- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Effect of the Double-Bounce Contribution in Polinsar-Based Height Estimates of Rice Crops Using Tandem-X Bistatic Data
摘要： In bistatic acquisitions the presence of a double-bounce contribution at the ground affects the interferometric coherence with a decorrelation factor which is usually overlooked in studies employing polarimetric SAR interferometry. The standard acquisition mode of TanDEM-X is bistatic, so the influence of this contribution in the estimation of scene parameters (ground topography and vegetation height) is studied here. The analysis is carried out both with simulations and real data acquired over rice fields during the science phase of TanDEM-X. Results show that the error in height and topography is small when incidence angle is below 30 degrees, but may become noticeable for shallower incidences.
关键词： vegetation,rice,Polarimetric SAR interferometry,bistatic radar,TanDEM-X
更新于2025-09-23 15:21:21
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[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - Target Detection and Classification of Small Drones by Boosting on Radar Micro-Doppler
摘要： Small drones, also called mini-UAVs (Unmanned Aerial Vehicles), have become very wide-spread. They have many positive applications. However, they also have negative uses and it is often necessary to detect and classify them. In this paper we employ radar micro-Doppler for detection and classification of small drones. Micro-Doppler are Doppler shifts generated by the movements of internal parts of the target. We have used radar measurements of small drones and birds, extracted physical features from TVDs (Time Velocity Diagrams), and used a boosting classifier to distinguish between drones and birds (target detection) and types of drones (target classification) with good results. We have also compared with a SVM (Support Vector Machine) classifier. Our conclusion is that Micro-Doppler radar has the potential for reliable small drone target detection and is also promising for classifying the type of drone. The boosting classifier has some advantages over SVM.
关键词： detection,boosting,drone,UAV,radar,micro-Doppler,classification
更新于2025-09-23 15:21:21
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[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - A New Antenna Array and Signal Processing Concept for an Automotive 4D Radar
摘要： On the way to Highly Automated Driving (HAD), new conditions for sensors used in vehicles arise. To achieve a highly accurate environmental perception the resolution of radar sensors has to be increased. Only with ?ne grained sensor information, is possible to maneuver safely and highly automated at all road conditions in urban and rural surroundings. A prototypical implementation of such a sensor, which ful?lls all these requirements, is presented in the following as automotive 4D radar. The relevant parts of the baseband signal processing are explained in combination with the used modulation waveform. A new antenna array arrangement is introduced which provides the ability to measure angles in both azimuth and elevation. To estimate the two angles of arrival a method which performs this in combination is exempli?ed. First measurements with a cyclist are recorded and show a radial speed enhanced 3D radar image. The ?rst results are extremely promising. For validation of the measured data, also a simulation of the same scenario with identical system parameters is performed and shown.
关键词： automotive radar,2d angular estimation,angular estimation,signal processing
更新于2025-09-23 15:21:21
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[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - Deep Learning based Human Activity Classification in Radar Micro-Doppler Image
摘要： A convolutional neural network (CNN) based deep learning (DL) approach to classify human activities in micro-Doppler spectrogram of radar is investigated. MOCAP dataset, from Carnegie Mellon University, is used for spectrogram simulation. Seven activities are classified with the proposed CNN network. Our network outperforms several previously published DL-based approaches. To understand the network’s impact on classification performance, we investigate some key parameters of the proposed network. Experiment result demonstrates that a deeper network does not necessarily result in a higher accuracy. We also examine the network size and the number of output feature maps to find out their impact on the result.
关键词： Deep Learning,Convolutional Neural Network,Human Activity Classification,Micro-Doppler Spectrogram,Radar image
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Ship Detection Based on Deep Convolutional Neural Networks for Polsar Images
摘要： In this paper, we proposed a ship detection method based on deep convolutional neural networks for PolSAR images. The proposed ship detector firstly segments PolSAR images into sub-samples using a sliding window of fixed size to effectively extract translational-invariant spatial features. Further, the modified faster region based convolutional neural network (Faster-RCNN) method is utilized to realize ship detection for ships with different sizes and fusion the detection result. Finally, the proposed method was validated using real measured NASA/JPL AIRSAR datasets by comparing the performance with the modified constant false alarm rate (CFAR) detector. The comparison results demonstrate the validity and generality of the proposed detection algorithm.
