In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are un...In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.展开更多
It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but th...It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.展开更多
The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a chall...The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a challenging task.Inspired by the wavelet threshold,the de-noising method for low-altitude battlefield acoustic signal based on threshold empirical mode decomposition(EMD-T)is proposed in this paper.Firstly,the noisy signal is decomposed by empirical mode decomposition(EMD)to get the intrinsic mode functions(IMFs).Then the IMFs,whose actual energy exceeds its estimated energy,are processed by the EMD threshold.Finally,the processed IMFs are summed to reconstruct the de-noised signal.To evaluate the performance of the proposed method,extensive simulations are performed using helicopter sound corrupted with four types of typical low-altitude ambient noise under different signal-to-noise ratio(SNR)input values.The performance is evaluated in terms of SNR,root mean square error(RMSE)and smoothness index(SI).The simulations results reveal that the proposed method de-noising method has the perspective of the highest SNR,smallest RMSE and SI in de-noising low-altitude ambient noise compared to other methods,including the wavelet transform(WT)and conventional EMD.展开更多
文摘In the signal processing for metrewave radar, the reflection paths of target echoes can cause severe error in the elevation estimation for the low-angle target tracking. The exact angles of the reflection paths are unknown beforehand, and therefore, the reflection paths can not be suppressed easily. Therefore, in this article, an improved reflection paths suppression approach is presented. A block matrix aggregate is constructed based on the possible angles of the reflection paths. Combined with the beamforming-like processing, a generalized maximum likelihood estimation is derived to optimize the estimation. Moreover, the noise reduction method based on the Toeplitz covariance matrix is used for better performance. This approach is applied to the real data collected by the low-angle tracking radar with 8-channel vertical array. The experiment results show that the reflection effects are reduced and the accuracy of the elevation estimate is improved.
基金supported by the National Natural Science Foundation of China(61771367)the Science and Technology on Communication Networks Laboratory(6142104190204).
文摘It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.
文摘The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a challenging task.Inspired by the wavelet threshold,the de-noising method for low-altitude battlefield acoustic signal based on threshold empirical mode decomposition(EMD-T)is proposed in this paper.Firstly,the noisy signal is decomposed by empirical mode decomposition(EMD)to get the intrinsic mode functions(IMFs).Then the IMFs,whose actual energy exceeds its estimated energy,are processed by the EMD threshold.Finally,the processed IMFs are summed to reconstruct the de-noised signal.To evaluate the performance of the proposed method,extensive simulations are performed using helicopter sound corrupted with four types of typical low-altitude ambient noise under different signal-to-noise ratio(SNR)input values.The performance is evaluated in terms of SNR,root mean square error(RMSE)and smoothness index(SI).The simulations results reveal that the proposed method de-noising method has the perspective of the highest SNR,smallest RMSE and SI in de-noising low-altitude ambient noise compared to other methods,including the wavelet transform(WT)and conventional EMD.
