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294 |
Lei Wentai, Liang Qiong, Tan Qianying |
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A New Ground Penetrating Radar Signal Denoising Algorithm Based on Automatic Reversed-phase Correction and Kurtosis Value Comparison |
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When using Ground Penetrating Radar (GPR) on the occasion of complex underground medium detection, radar echo can be easily affected by various noise. In order to improve GPR detection resolution and data interpretation quality, this paper proposed a new GPR denoising algorithm based on automatic reversed-phase correction and kurtosis value comparison. GPR echo signal and random noise with the same length were fitted and two signals can be obtained. By using Independent Component Analysis (ICA) algorithm, these two signals can be decomposed into two other signals, one with high kurtosis named S1 and one with low kurtosis named S2. S1 signal's phase was determined and automatic phase correction was carried out. By using Complete Ensemble Empirical Mode Decomposition (CEEMD) algorithm, S1 after automatic phase correction was decomposed, several Intrinsic Mode Function (IMF) can be obtained and kurtosis value of each IMF can be calculated. S2 signal's kurtosis value was set as a threshold. The IMFs whose kurtosis values are lower than this threshold are classified as noise components, while the other IMFs whose kurtosis values are higher than this threshold are classified as signal components. By summing the IMFs of signal components, GPR echo signal can be reconstructed and denoising. This new GPR denoising algorithm solves the problems of phase uncertainty in ICA and manual IMF components classification in CEEMD and thus improves GPR denoising effects with higher computation efficiency. The effectiveness of the proposed algorithm is verified by simulation and real data processing experiments.
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2018 Vol. 7 (3): 294-302
[Abstract]
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315
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[PDF 1502KB]
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677
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313 |
Li Yuqian, Yi Jianxin, Wan Xianrong, Liu Yuqi, Zhan Weijie |
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Helicopter Rotor Parameter Estimation Method for Passive Radar |
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The passive radar is a new radar system based on third-party non-cooperative radiation sources, which has unique advantages in micro-Doppler target classification and recognition. Its characteristics determine that the micro-Doppler effect parameter estimation method must have a good anti-noise performance and a small amount of calculation. In view of these considerations, this study presents a new idea of helicopter rotor parameter estimation using an echo flicker in the time-frequency domain based on the micro-motion signal model for the passive radar. The echo flicker parameters are extracted by accumulating the amplitudes of the positive and negative frequency axis data in the time-frequency diagram. The dictionary matrix is constructed based on the inherent characteristics of the micro-motion signals. The blade length, blade number, rotor speed, and other parameters are estimated using the orthogonal matching pursuit algorithm. Compared with the method based on the conventional Hough transform, the proposed method is more accurate and more rapid. The simulation and experimental results prove the feasibility of this method.
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2018 Vol. 7 (3): 313-319
[Abstract]
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280
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[PDF 1469KB]
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823
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346 |
Fan Huaitao, Zhang Zhimin, Li Ning |
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Channel Phase Mismatch Calibration for Multichannel in Azimuth SAR Imaging Based on Eigen-structure Method |
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As one of the most important means to achieve a High-Resolution and Wide-Swath (HRWS) imaging of the earth, multichannel in azimuth Synthetic Aperture Radar (SAR) have attracted considerable attention in recent years. However, prior to the unambiguous reconstruction of the multichannel SAR signal, each channel needs to be well calibrated, otherwise the performance of the reconstruction processor may degrade or even lose its effectiveness. Accurate baseband Doppler centroid estimation are critical for channel mismatch calibration and high-resolution imaging in the multichannel SAR systems. However, in the multichannel HRWS SAR system, the signal acquired by each channel is under-sampled that renders the traditional Doppler centroid estimation methods obsolete. In this paper, an eigen-structure method has been used to achieve a robust estimation of the baseband Doppler centroid and the phase mismatch in the multichannel SAR system. Processing with simulated and experimental C-band, four-channel airborne SAR data validates the effectiveness of this method.
