- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - An Object-Based Method Based on a Novel Statistical Distance for SAR Image Change Detection
摘要： This paper introduces an object-based method based on a new statistical distance for SAR image change detection. Firstly, multi-temporal segmentation is carried out to segment two temporal SAR images simultaneously. It considers the homogeneity in two temporal images, and could generate homogeneous objects in spectral, spatial and temporal. In addition, through setting different segmentation parameters, the multi-temporal images can be segmented in a set of scales. This process exploits the advantages of OBIA that could effectively reduce spurious changes, and considers the scale of change detection task. Secondly, a multiplicative noise model called Nakagami–Rayleigh distribution is employed to describe SAR data, and then applied to Bayesian formulation. Thus, a new statistical distance that is insensitive to speckles is derived to measure the distances between pairs of parcels. Then, cluster ensemble algorithm is utilized to improve accuracy of individual result in each scale to obtain the final change detection map. Finally, multi-temporal Radarsat-2 images are employed to verify the effectiveness of the proposed method compared with other four methods.
关键词： synthetic aperture radar (SAR),multi-scale analysis,object-based image analysis,change detection
更新于2025-09-23 15:22:29
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Leakage Mitigation in Heterodyne FMCW Radar for Small Drone Detection With Stationary Point Concentration Technique
摘要： To prevent potential hazards posed by fast-evolving drones, it is of importance to develop a radar system for drone detection. Frequency modulated continuous wave (FMCW) radars are widely used for that purpose. Heterodyne architectures are preferred for them to mitigate dc offset errors. Having said that, FMCW radars suffer from permanent leakage from the transmitter into the receiver. The leakage phase noise raises the total noise floor and limits the radar sensitivity. Here, we propose a stationary point concentration (SPC) technique in order to overcome the challenges. The SPC technique concentrates the leakage phase noise on a stationary point to alleviate the impact of the noise. The technique can be realized using digital signal processing without additional hardware. The results show that the proposed technique significantly lowers the noise floor.
关键词： heterodyne,down-conversion,leakage,digital signal processing (DSP),frequency modulated continuous wave (FMCW) radar,stationary point concentration (SPC) technique,stationary point,phase noise,noise floor
更新于2025-09-23 15:22:29
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[IEEE 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Hangzhou (2018.10.18-2018.10.20)] 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Dynamic Hand Gesture Recognition Using FMCW Radar Sensor for Driving Assistance
摘要： Dynamic hand gesture recognition is very important for human-computer interaction. In vehicles, hand gesture recognition can be used as the driver's auxiliary system to achieve remote control of the instrument. To a certain extent, this system can avoid physical buttons and touch screens causing interference to the driver. In this paper, we describe a driver-assisted dynamic gesture recognition system to classify nine hand gestures based on micro-Doppler signatures obtained by 77GHz FMCW radar using a convolutional neural network (CNN). We further explore the changes in the accuracy of same gestures in a variety of experimental scenarios to help optimize the robustness of the system.
关键词： convolutional neural network,hand gesture recognition,driver assistance system,FMCW radar sensor
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Fast Sparse Representation Method for SAR Target Configuration Recognition
摘要： Focusing on the problem of the real-time implementation in sparse representation (SR) based recognition algorithm, a fast sparse representation (FSR) algorithm is presented in this paper to improve the efficiency of synthetic aperture radar (SAR) target configuration recognition. Taking the inertia variance characteristic of SAR target images over a small range of azimuth angles into consideration, training samples of each configuration are averaged. Instead of using all the training samples to establish the dictionary in SR, the average samples are utilized to construct the dictionary in FSR. A small dictionary accelerates the speed of the proposed algorithm.
关键词： sparse representation (SR),Synthetic aperture radar (SAR) images,target configuration recognition
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Fully Convolutional Network with Polarimetric Manifold for SAR Imagery Classification
摘要： Image classification performance depends on the understanding of image features and classifier selection. Owing to the special imaging mechanism, achieving precise classification for remote sensing imagery is still quite challenging. In this paper, a fully convolutional network with polarimetric manifold, is proposed for Synthetic Aperture Radar (SAR) image classification. First, the polarimetric features are extracted to describe the target information; then the feature points in high-dimension are mapped to low-dimension through the manifold structure. In this way, the effect of single manifold is equal to that of multi-layer convolution. The experimental results on SAR image data indicate that the presented manifold network can effectively separate the polarimetric features and improve the classification accuracy.
