| 133 | 0 | 3 |
| Downloads | Citas | Reads |
在现有的基于时频脊线的跳频参数盲估计算法中，当信噪比（signal to noise ratio,SNR）低于-5 dB时，其性能会出现显著下降的情况。针对这一问题，提出一种基于时频脊线的跳频参数盲估计改进算法。首先，通过短时傅里叶变换（short time Fourier transform,STFT）获取接收信号时频矩阵。随后，运用高斯滤波对信号进行平滑处理，同时实现对噪声的有效抑制。由于定频干扰与跳频信号在时频矩阵中的能量分布存在差异，利用能量对消法去除定频干扰。在此基础上，采用OTSU阈值分割算法确定的阈值对能量对消后的时频矩阵进行阈值分割，进一步消除残留的定频干扰和噪声，从而得到清晰的跳频信号时频图像。从该图像中提取跳频信号时频脊线，最后借助最小二乘法对时频脊线中的跳变时刻进行拟合，实现对跳频参数的精确估计。仿真结果表明，所提方法在SNR低至-5 dB且存在定频干扰时，可得到干净的时频图像，对各项跳频参数的平均估计相对误差低于1%，同时对不同强度与数量的定频干扰具有较强鲁棒性。
Abstract：In existing blind estimation algorithms for frequency-hopping parameters based on time-frequency ridges,performance degrades significantly when the signal-to-noise ratio(SNR) falls below-5 dB. To address this issue, an improved blind estimation method based on time-frequency ridges is proposed. First, the time-frequency matrix of the received signal is obtained using the short-time Fourier transform(STFT). Then, Gaussian filtering is applied for signal smoothing and noise suppression. Since the energy distribution of fixed-frequency interference differs from that of frequency-hopping signals in the time-frequency matrix, an energy cancellation method is used to eliminate such interference. Next, OTSU thresholding is applied to the matrix after energy cancellation to further remove residual fixed-frequency interference and noise, yielding a clearer time-frequency representation. Time-frequency ridges are then extracted from this image, and the least-squares method is employed to fit the hopping instants along these ridges, enabling accurate estimation of frequency-hopping parameters. Simulation results show that the proposed method effectively produces clean time-frequency images even at SNR levels as low as-5 dB in the presence of fixed-frequency interference. The average relative estimation error of each parameter remains below 1%, and the method demonstrates strong robustness against varying intensity and quantity of interference.
[1] JIN Y, C HEN S K, XIE Z, et al. A novel optical frequency-hopping scheme using dual drive Mach-Zehnder modulator[J]. IEEE Photonics Journal, 2022, 14(1):7209306.
[2] ZHANG C Z, WANG Y, JING F L. Underdetermined blind source separation of synchronous orthogonal frequency hopping signals based on single source points detection[J]. Sensors, 2017, 17(9):2074.
[3] WANG Z C, CHENG J, SU R H, et al. Signal detection and parameter estimation of hybrid hopping spread spectrum signal[C]//Proceedings of the 2023 6th International Conference on Information Communication and Signal Processing(ICICSP), September 23-25, 2023, Xi′an, China. New York:IEEE Xplore, 2023:300-307.
[4]付卫红，张云飞，韦娟，等.基于压缩感知的跳频信号参数盲估计算法[J].通信学报，2017, 38(12):48-56.FU W H, ZHANG Y F, WEI J, et al. Blind parameter estimation algorithm for frequency-hopping signals based on compressed sensing[J]. Journal on Communications,2017, 38(12):48-56.(in Chinese)
[5] SHEN Z Y, WANG Q Q, CHENG X M. A sparsity adaptive compressed signal reconstruction based on sensing dictionary[J]. Journal of Systems Engineering and Electronics,2021, 32(6):1345-1353.
