決二階互模糊函數(shù)對相關(guān)噪聲處理的局限性問題，以及基于四階累積量的聯(lián)合估計算法的運算量大的問題，該文利用小波閾值去噪方法結(jié)合非圓信號的特性，提出一種新的時頻差聯(lián)合估計算法。該方法首先對接收信號進行小波閾值去噪，然后構(gòu)造共軛模糊函數(shù)，最后再進行2維搜索，得到時差和頻差參數(shù)。仿真實驗給出不同信噪比下的參數(shù)估計結(jié)果，得出這種算法能抑制相關(guān)噪聲，又能相對降低運算復(fù)雜度，并且在較低信噪比下也能做出準確估計。
- 信號處理 /
- 小波閾值去噪 /
- 非圓信號 /
- 共軛模糊函數(shù) /
- 聯(lián)合估計
Abstract: To solve the problem that the second-order fuzzy function can not deal with related noise, as well as the problem of large computation based on fourth-order cumulants joint estimation algorithm, this paper proposes a new joint estimation algorithm of TDOA and FDOA by using wavelet thresholding denoising method combined with characteristics of non-circular signals. The method operates firstly wavelet thresholding denoising for the received signal, then constructs conjugate fuzzy function, and finally two-dimensional search is made to obtain the time difference and frequency difference parameters. The simulation experimental results under different signal-to- noise ratio show that the proposed algorithm can not only suppress correlated noise, but also has relatively lower computational complexity and also can make accurate estimation under low signal-to-noise ratio.
- Signal processing /
- Wavelet threshold de-noising /
- Non-circular signal /
- Conjugate fuzzy function /
- Joint estimation

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參考文獻(24)

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