跳频通信信号参数盲估计算法研究
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摘要
跳频通信作为扩展频谱通信技术的一种,凭借其强的抗干扰、抗截获和易组网能力,在军事和民用领域都得到了很好的应用。跳频通信系统是一种用码序列来控制载波频率跳变的系统,跳频信号是一种典型的多分量非平稳信号,从时域上来看是一个多频率的频移键控信号,在频域上则看做是一个在很宽频带上以相等间隔或者不等间隔随机跳变的信号。对这种非平稳信号进行分析时,要得到其时域和频域的信息,仅仅依靠傅里叶变换是不可能的。时频分析是一种可以同时描述信号在不同时刻和不同频率的能量密度的信号处理方法,因此,近些年来得到广泛的关注。本论文主要从时频分析技术着手,研究其在跳频信号参数盲估计中的应用。
时频分析方法分为线性和双线性两种,线性时频分布包括短时傅里叶变换和小波变换。魏格纳分布和伪魏格纳分布、平滑伪魏格纳分布以及Butterworth分布等都属于双线性时频分布。本文主要对以下几个方面进行研究：
(1)基于FFT的重排谱图算法虽然可以提高短时傅里叶变换的时频分辨率,但算法复杂度较高,并且时频分布性能受窗函数长度和类型的影响,为此,本文利用前人提出的一种递归谱图重排算法对跳频信号进行参数盲估计,并通过仿真分析了在跳频参数盲估计过程中对比两种算法的性能,结果表明递归重排算法的复杂度要低于基于FFT的谱图重排算法,且不受窗函数长度的影响,在抗噪声能力方面两种算法性能相差不大,在信噪比大于0dB时都可以很好的估计出跳频信号参数。
(2)描述了一种衡量时频分布优劣的信息熵测度准则,用信息熵准则来优化平滑伪魏格纳分布的参数信息,以此来提高平滑伪魏格纳分布的时频聚集性,并基于该算法进行跳频信号参数盲估计,在信噪比不低于0dB时可以实现对跳频参数的正确估计。为实现在更低信噪比下的参数估计,本文通过提取平滑伪魏格纳分布的时频脊线,联合利用小波变换的奇异点检测性能来检测时频脊线的跳变点的算法,来估计跳频周期和跳变时刻,仿真结果表明在信噪比不低于-1dB时可以实现跳频参数的正确估计。
(3)针对慢速跳频信号的特点和魏格纳-威尔分布(Winger-Ville Distribution,WVD)对单分量信号优良的时频聚集特性,改进了一种基于信号分解的跳频信号参数盲估计算法。在低信噪比条件下,采用频率细化方法提高了频率估计的准确度。仿真结果表明提出的方案对慢速跳频信号参数估计能够降低信噪比阈值门限和算法复杂度。本文还将该频率细化方案应用到快跳频信号的跳频频率的参数估计中,也可以提高跳频频率估计的准确度。
As a kind of spread spectrum communication technology, frequency hopping communication has been extensively used in the military and civilian fields, because of its strong anti-jamming and anti-intercept properties and networking ability. In frequency hopping communication system, code sequence is used to control hopping of the carrier frequency, so frequency hopping signal is a typical of multi-component non-stationary signal. In the time domain, frequency hopping signal is a multi-frequency shift keying signal. In the frequency domain, it is a random hopping signal in a wide frequency band on equal or unequal intervals. In analysis of this non-stationary signal, the Fourier transform is unable to obtain the joint information of time domain and frequency domain. Time-frequency analysis is a kind of signal processing method which can describe energy density at different times and frequencies. So it gets extensive attention in recent years. In the paper, time-frequency analysis technology is mainly used to study the parameter blind estimation in frequency hopping signal.
The method of time-frequency analysis can be divided into linear time-frequency analysis and bilinear time-frequency analysis. In Linear time-frequency distribution, including short time Fourier transform and wavelet transform. Wigner and pseudo-Wigner distribution, smoothed pseudo Wigner distribution and Butterworth distribution belong to bilinear time-frequency distribution. This paper mainly study from the following aspects:
Firstly, although FFT-based algorithm for the spectrogram reassignment is able to improve the time-frequency resolution of short time Fourier transform, the algorithm complexity is higher. And the performance of time-frequency distribution is affected by the type of window function and length. So, recursive algorithm that has been proposed by the previous is used to realize the parameter blind estimation in frequency hopping signal. And in the process of parameter blind estimation, the performance of these algorithms is analyzed and compared by simulation. The results show that the algorithm complexity of recursive algorithm is lower than FFT-based algorithm, and is not affected by the length of window function. In terms of anti-noise ability, when signal-to-noise ratio is greater than OdB, this two algorithms both can realize the parameter blind estimation.
Secondly, information entropy criteria which can be used to measure the merits of time-frequency distribution is described. In order to improve time-frequency concentration, the information entropy criterion is used to optimize the parameter information of smoothed pseudo Wigner-Ville distribution, And smoothed pseudo Wigner-Ville distribution which has been optimized is applied to realize the parameter blind estimation in frequency hopping signal, can get the correct estimation of frequency hopping parameters when the signal-to-noise ratio is not less than OdB. In order to realize the estimation of the frequency hopping parameters when the signal-to-noise ratio is lower, a algorithm that wavelet transform with singularity detection performance is used to detect hopping point of time-frequency ridge of smoothed pseudo Wigner-Ville distribution is proposed. Frequency-hopping duration and frequency-hopping timing can be estimated. The results of simulation show that the estimation of frequency hopping parameters can be get when the signal-to-noise ratio is not less than-1dB.
