- 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) - Spacecraft Detection Based on Deep Convolutional Neural Network
摘要： Spacecraft detection is one of essential issues on aerospace information processing and control, and can provide reliable dynamic state of target, so as to support decisions made on target recognition, classification, catalogue, et al. Although numerous spacecraft detection methods exist, most of them cannot achieve real-time detection, and are still lack of better accuracy and fault-tolerance for different scenes. Recently, deep learning algorithms have achieved fantastic detection performance in computer vision community, especially the regression-based convolutional neural network YOLOv2, which has good accuracy and speed, and outperforming other state-of-the-art detection methods. This paper for the first time applies CNN to the detection of spacecraft and sets up a dataset for target detection in space. Our method starts with image annotation and data augmentation, and then uses our improved regression-based convolutional neural network YOLOv2 to detect spacecraft in an image. The experimental results have shown that our algorithm achieves 97.8% detection rate in the test set, and the average detection time of each image is about 0.018s, which has lower time overhead and better robustness to rotation and illumination changes of spacecraft.
关键词： Spacecraft,CNN,Target detection,YOLOv2
更新于2025-09-23 15:23:52
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Co-polarization channel imbalance phase estimation by corner-reflector-like targets
摘要： Polarimetric calibration is a critical step to suppress the potential system distortion before implementing any applications for polarimetric synthetic aperture radar (PolSAR). Among all the distortion elements, the crosstalk and cross-pol channel imbalance are generally estimated by the use of natural media, and the co-pol channel imbalance is traditionally solved by the use of corner reflectors (CRs). However, the deployment of ground CRs is costly and may even be impossible in some areas. Many bright point targets, such as poles, lamps, and corner points of structures, are commonly found in manmade regions. In particular, if the object orientation is parallel or perpendicular to the radar flight direction, some points will present similar polarimetric responses to trihedral or dihedral CRs. These points, which are referred to here as "CR-like targets", can be treated as a supplement to approximately solve the system distortion elements when CRs are unavailable. In this paper, we propose a novel step-by-step algorithm to determine the CR-like targets and estimate the co-pol channel imbalance phase in uncalibrated PolSAR imagery. Chinese X-band airborne and C-band satellite PolSAR data were used to test the proposed method. Compared with the CR-derived co-pol channel imbalance phase, the solution errors of the CR-like targets were 1.305° and 0.03° for the X- and C-band experiments, respectively. The results of the experiments confirm that the solutions of the CR-like targets are very close to those of ground-deployed CRs, and the proposed method can be considered as an effective way to calibrate PolSAR images when sufficient CR-like point targets are detected in manmade regions.
关键词： Corner reflector,Polarimetric synthetic aperture radar,Calibration,Target detection
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) - Qingdao, China (2018.9.14-2018.9.16)] 2018 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) - A Real-time Detection Algorithm for Unmanned Aerial Vehicle Target in Infrared Search System
摘要： Aiming at the difficulty of infrared target detection of 'low and slow small' unmanned aerial vehicles (UAV) in complex low-altitude background, this paper proposes a new target detection algorithm based on multiscale fusion filtering. Combined with spatial multiscale decomposition filtering and temporal multiscale difference processing, the algorithm can effectively overcome many difficulties such as complex low-altitude background interference, unknown target scale, unknown angular velocity and low target signal-to-noise ratio (SNR). The test result shows that the algorithm can effectively detect the UAV targets with different distances in complex low-altitude background, and the false alarm rate is low. The algorithm is realized in TI 6657 DSP and realizes 100Hz real-time processing of mid-wave infrared images with 640*512 resolution, which has been effectively applied to the large-field circumferential scanning infrared search system developed by ATR Lab.
关键词： real-time algorithm,multiscale fusion filtering,UAV target detection,low-altitude background,low and slow small targets
更新于2025-09-23 15:23:52
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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 - Processing a New Hyperspectral Data Set for Target Detection and Atmospheric Compensation Algorithm Assessment: The RIT2017 Data Set
摘要： This paper introduces a new and challenging hyperspectral dataset to the remote sensing community called the 'RIT2017 Data Set' which can be used for the assessment of target detection algorithms. This dataset encompasses 90 targets in a background of up to 8 million pixels (or less if sub-setting). The same dataset can also be used for atmospheric compensation studies for it has identical sets of large panels in both the sun and full shadow. This paper briefly introduces the data collection campaign, the target objects, and addresses the radiometric fidelity of the imaging spectrometer data, which showed very good results. Lastly, the data is atmospherically compensated using an in-scene technique, which also showed fairly good results.
