This paper considers multi-frequency passive radar and develops a multi-frequency joint direction of arrival(DOA)estimation algorithm to improve estimation accuracy and resolution.The developed algorithm exploits the ...This paper considers multi-frequency passive radar and develops a multi-frequency joint direction of arrival(DOA)estimation algorithm to improve estimation accuracy and resolution.The developed algorithm exploits the sparsity of targets in the spatial domain.Specifically,we first extract the required frequency channel data and acquire the snapshot data through a series of preprocessing such as clutter suppression,coherent integration,beamforming,and constant false alarm rate(CFAR)detection.Then,based on the framework of sparse Bayesian learning,the target’s DOA is estimated by jointly extracting the multi-frequency data via evidence maximization.Simulation results show that the developed algorithm has better estimation accuracy and resolution than other existing multi-frequency DOA estimation algorithms,especially under the scenarios of low signalto-noise ratio(SNR)and small snapshots.Furthermore,the effectiveness is verified by the field experimental data of a multi-frequency FM-based passive radar.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
信噪比是衡量信道质量的一个重要参数,该文主要研究LTE(Long Term Evolution)系统中基于探测参考信号(Sounding Reference Signal,SRS)的信噪比估计方法。针对DASS(Difference of Adjacent Subcarrier Signal)算法在高信噪比下噪声估计...信噪比是衡量信道质量的一个重要参数,该文主要研究LTE(Long Term Evolution)系统中基于探测参考信号(Sounding Reference Signal,SRS)的信噪比估计方法。针对DASS(Difference of Adjacent Subcarrier Signal)算法在高信噪比下噪声估计误差较大的这一缺点,该文提出一种适用于SRS的改进DASS方法。该方法通过重新定义子载波的差分方式,减小了噪声估计的误差,并且由于对连续的3个SRS频点,仅需要估计一次噪声,使得该文方法的复杂度仅为原DASS方法的1/3。仿真结果表明,所提方法的估计性能优于其余的方法,特别是在低时延和中等时延信道下,高信噪比时的估计精度提高了约10倍。展开更多
针对多重信号分类(multiple signal classification,MUSIC)算法、旋转不变子空间(estimation of signal parameters via rotational invariance technique,ESPRIT)等大多数空间谱估计算法需要进行准确的信源数估计,且当信源数估计出现...针对多重信号分类(multiple signal classification,MUSIC)算法、旋转不变子空间(estimation of signal parameters via rotational invariance technique,ESPRIT)等大多数空间谱估计算法需要进行准确的信源数估计,且当信源数估计出现误差时性能易受影响的问题,提出了一种基于导向矢量信号的未知信源数波达方向(direction of arrival,DOA)估计算法。该算法通过引入导向矢量信号,以自适应波束形成中最大信噪比准则下最优权矢量对应的准最大信噪比作为来波方向估计参数,从而避免了大多数空间谱估计算法中的信源数估计并实现了各个信号来向的准确估计。对该方法进行了计算机仿真验证,仿真实验结果表明该算法是有效的。展开更多
基金supported by the National Natural Science Foundation of China(62071335,61931015,61831009)the Technological Innovation Project of Hubei Province of China(2019AAA061).
文摘This paper considers multi-frequency passive radar and develops a multi-frequency joint direction of arrival(DOA)estimation algorithm to improve estimation accuracy and resolution.The developed algorithm exploits the sparsity of targets in the spatial domain.Specifically,we first extract the required frequency channel data and acquire the snapshot data through a series of preprocessing such as clutter suppression,coherent integration,beamforming,and constant false alarm rate(CFAR)detection.Then,based on the framework of sparse Bayesian learning,the target’s DOA is estimated by jointly extracting the multi-frequency data via evidence maximization.Simulation results show that the developed algorithm has better estimation accuracy and resolution than other existing multi-frequency DOA estimation algorithms,especially under the scenarios of low signalto-noise ratio(SNR)and small snapshots.Furthermore,the effectiveness is verified by the field experimental data of a multi-frequency FM-based passive radar.
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.
文摘信噪比是衡量信道质量的一个重要参数,该文主要研究LTE(Long Term Evolution)系统中基于探测参考信号(Sounding Reference Signal,SRS)的信噪比估计方法。针对DASS(Difference of Adjacent Subcarrier Signal)算法在高信噪比下噪声估计误差较大的这一缺点,该文提出一种适用于SRS的改进DASS方法。该方法通过重新定义子载波的差分方式,减小了噪声估计的误差,并且由于对连续的3个SRS频点,仅需要估计一次噪声,使得该文方法的复杂度仅为原DASS方法的1/3。仿真结果表明,所提方法的估计性能优于其余的方法,特别是在低时延和中等时延信道下,高信噪比时的估计精度提高了约10倍。
文摘针对多重信号分类(multiple signal classification,MUSIC)算法、旋转不变子空间(estimation of signal parameters via rotational invariance technique,ESPRIT)等大多数空间谱估计算法需要进行准确的信源数估计,且当信源数估计出现误差时性能易受影响的问题,提出了一种基于导向矢量信号的未知信源数波达方向(direction of arrival,DOA)估计算法。该算法通过引入导向矢量信号,以自适应波束形成中最大信噪比准则下最优权矢量对应的准最大信噪比作为来波方向估计参数,从而避免了大多数空间谱估计算法中的信源数估计并实现了各个信号来向的准确估计。对该方法进行了计算机仿真验证,仿真实验结果表明该算法是有效的。
