The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based de...The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based detection method is proposed for the detection of weak harmonic signal. The EKF method avoids matrix inversion by iterating measurement equation and state equation, which simultaneously improves the robustness and reduces the complexity. Compared with the existing detection methods, the proposed method has the following advantages: 1) it has better performance than the neural network method;2) it has similar performance with the optimal filtering method, but with lower computational complexity;3) it is more robust compared with the optimal filtering method.展开更多
Due to the strong electromagnetic interferences and human interference,traditional electromagnetic methods cannot obtain high quality resistivity data of mineral deposits in Chinese mines.The wide field electromagneti...Due to the strong electromagnetic interferences and human interference,traditional electromagnetic methods cannot obtain high quality resistivity data of mineral deposits in Chinese mines.The wide field electromagnetic method(WFEM),in which the pseudo-random signal is taken as the transmitter source,can extract high quality resistivity data in areas with sever interference by only measuring the electric field component.We use the WFEM to extract the resistivity information of the Dongguashan mine in southeast China.Compared with the audio magnetotelluric(AMT)method,and the controlled source audio-frequency magnetotelluric(CSAMT) method,the WFEM can obtain data with higher quality and simpler operations.The inversion results indicate that the WFEM can accurately identify the location of the main ore-body,which can be used for deep mine exploration in areas with strong interference.展开更多
静止无功发生器(Static Var Generator,SVG)微弱谐波信号处于强干扰区域的中心频带时,会影响谐波信号检测有效性。为提升谐波信号检测性能,提出强干扰下的SVG微弱谐波信号传感检测方法。在强干扰下提取出SVG信号,并采用修正投影阻塞法消...静止无功发生器(Static Var Generator,SVG)微弱谐波信号处于强干扰区域的中心频带时,会影响谐波信号检测有效性。为提升谐波信号检测性能,提出强干扰下的SVG微弱谐波信号传感检测方法。在强干扰下提取出SVG信号,并采用修正投影阻塞法消除SVG信号中存在的干扰。选取振动传感器作为SVG微弱谐波信号检测仪器,由于振动传感器中的仪表放大器会对放大后的SVG信号叠加较多高频噪声,所以在强干扰抑制的基础上进一步滤除噪声。将振动传感器放置在振动台上,并检测处理后的SVG信号。通过数字示波器观测SVG微弱谐波信号在放大电路中的输出波形,判断信号在输送期间是否出现失真问题,从而实现SVG微弱谐波信号传感检测。实验结果表明,所提方法的信噪比高于23.51 dB,幅值检测误差低于0.63 Hz,频率检测误差低于7.1 Hz。展开更多
In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series...In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.展开更多
针对强干扰背景下的二维微弱信号波达方向(Direction of Arrival,DOA)估计问题,提出了一种基于修正投影阻塞的算法。该算法通过构造干扰子空间的正交投影矩阵作为干扰阻塞矩阵,对接收阵列信号做预处理,从而达到抑制干扰的目的。本文对...针对强干扰背景下的二维微弱信号波达方向(Direction of Arrival,DOA)估计问题,提出了一种基于修正投影阻塞的算法。该算法通过构造干扰子空间的正交投影矩阵作为干扰阻塞矩阵,对接收阵列信号做预处理,从而达到抑制干扰的目的。本文对提出的修正投影阻塞法进行了理论分析,并在常见二维阵型(如面阵、十字阵、Y阵)上进行仿真和性能对比,仿真结果表明:该方法无需已知干扰角度,在多个干扰条件下能有效估计弱信号的波达方向,且不损失自由度。展开更多
基金the National Natural Science Foundation of China (Grant No. 61871102 and 61731006)Sichuan province science and technology support program under Grant N0. 2017GZ0345.
文摘The traditional methods of weak harmonic signal detection under strong chaotic interference often suffer from high computational complexity and poor performance. In this paper, an Extended Kalman Filter (EKF) based detection method is proposed for the detection of weak harmonic signal. The EKF method avoids matrix inversion by iterating measurement equation and state equation, which simultaneously improves the robustness and reduces the complexity. Compared with the existing detection methods, the proposed method has the following advantages: 1) it has better performance than the neural network method;2) it has similar performance with the optimal filtering method, but with lower computational complexity;3) it is more robust compared with the optimal filtering method.
基金Project(2018YFC0807802)supported by the National Key R&D Program of ChinaProject(41874081)supported by the National Natural Science Foundation of China
文摘Due to the strong electromagnetic interferences and human interference,traditional electromagnetic methods cannot obtain high quality resistivity data of mineral deposits in Chinese mines.The wide field electromagnetic method(WFEM),in which the pseudo-random signal is taken as the transmitter source,can extract high quality resistivity data in areas with sever interference by only measuring the electric field component.We use the WFEM to extract the resistivity information of the Dongguashan mine in southeast China.Compared with the audio magnetotelluric(AMT)method,and the controlled source audio-frequency magnetotelluric(CSAMT) method,the WFEM can obtain data with higher quality and simpler operations.The inversion results indicate that the WFEM can accurately identify the location of the main ore-body,which can be used for deep mine exploration in areas with strong interference.
基金supported by the Natural Science Foundation of Chongqing Science & Technology Commission,China (Grant No.CSTC2010BB2310)the Chongqing Municipal Education Commission Foundation,China (Grant Nos.KJ080614,KJ100810,and KJ100818)
文摘In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.
文摘针对强干扰背景下的二维微弱信号波达方向(Direction of Arrival,DOA)估计问题,提出了一种基于修正投影阻塞的算法。该算法通过构造干扰子空间的正交投影矩阵作为干扰阻塞矩阵,对接收阵列信号做预处理,从而达到抑制干扰的目的。本文对提出的修正投影阻塞法进行了理论分析,并在常见二维阵型(如面阵、十字阵、Y阵)上进行仿真和性能对比,仿真结果表明:该方法无需已知干扰角度,在多个干扰条件下能有效估计弱信号的波达方向,且不损失自由度。