Finally, the characteristics of slow frequency hopping signal and Winger-Ville Distribution with excellent time-frequency concentration for single frequency component signals, the signal decomposition method which is used to estimate slow frequency hopping signal parameters is proposed. When signal-to-noise ratio is low, frequency refining method is used to improve accuracy of frequency estimation. The results of simulation show that the method is effective for parameter estimation in slow frequency hopping signal, and reduce the signal to noise ratio threshold and computational complexity. The frequency refining method is also applied to estimate the frequency-hopping frequency of fast frequency hopping signal, the accuracy also can be increased.
时频分析方法分为线性和双线性两种,线性时频分布包括短时傅里叶变换和小波变换。魏格纳分布和伪魏格纳分布、平滑伪魏格纳分布以及Butterworth分布等都属于双线性时频分布。本文主要对以下几个方面进行研究：
(1)基于FFT的重排谱图算法虽然可以提高短时傅里叶变换的时频分辨率,但算法复杂度较高,并且时频分布性能受窗函数长度和类型的影响,为此,本文利用前人提出的一种递归谱图重排算法对跳频信号进行参数盲估计,并通过仿真分析了在跳频参数盲估计过程中对比两种算法的性能,结果表明递归重排算法的复杂度要低于基于FFT的谱图重排算法,且不受窗函数长度的影响,在抗噪声能力方面两种算法性能相差不大,在信噪比大于0dB时都可以很好的估计出跳频信号参数。
(2)描述了一种衡量时频分布优劣的信息熵测度准则,用信息熵准则来优化平滑伪魏格纳分布的参数信息,以此来提高平滑伪魏格纳分布的时频聚集性,并基于该算法进行跳频信号参数盲估计,在信噪比不低于0dB时可以实现对跳频参数的正确估计。为实现在更低信噪比下的参数估计,本文通过提取平滑伪魏格纳分布的时频脊线,联合利用小波变换的奇异点检测性能来检测时频脊线的跳变点的算法,来估计跳频周期和跳变时刻,仿真结果表明在信噪比不低于-1dB时可以实现跳频参数的正确估计。
(3)针对慢速跳频信号的特点和魏格纳-威尔分布(Winger-Ville Distribution,WVD)对单分量信号优良的时频聚集特性,改进了一种基于信号分解的跳频信号参数盲估计算法。在低信噪比条件下,采用频率细化方法提高了频率估计的准确度。仿真结果表明提出的方案对慢速跳频信号参数估计能够降低信噪比阈值门限和算法复杂度。本文还将该频率细化方案应用到快跳频信号的跳频频率的参数估计中,也可以提高跳频频率估计的准确度。
As a kind of spread spectrum communication technology, frequency hopping communication has been extensively used in the military and civilian fields, because of its strong anti-jamming and anti-intercept properties and networking ability. In frequency hopping communication system, code sequence is used to control hopping of the carrier frequency, so frequency hopping signal is a typical of multi-component non-stationary signal. In the time domain, frequency hopping signal is a multi-frequency shift keying signal. In the frequency domain, it is a random hopping signal in a wide frequency band on equal or unequal intervals. In analysis of this non-stationary signal, the Fourier transform is unable to obtain the joint information of time domain and frequency domain. Time-frequency analysis is a kind of signal processing method which can describe energy density at different times and frequencies. So it gets extensive attention in recent years. In the paper, time-frequency analysis technology is mainly used to study the parameter blind estimation in frequency hopping signal.
The method of time-frequency analysis can be divided into linear time-frequency analysis and bilinear time-frequency analysis. In Linear time-frequency distribution, including short time Fourier transform and wavelet transform. Wigner and pseudo-Wigner distribution, smoothed pseudo Wigner distribution and Butterworth distribution belong to bilinear time-frequency distribution. This paper mainly study from the following aspects:
Firstly, although FFT-based algorithm for the spectrogram reassignment is able to improve the time-frequency resolution of short time Fourier transform, the algorithm complexity is higher. And the performance of time-frequency distribution is affected by the type of window function and length. So, recursive algorithm that has been proposed by the previous is used to realize the parameter blind estimation in frequency hopping signal. And in the process of parameter blind estimation, the performance of these algorithms is analyzed and compared by simulation. The results show that the algorithm complexity of recursive algorithm is lower than FFT-based algorithm, and is not affected by the length of window function. In terms of anti-noise ability, when signal-to-noise ratio is greater than OdB, this two algorithms both can realize the parameter blind estimation.
Secondly, information entropy criteria which can be used to measure the merits of time-frequency distribution is described. In order to improve time-frequency concentration, the information entropy criterion is used to optimize the parameter information of smoothed pseudo Wigner-Ville distribution, And smoothed pseudo Wigner-Ville distribution which has been optimized is applied to realize the parameter blind estimation in frequency hopping signal, can get the correct estimation of frequency hopping parameters when the signal-to-noise ratio is not less than OdB. In order to realize the estimation of the frequency hopping parameters when the signal-to-noise ratio is lower, a algorithm that wavelet transform with singularity detection performance is used to detect hopping point of time-frequency ridge of smoothed pseudo Wigner-Ville distribution is proposed. Frequency-hopping duration and frequency-hopping timing can be estimated. The results of simulation show that the estimation of frequency hopping parameters can be get when the signal-to-noise ratio is not less than-1dB.
Finally, the characteristics of slow frequency hopping signal and Winger-Ville Distribution with excellent time-frequency concentration for single frequency component signals, the signal decomposition method which is used to estimate slow frequency hopping signal parameters is proposed. When signal-to-noise ratio is low, frequency refining method is used to improve accuracy of frequency estimation. The results of simulation show that the method is effective for parameter estimation in slow frequency hopping signal, and reduce the signal to noise ratio threshold and computational complexity. The frequency refining method is also applied to estimate the frequency-hopping frequency of fast frequency hopping signal, the accuracy also can be increased.
引文
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