为了进一步提高雷达的探测性能,设计了线性调频–二相码(LFM-M)混合调制脉冲压缩信号。采用分类比较的方法,研究了反向传播网络、Elman网络和径向基函数(RBF)网络等3种典型神经网络在其脉冲压缩中的应用,设计了网络的结构,分析了网络的...为了进一步提高雷达的探测性能,设计了线性调频–二相码(LFM-M)混合调制脉冲压缩信号。采用分类比较的方法,研究了反向传播网络、Elman网络和径向基函数(RBF)网络等3种典型神经网络在其脉冲压缩中的应用,设计了网络的结构,分析了网络的算法。通过仿真和对脉冲压缩输出性能的研究得出,采用RBF神经网络对LFM-M码信号进行脉冲压缩,网络具有较快的收敛速度和较好的数值稳定性,可获得60 d B左右的输出主旁瓣比。展开更多
为了改善线性调频(linear frequency modulation,LFM)信号脉冲压缩输出的性能,研究了误差反向传播(back propagation,BP)神经网络在线性调频信号脉冲压缩中的应用。采用遗传算法(genetic algorithm,GA)对BP神经网络的连接权值进行训练学...为了改善线性调频(linear frequency modulation,LFM)信号脉冲压缩输出的性能,研究了误差反向传播(back propagation,BP)神经网络在线性调频信号脉冲压缩中的应用。采用遗传算法(genetic algorithm,GA)对BP神经网络的连接权值进行训练学习,该算法可克服BP网络容易陷入局部最优的缺点。仿真结果表明,GA-BP网络具有较快的收敛速度和较好的数值稳定性,在信噪比损失小于1dB的条件下,可获得60dB左右的输出主旁瓣比。展开更多
To the problem of the unknown underwater target detection, according to the feature that the underwater target radiated noise contains the stable line spectrum, a weighted method based on the main-to-side lobe ratio ...To the problem of the unknown underwater target detection, according to the feature that the underwater target radiated noise contains the stable line spectrum, a weighted method based on the main-to-side lobe ratio （MSLR） is proposed for broadband beam-forming. This weighted method can be implemented by using the following steps. Firstly, optimize the spatial spectrum of each frequency unit by the second-order cone programming （SOCP）, and obtain the optimized spatial spectrum with lower side lobe. Secondly, construct weighting factors based on the MSLR of the optimized spatial spectrums to from weight factors. Lastly, cumulate the spatial spectrum of each frequency unit via the weight statistical method of this paper. This method can restrain the disturbance of background noise, enhance the output signal-to-noise ratio （SNR）, and overcome the difficulty of traditional four-dimensional display. The theoretical analysis and simulation results both verify that this method can well enhance the spatial spectrum of line spectrum units, restrain the spatial spectrum of background noise units, and improve the performance of the broadband beam-forming.展开更多
文摘为了进一步提高雷达的探测性能,设计了线性调频–二相码(LFM-M)混合调制脉冲压缩信号。采用分类比较的方法,研究了反向传播网络、Elman网络和径向基函数(RBF)网络等3种典型神经网络在其脉冲压缩中的应用,设计了网络的结构,分析了网络的算法。通过仿真和对脉冲压缩输出性能的研究得出,采用RBF神经网络对LFM-M码信号进行脉冲压缩,网络具有较快的收敛速度和较好的数值稳定性,可获得60 d B左右的输出主旁瓣比。
文摘为了改善线性调频(linear frequency modulation,LFM)信号脉冲压缩输出的性能,研究了误差反向传播(back propagation,BP)神经网络在线性调频信号脉冲压缩中的应用。采用遗传算法(genetic algorithm,GA)对BP神经网络的连接权值进行训练学习,该算法可克服BP网络容易陷入局部最优的缺点。仿真结果表明,GA-BP网络具有较快的收敛速度和较好的数值稳定性,在信噪比损失小于1dB的条件下,可获得60dB左右的输出主旁瓣比。
基金supported by the National Natural Science Foundation of China(Grant No.61372180)the National Key Scientific Instrument Equipment Development Project of China(Grant No.2013YQ140431)
文摘To the problem of the unknown underwater target detection, according to the feature that the underwater target radiated noise contains the stable line spectrum, a weighted method based on the main-to-side lobe ratio （MSLR） is proposed for broadband beam-forming. This weighted method can be implemented by using the following steps. Firstly, optimize the spatial spectrum of each frequency unit by the second-order cone programming （SOCP）, and obtain the optimized spatial spectrum with lower side lobe. Secondly, construct weighting factors based on the MSLR of the optimized spatial spectrums to from weight factors. Lastly, cumulate the spatial spectrum of each frequency unit via the weight statistical method of this paper. This method can restrain the disturbance of background noise, enhance the output signal-to-noise ratio （SNR）, and overcome the difficulty of traditional four-dimensional display. The theoretical analysis and simulation results both verify that this method can well enhance the spatial spectrum of line spectrum units, restrain the spatial spectrum of background noise units, and improve the performance of the broadband beam-forming.