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2018 Vol. 7 (3): 346-354
[Abstract]
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353
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[PDF 4070KB]
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1335
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355 |
Wang Song, Zhang Fubo, Chen Longyong, Liang Xingdong |
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Array-interferometric Synthetic Aperture Radar Point Cloud Filtering Based on Spatial Clustering Seed Growth Algorithm |
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By arranging multiple antennas in the intersection direction and combining the synthetic aperture of azimuth direction and large bandwidth signal with oblique distance, array-interferometric Synthetic Aperture Radar (SAR) can generate a three-dimensional resolution and ensure the elevation spacial sampling due to its multiple array element, which could avoid the layover problem in surveying and mapping in the Interference SAR (InSAR) and realize the three-dimensional imaging of the observation scene. However, considering the existence of too much noise in the three-dimensional point cloud distribution in the scene area and the large elevation error, the traditional Light Detection And Ranging (LiDAR) point cloud filtering method is not suitable for the filtering processing of the array-interferometric SAR point cloud. In order to solve this problem, an array-interferometric SAR point cloud filtering algorithm based on spatial clustering seed growth algorithm is proposed, in which the density-elevation image is generated by the double threshold of density and elevation, the small clutter is removed by image processing, and the vegetation is removed from the point cloud data by using the spatial clustering seed growth algorithm, thus the point cloud filtering process is completed. Using the first airborne array-interferometric SAR experimental data, the validity of the proposed algorithm is verified compared to the traditional LiDAR filtering method, which provides the guarantee for the subsequent building extraction and meticulous treatment.
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2018 Vol. 7 (3): 355-363
[Abstract]
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387
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[PDF 3997KB]
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739
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| Special Topic Papers: Millimeter Wave Radar |
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364 |
Xu Zhihuo, Shi Quan, Sun Ling |
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Novel Orthogonal Random Phase-Coded Pulsed Radar for Automotive Application(in English) |
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In contrast to remote sensing radar, automotive radar focuses on the detection of short-range targets in the 0-1000 m range. Conventional automotive pulsed radar usually uses a monostatic antenna and it requires high peak power for the transmission of the short duration pulses to reliably detect targets at close range with a high resolution. Unfortunately, it is difficult and expensive to generate high-powered pulses on the nanosecond scale. Meanwhile, the existing automotive radars suffer from bottlenecks, i.e., spatial resolution, sidelobe levels, and Inter-Sensor Interference (ISI). To overcome the above challenges, a bistatic antenna to transmit and receive large time-bandwidth product waveforms is firstly proposed in this paper. Secondly, high spatial resolution is implemented using a Digital Beam Forming (DBF) transmitter and the high range resolution is achieved by using the pulse compression technique. Additionally, the radial velocity of the target is calculated by applying pulse Doppler processing. Finally, to deal with the sidelobe effect of impulse response function of point target and the interference arising from neighboring radars, novel Orthogonal Random Phase-Coded (ORPC) radar signals are presented. Using these ORPC signals, the impulse response function of the radar can achieve a peak sidelobe ratio of -45 dB without any loss in the signal-to-noise ratio. Most importantly, interference can be significantly reduced by using the proposed signals. Extensive simulations demonstrate the effectiveness and advantages of the proposed radar.
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2018 Vol. 7 (3): 364-375
[Abstract]
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366
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[PDF 1047KB]
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991
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376 |
Tian He, Li Daojing, Qi Chunchao |
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Millimeter-wave Human Security Imaging Based on Frequency-domain Sparsity and Rapid Imaging Sparse Array Architecture |
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This paper examines the processing of millimeter-wave imaging data based on sparse sampling and sparse array design for the rapid imaging of human security data. First, based on the cylindrical scanning imaging model, the Barker code-based randomly sparse sampling method is employed to reduce the scanning time. Then, a three-dimensional imaging algorithm based on interferometry and compressed sensing in the frequency domain is proposed, with sparse representation of the image in the frequency domain after interferometry and Compressed Sensing measurement model, to recover the image frequency spectrum, thereby implementing human security image reconstruction via sparse sampling. Real data processing results indicated that the proposed method could obtain image resolution and performance similar to those of complete samples and that the image correlation coefficients before and after sparse sampling were better than 0.9, with 50% time/data reduction. Furthermore, based on the Barker codes and multistatic work mode, a sparse array architecture for rapid imaging was designed with a sparse rate of 94.6% and the guarantee of imaging quality. The proposed method was found to considerably increase the passage rate and reduce the amount of radiation unit and system complexity, marking its application significance and market prospect in security clearance.
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2018 Vol. 7 (3): 376-386
[Abstract]
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548
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[PDF 2847KB]
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1089
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