关键词： Deep convolutional neural networks,polarimetric synthetic aperture radar (PolSAR),ship detection
更新于2025-09-23 15:21:21
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[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - Expanding the Unambiguous Velocity Limitation of the Stepped-Carrier OFDM Radar Scheme
摘要： The main limitation for the practical implementation of OFDM radars is the required high sampling rate of AD/DA converters. It can be solved by using a stepped-carrier OFDM scheme. Thereby, the same range and Doppler resolution is obtained as for a standard OFDM scheme at the cost of a reduced unambiguously measurable velocity. This paper presents a method to determine the actual velocity even for targets that violate the unambiguous velocity limitation. It is based on characteristics of the DFT and it is suitable for scenes with few targets or if all targets have a similar velocity.
关键词： OFDM,radar,DFT,stepped carrier,frequency-agility,automotive
更新于2025-09-23 15:21:21
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[IEEE 2018 15th European Radar Conference (EuRAD) - Madrid, Spain (2018.9.26-2018.9.28)] 2018 15th European Radar Conference (EuRAD) - Distributed Signal Processing of High-Resolution FMCW MIMO Radar for Automotive Applications
摘要： For driving automated applications, high resolution radar systems are necessary to extract more information about different types of objects in the environment. However, a single automotive microcontroller might not be sufficient to processing high number of transmit and receive antenna channels. Hence, in this paper, a system concept for distributed signal processing of high resolution FMCW MIMO radar has been proposed to highlight the feasibility using automotive microcontrollers. The execution time and computaional/memory requirements show the feasibility of such systems for automotive safety applications.
关键词： signal processing,FMCW,high resolution radar,MIMO,automotive
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Two-Dimensional Displacement Analysis with Sar Images Based on Persistent Scatterer Clustering
摘要： In this paper, we propose a two-dimensional displacement analysis method with persistent scatterer (PS) clustering technique for monitoring ground and buildings. PS interferometry (PSI) technique measures millimetric displacement of ground and buildings, by employing stable reflection points called PSs obtained by a time-series analysis of synthetic aperture radar images. In order to extend PSI technique to two-dimensional displacement analysis, alignment and integration analysis of PSs obtained by different observation directions are needed. The proposed method integrates the PSs aligned by PS clustering, which separates the PSs corresponding to the structures assuming that displacements of the PSs on a rigid structure are similar. The PS clustering leads to an easy alignment of the PSs before the integration of displacements from different observation directions. The resulting integrated displacement analysis avoids errors caused by inappropriate interpolation in the conventional alignment method. Experimental results demonstrate that the proposed method achieves accuracy comparable with benchmarks.
关键词： clustering,persistent scatterer interferometry,synthetic aperture radar,Displacement analysis
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Annular Array 3-D Sar: Resolution Analysis and Data Processing
摘要： Array synthetic aperture radar (SAR) is one of the hot areas in radar imaging field because of its three-dimensional (3-D) imaging ability. Combining the advantages of linear array SAR in aspect of side-lobe suppression and circular SAR in aspect of high resolution, a new kind of annular array synthetic aperture radar (AASAR) mode is employed for 3-D microwave imaging. Based on the mathematical derivation of AASAR model, the sparse layout of the annular array in the cross-track direction can acquire 3-D high resolution and effective side-lobe suppression ability. Then on this basis, a proto-type AASAR experiment system is built, and some 3-D AASAR imaging outdoor experiments are conducted. Through the experiment result, the validity of 3-D AASAR imaging can be demonstrated.
关键词： 3-D imaging,annular array,high resolution,side-lobe suppression,Synthetic aperture radar
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Pr-Based Sar Reconstruction Autofocus Algorithm for Persistent Surveillance Change Detection
摘要： Random phase noises arising from frequency jitter of transmit signal and atmospheric turbulence result in corrupted synthetic aperture radar (SAR) imagery, which in turn degrades change detection (CD) performance. In this paper, a phase retrieval (PR) based SAR reconstruction autofocus framework by exploiting the hidden convexity is proposed with the goal of achieving reliable persistent surveillance CD. Firstly the original non-convex quartic SAR reconstruction is reformulated as a convex quadratic program. Under the minimum phase assumption, the auto-correlation retrieval-Kolmogorov factorization (CoRK) algorithm is then utilized to optimally and efficiently retrieve the underlying SAR reflectivity. The devised scheme possesses effective capabilities of phase noise mitigation, thus has a superior CD performance. Experimental results are provided to verify the effectiveness of the proposed method.
关键词： Synthetic aperture radar (SAR),hidden convexity,change detection (CD),phase retrieval (PR),random phase noises
更新于2025-09-23 15:21:21