Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gra...Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.展开更多
The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and ...The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.展开更多
This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail...This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.展开更多
Three-dimensional (3-D) matched filtering has been suggested as a powerful processing technique for detecting weak, moving IR point target immersed in a noisy field. Based on the theory of the 3-D matched filtering an...Three-dimensional (3-D) matched filtering has been suggested as a powerful processing technique for detecting weak, moving IR point target immersed in a noisy field. Based on the theory of the 3-D matched filtering and the optimal linear processing, the optimal point target detector is being analyzed in this paper. The performance of the detector is introduced in detail. The results provide a standard reference to evaluate the performance of any other point target detection algorithms.展开更多
A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,t...A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.展开更多
为解决带式高速导种装置导种过程中种带托片与种粒均经过监测点,无法区分脉冲变化特征,导种性能难以监测的问题,研究一种基于红外传感器的带式高速导种装置监测方法并设计了监测系统。利用其导种特性提出了双侧脉冲比较法,设计了带式高...为解决带式高速导种装置导种过程中种带托片与种粒均经过监测点,无法区分脉冲变化特征,导种性能难以监测的问题,研究一种基于红外传感器的带式高速导种装置监测方法并设计了监测系统。利用其导种特性提出了双侧脉冲比较法,设计了带式高速导种装置监测模块硬件电路与软件程序。同时通过对监测系统采样试验结果分析,提出一种基于双侧脉冲值分析与能量掩码平滑算法(Bilateral pulse value analysis and energy masking smoothing algorithm,BPV-EMSA)的带式高速导种装置监测算法。仿真试验表明:该算法减少了原始脉冲的噪声和随机波动,使数据更加平滑稳定并突出了数据主要趋势和模式,同时抑制了瞬态脉冲干扰,提升了数据可解释性和分析准确性。监测系统精度试验结果表明:所设计的带式高速导种装置监测系统在不同作业速度下最高监测精度为97.65%,最低精度为95.99%,系统能够精确采集种粒经过监测点的脉冲变化。监测系统性能评价试验结果表明:播种合格率平均监测差值为2个百分点,播种漏播率平均监测差值为1.45个百分点,播种重播率平均监测差值为0.56个百分点。播种合格率相对差值不大于2.23个百分点,播种漏播率相对差值不大于1.78个百分点,播种重播率相对差值不大于1.00个百分点。该监测方法能够准确监测带式高速导种装置的导种性能。展开更多
基金This project was supported by the National Natural Science Foundation of China (No. 49831060).
文摘Using the Radon transform and morphological image processing, an algorithm for ship's wake detection in the SAR (synthetic aperture radar) image is developed. Being manipulated in the Radon space to invert the gray-level and binary images, the linear texture of ship wake in oceanic clutter can be well detected. It has been applied to the automatic detection of a moving ship from the SEASAT SAR image. The results show that this algorithm is well robust in a strong noisy background and is not very sensitive to the threshold parameter and the working window size.
基金Supported by National Science and Technology Support Program(2014BAD06B04-1-09)China Postdoctoral Fund(2016M601406)Heilongjiang Postdoctoral Fund(LBHZ15024)
文摘The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.
文摘This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented.
文摘Three-dimensional (3-D) matched filtering has been suggested as a powerful processing technique for detecting weak, moving IR point target immersed in a noisy field. Based on the theory of the 3-D matched filtering and the optimal linear processing, the optimal point target detector is being analyzed in this paper. The performance of the detector is introduced in detail. The results provide a standard reference to evaluate the performance of any other point target detection algorithms.
基金Sponsored by the National Natural Science Foundation of China (60773129)the Excellent Youth Science and Technology Foundation of Anhui Province of China ( 08040106808)
文摘A novel classification algorithm based on abnormal magnetic signals is proposed for ground moving targets which are made of ferromagnetic material. According to the effect of diverse targets on earth's magnetism,the moving targets are detected by a magnetic sensor and classified with a simple computation method. The detection sensor is used for collecting a disturbance signal of earth magnetic field from an undetermined target. An optimum category match pattern of target signature is tested by training some statistical samples and designing a classification machine. Three ordinary targets are researched in the paper. The experimental results show that the algorithm has a low computation cost and a better sorting accuracy. This classification method can be applied to ground reconnaissance and target intrusion detection.
文摘为解决带式高速导种装置导种过程中种带托片与种粒均经过监测点,无法区分脉冲变化特征,导种性能难以监测的问题,研究一种基于红外传感器的带式高速导种装置监测方法并设计了监测系统。利用其导种特性提出了双侧脉冲比较法,设计了带式高速导种装置监测模块硬件电路与软件程序。同时通过对监测系统采样试验结果分析,提出一种基于双侧脉冲值分析与能量掩码平滑算法(Bilateral pulse value analysis and energy masking smoothing algorithm,BPV-EMSA)的带式高速导种装置监测算法。仿真试验表明:该算法减少了原始脉冲的噪声和随机波动,使数据更加平滑稳定并突出了数据主要趋势和模式,同时抑制了瞬态脉冲干扰,提升了数据可解释性和分析准确性。监测系统精度试验结果表明:所设计的带式高速导种装置监测系统在不同作业速度下最高监测精度为97.65%,最低精度为95.99%,系统能够精确采集种粒经过监测点的脉冲变化。监测系统性能评价试验结果表明:播种合格率平均监测差值为2个百分点,播种漏播率平均监测差值为1.45个百分点,播种重播率平均监测差值为0.56个百分点。播种合格率相对差值不大于2.23个百分点,播种漏播率相对差值不大于1.78个百分点,播种重播率相对差值不大于1.00个百分点。该监测方法能够准确监测带式高速导种装置的导种性能。