[6]刘佳敏，赵知劲，尚俊娜，等.基于时频矩阵局部对比度的跳频信号参数估计[J].电信科学，2021, 37(10):126-135.LIU J M, ZHAO Z J, SHANG J N, et al. Parameter estimation of frequency hopping signal based on time-frequency matrix LCM[J]. Telecommunications Science, 2021,37(10):126-135.(in Chinese)
[7]张盛魁，姚志成，何岷，等.基于时频方差聚类的FH信号参数盲估计[J].系统工程与电子技术，2020, 42(8):1662-1667.ZHANG S K, YAO Z C, HE M, et al. FH signal parameter blind estimation based on time-frequency variance clustering[J]. Systems Engineering and Electronics, 2020,42(8):1662-1667.(in Chinese)
[8] WANG L D, LIU Z P, FENG Y T, et al. A parameter estimation method for time-frequency-overlapped frequency hopping signals based on sparse linear regression and quadratic envelope optimization[J]. International Journal of Communication Systems, 2020, 33(12):e4463.
[9] MI W H, WANG H B, GUO D X, et al. Parameter estimation of frequency-hopping signal and simulation based on kernel function design[C]//Proceedings of the 2022 7th International Conference on Intelligent Computing and Signal Processing(ICSP), April 15-17, 2022, Xi′an, China.New York:IEEE Xplore, 2022:997-1003.
[10]陈利虎，张尔扬，沈荣骏.跳频信号的时频分析[J].宇航学报，2009, 30(2):740-747.CHEN L H, ZHANG E Y, SHEN R J. Time-frequency analysis of frequency-hopping signals[J]. Journal of Astronautics, 2009, 30(2):740-747.(in Chinese)
[11]蔡云，刘成皓，张鑫.非协作跳频通信信号参数估计与仿真[J].计算机仿真，2018, 35(11):202-206.CAI Y, LIU C H, ZHANG X. Estimation and simulation of parameters from non-cooperative hopping signal[J].Computer Simulation, 2018, 35(11):202-206.(in Chinese)
[12]冯涛，袁超伟.基于时频脊线的跳频参数盲估计[J].电子学报，2011, 39(12):2921-2925.FENG T, YUAN C W. Blind parameter estimation of frequency-hopping signals based on the time-frequency distribution maxima[J]. Acta Electronica Sinica, 2011, 39(12):2921-2925.(in Chinese)
[13] SARKAR T K, PEREIRA O. Using the matrix pencil method to estimate the parameters of a sum of complex exponentials[J]. IEEE Antennas and Propagation Magazine,1995, 37(1):48-55.
[14] ROY R, PAULRAJ A, KAILATH T. Comparative performance of ESPRIT and MUSIC for direction-of-arrival estimation[C]//Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, April6-9, 1987, Dallas, TX, USA. New York:IEEE Xplore,1987:2344-2347.
[15] LUO L Q, PARMIGIANI F, YU Y F, et al. Frequency uncertainty improvement in a STFT-BOT DR using highly nonlinear optical fibers[J]. Optics Express, 2018, 26(4):3870-3881.
[16] SATAEV V. Designing Gaussian filters in the structure of a hydroacoustic channel[C]//Proceed ings of the 2022 24th International Conference on Digital Signal Processing and its Applications(DSPA), March 30-April 1, 2022, Moscow,Russian Federation. New York:IEEE Xplore, 2022:1-4.
[17] JI D, LIU Y X, WANG C. Research on image edge detection based on improved canny operator[C]//Proceedings of the 2022 3rd International Conference on Information Science, Parallel and Distributed Systems(ISPDS), July 22-24, 2022, Guangzhou, China. New York:IEEE Xplore,2022:229-232.
[18]姚志成，侯范，杨剑，等.基于时频能量对消的跳频信号参数盲估计[J].电光与控制，2022, 29(9):58-63.YAO Z C, HOU F, YANG J, et al. Blind estimation of frequency hopping signal parameters based on time-frequency energy cancellation[J]. Electronics Optics&Control, 2022, 29(9):58-63.(in Chinese)
Basic Information:
DOI：10.12194/j.ntu.20241109001
China Classification Code:TN914.41
Citation Information:
[1]万凯,常诚,侯长波等.基于改进时频脊线的跳频参数盲估计算法[J].南通大学学报(自然科学版),2025,24(02):48-55.DOI:10.12194/j.ntu.20241109001.
Fund Information:
国家自然科学基金项目（U23A20271）