双曲调频(Hyperbolic Frequency Modulation,HFM)波形是传统主动声呐常用的信号波形,具有多普勒不变性。HFM信号虽然便于匹配,但无法进行准确的测速、测距。升降HFM组合的V型双曲调频(V-Hyperbolic Frequency Modulation,V-HFM)脉冲信号...双曲调频(Hyperbolic Frequency Modulation,HFM)波形是传统主动声呐常用的信号波形,具有多普勒不变性。HFM信号虽然便于匹配,但无法进行准确的测速、测距。升降HFM组合的V型双曲调频(V-Hyperbolic Frequency Modulation,V-HFM)脉冲信号,可以解决HFM的距离-速度耦合模糊问题,但在多目标情况下会有虚假亮点干扰问题。受V-HFM组合方式启发,文章提出一种新的HFM组合方法:N型双曲调频(N-Hyperbolic Frequency Modulation,N-HFM)组合信号。该信号形式可以降低虚假亮点出现的概率。水池实验表明:在多目标情况下,N-HFM脉冲信号可以实现距离和速度二维检测的较高分辨力,以及较强的抑制虚假目标的能力。展开更多
Seismic signal is generally employed in moving target monitoring due to its robust characteristic.A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural...Seismic signal is generally employed in moving target monitoring due to its robust characteristic.A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network.For analyzing the seismic signal of the moving objects,the seismic signal of person and vehicle was acquisitioned from the seismic sensor,and then feature vectors were extracted with combined methods after filter processing.Finally,these features were put into the improved BP neural network designed for effective signal classification.Compared with previous ways,it is demonstrated that the proposed system presents higher recognition accuracy and validity based on the experimental results.It also shows the effectiveness of the improved BP neural network.展开更多
文摘双曲调频(Hyperbolic Frequency Modulation,HFM)波形是传统主动声呐常用的信号波形,具有多普勒不变性。HFM信号虽然便于匹配,但无法进行准确的测速、测距。升降HFM组合的V型双曲调频(V-Hyperbolic Frequency Modulation,V-HFM)脉冲信号,可以解决HFM的距离-速度耦合模糊问题,但在多目标情况下会有虚假亮点干扰问题。受V-HFM组合方式启发,文章提出一种新的HFM组合方法:N型双曲调频(N-Hyperbolic Frequency Modulation,N-HFM)组合信号。该信号形式可以降低虚假亮点出现的概率。水池实验表明:在多目标情况下,N-HFM脉冲信号可以实现距离和速度二维检测的较高分辨力,以及较强的抑制虚假目标的能力。
基金Project(61201028)supported by the National Natural Science Foundation of ChinaProject(YWF-12-JFGF-060)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(2011ZD51048)supported by Aviation Science Foundation of China
文摘Seismic signal is generally employed in moving target monitoring due to its robust characteristic.A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network.For analyzing the seismic signal of the moving objects,the seismic signal of person and vehicle was acquisitioned from the seismic sensor,and then feature vectors were extracted with combined methods after filter processing.Finally,these features were put into the improved BP neural network designed for effective signal classification.Compared with previous ways,it is demonstrated that the proposed system presents higher recognition accuracy and validity based on the experimental results.It also shows the effectiveness of the improved BP neural network.