关键词： manifold structure,Synthetic Aperture Radar (SAR),image classification,convolution network
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Spaceborne Bistatic SAR Scene Simulation
摘要： Augmenting traditional spaceborne SAR sensors with additional receive-only satellites in close formation enhances the observation space, allowing for single-pass interferometry in along- and/or across-track with flexible baselines and the potential to build tomographic stacks with reduced temporal decorrelation properties. The feasibility of such add-ons is presently investigated by ESA and other national space agencies and for a variety of master satellites operating from X- to L-band. This paper presents a simulation framework for complete scenes dedicated specifically to the analysis of the additional technical requirements imposed by the bistatic SAR imaging geometry with relatively large along-track separation of illuminating master/chief and the receive-only slaves/deputies.
关键词： synchronisation,bistatic synthetic aperture radar
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Towards the Retrieval of 2-D Vessel Velocities with Single-Platform Spaceborne SAR: Experimental Results with the TerraSAR-X 2-Looks Tops Mode
摘要： In this contribution, we propose the use of 2-looks Synthetic Aperture Radar data to retrieve azimuth velocities of moving targets with a single platform. The established technique to retrieve velocities of moving targets is Along-track Interferometry (ATI), which provides a measurement of the velocity in the radar line of sight direction by employing two or more phase centers separated in the along-track direction. The use of 2-looks data allows to observe targets at two different instants of time, with a Doppler separation, enabling the retrieval of the target velocity in the azimuth direction. We introduce the 2-looks Terrain Observation by Progressive Scans (TOPS) mode, presenting the performance that can be achieved with the TerraSAR-X system. Moreover, we present experimental results with real data acquired with TerraSAR-X over coastal areas to retrieve velocities of vessels. A validation of the results with Automatic Identification System (AIS) data (ground truth) provides accuracies below 1 m/s.
关键词： Synthetic Aperture Radar (SAR),Vessel tracking,2-looks TOPS,TerraSAR-X
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Reconstruction of Full-Pol SAR Data from Partialpol Data Using Deep Neural Networks
摘要： We propose a deep neural networks based method to reconstruct full polarimetric (full-pol) information from single polarimetric (single-pol) SAR data. It consists of two parts: feature extractor which is used to obtain multi-scale multi-layer features of targets in single-pol gray image, and feature translator that converts the geometric features to defined polarimetric feature space. The proposed method is demonstrated on L-band UAVSAR of NASA/JPL images over San Diego, CA, and New Orleans LA, USA. Both qualitative and quantitative results show the reconstructed full-pol images agree well with true full-pol images, the proposed networks have a good spatial robustness. Model-based target decomposition and unsupervised classification can be used directly on constructed full-pol images.
关键词： Deep Neural Network,unsupervised classification,Polarimetric Synthetic Aperture Radar (PolSAR),SAR image colorization
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Omega-K Algorithm Based on Series Reversion and Least Square for High-Resolution Spaceborne SAR
摘要： When processing high-resolution spaceborne synthetic aperture radar (SAR) data, the orbit curvature is a key aspect that must be taken into account. The non-hyperbolic range history makes most SAR imaging approaches not suitable for the curved orbit. Based on the two-dimensional spectrum derived by series reversion (SR), a modified Omega-K algorithm (OKA) is proposed in this paper. Making use of the reference function calculated by SR, an accurate bulk compression is implemented. Following, a modified Stolt interpolation is applied based on least square (LS), to perform the residual range-variant processing efficiently. The method described can achieve satisfactory focusing results for spaceborne SAR, without a large number of computation. Point targets simulations have validated the presented research.
关键词： curved orbit,Omega-K algorithm,Spaceborne synthetic aperture radar,series reversion,least square
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Integration of SAR and GEOBIA for the Analysis of Time-Series Data
摘要： In this work, we present a new architecture for the analysis multitemporal SAR data combining classic synthetic aperture radar processing and geographical object-based image analysis. The architecture exploits the characteristics of the recently introduced RGB products of the Level-1α and Level-1β families, employing self-organizing map clustering and object-based image analysis aiming at the definition of opportune layers measuring scattering and geometric properties of candidate objects to classify. The obtained results have been compared with those given by literature and turned out to provide high degree of accuracy and negligible false alarms. The discussion is supported by an example concerning small reservoir mapping in semi-arid environment.
关键词： self-organizing map clustering,classification,object-based image analysis,multitemporal synthetic aperture radar
更新于2025-09-23 15:22:29