基于小波阈值去噪和共轭模糊函数的时频差联合估计算法

窦慧晶; 王千龙; 张雪

doi:10.11999/JEIT150878

基于小波阈值去噪和共轭模糊函数的时频差联合估计算法

doi: 10.11999/JEIT150878

基金项目:

国家自然科学基金(61171137)，北京市教委科研发展计划(KM201210005001)

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- 被引次数: 0
出版历程
- 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: 为了解决二阶互模糊函数对相关噪声处理的局限性问题，以及基于四阶累积量的联合估计算法的运算量大的问题，该文利用小波阈值去噪方法结合非圆信号的特性，提出一种新的时频差联合估计算法。该方法首先对接收信号进行小波阈值去噪，然后构造共轭模糊函数，最后再进行2维搜索，得到时差和频差参数。仿真实验给出不同信噪比下的参数估计结果，得出这种算法能抑制相关噪声，又能相对降低运算复杂度，并且在较低信噪比下也能做出准确估计。
- 信号处理 /
- 小波阈值去噪 /
- 非圆信号 /
- 共轭模糊函数 /
- 联合估计
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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参考文献(24)

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