The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondor...The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.展开更多
Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high comp...Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.展开更多
Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction ...Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.展开更多
Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range target...Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.展开更多
针对低信噪比(signal-to-noise ratio,SNR)下跳周期估计和跳频频率估计误差较大的情况,提出了一种基于最大熵二值化时频图以及检测和定位(detection and localization,DL)-YOLOv5s的跳周期估计和跳频频率估计方法。首先,利用最大熵阈值...针对低信噪比(signal-to-noise ratio,SNR)下跳周期估计和跳频频率估计误差较大的情况,提出了一种基于最大熵二值化时频图以及检测和定位(detection and localization,DL)-YOLOv5s的跳周期估计和跳频频率估计方法。首先,利用最大熵阈值分割方法结合形态学滤波对时频图进行处理,获得清晰的最大熵二值化时频图,再通过提出的DL-YOLOv5s模型对最大熵二值化时频图中的跳频信号进行检测和定位,通过增加ASPP模块和BiFPN模块,提高跳频信号的边缘和角点检测精度,并通过BOT3模块引入多头自注意力机制,提高跳频信号的定位精度,最后得到跳频信号的坐标位置,通过坐标的对照关系完成跳周期估计和跳频频率估计。实验结果表明,相较于YOLOv5s模型,提出的DL-YOLOv5s模型精确率P提高了5%,召回率R提高了2.2%,平均精度mAP 0.5和mAP 0.5:0.9分别提高了5.1%和4.2%,相较于YOLOv7、YOLOv8等其他模型,提出的DL-YOLOv5s模型体积更小,更适用于跳频信号参数估计常用的嵌入式设备这类资源受限的环境,且相较于传统跳频信号参数估计方法,提出的方法可以有效降低低信噪比下跳周期估计和跳频频率估计的误差。展开更多
基金supported by the Program for New Century Excellent Talents in University, Ministry of Education (NCET-05-0803)
文摘The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.
基金supported by the National Natural Science Foundation of China(61671469)
文摘Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.
基金supported by the National Natural Science Foundation of China(62141108)Natural Science Foundation of Tianjin(19JCQNJC01000)。
文摘Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.
文摘Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.