关键词： atmospheric compensation,physics-based modeling,hyperspectral imaging,target detection,radiative transfer
更新于2025-09-23 15:23:52
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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 - Hybrid Parametric - Nonparametric Target Detector for Hyperspectral Images
摘要： In this work a novel target detector is proposed that is nonparametric in terms of conditional probability density function (pdf) estimation and parametric with respect to the target strength of the additive model it relies upon. The variable bandwidth kernel density estimator is employed to estimate the conditional pdfs, whereas the target strength is estimated via the Maximum Likelihood approach. Experimental results over real hyperspectral data show that the detector succeeds in detecting target objects embedded in a complex background and in providing reasonable estimates for the target strengths.
关键词： nonparametric approach,kernel density estimation,additive model,target detection,Hyperspectral imaging
更新于2025-09-23 15:23:52
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Incoherent Range Walk Compensation for Spaceborne GNSS-R Imaging
摘要： Global navigation satellite system reflectometry (GNSS-R) receivers produce delay-Doppler maps (DDMs) by incoherently integrating coherent integration results. Due to system dynamics, during incoherent integration, the receiver aligns each coherent result by tracking the delay and Doppler of the specular point. This is known to cause a blurring of the spatial footprint of the Woodward ambiguity function (WAF) on the reflecting surface. In this paper, we demonstrate that the blurring of the WAF varies over the glistening zone (GZ), and even if a fixed point on the ground is tracked, blurring still occurs. We derive the expressions for the delay and Doppler change rates over the GZ and then predict the error introduced by range walk for typical GNSS-R scatterometry configurations. We find that ≈6 dB of loss is expected for a point scatterer near the edge of the GZ when a fixed point on the surface is tracked. The incoherent range walk compensation (IRWC) method is then presented for GNSS-R receivers to mitigate this loss. The IRWC method focuses the power in the DDM to the isodelay and iso-Doppler configuration occurring at the midpoint of the integration time. DDMs produced by tracking a fixed point with and without IRWC are simulated, and errors are found to be in agreement with those predicted. Spatial domain GNSS-R products will be improved with IRWC. Target detection will benefit from a larger usable swath, allowing longer tracking and detection times as a result of the increased target to clutter and noise ratio. At the same time, imaging applications will no longer suffer from a spatially variant blurring of the WAF, which limits the resolution of the estimated products. IRWC is shown to mitigate the range migration losses and improve the SNR of an imaging GNSS-R receiver by ≈6 dB near the edge of the GZ.
关键词： integration,global navigation satellite system reflectometry (GNSS-R),reflectometry,imaging,target detection,receiver,incoherent range walk compensation (IRWC),Dynamic corrections
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP) - Auckland (2018.8.5-2018.8.8)] 2018 IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP) - Moving Target Detection for THz SAR Systems Based on Multilook Processing
摘要： Compared with conventional X-band synthetic aperture radar (SAR) systems, THz SAR is more sensitive to Doppler vibration and has better detection performance for moving targets. In this paper, a moving target detection scheme is designed for terahertz SAR systems based on multilook processing. The Doppler spectrum is divided into several sub-looks and focused separately to generate corresponding sub-images. Moving targets are indicated through sharpness detection of the sub-images. The effectiveness of the proposed algorithm is veri?ed by simulated data.
关键词： terahertz,multilook processing,moving target detection,Synthetic aperture radar
更新于2025-09-23 15:23:52
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[IEEE 2018 China International SAR Symposium (CISS) - Shanghai (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - A Fast Target Detection Method for SAR Image Based on Electromagnetic Characteristics
摘要： Target detection for remote sensing images which contain optical images and radar images has attracted lots of relative researchers. With the development of deep learning, target detection for optical images has been developing towards high accuracy and real-time detection. High resolution optical images reflect geometric features of the object. Unlike optical images, SAR images reflect the electromagnetic characteristics of the target, so the SAR image detection which uses optical image detection algorithm will lead to weak detection performance. This paper studies a fast target detection algorithm for SAR images which fused electromagnetic characteristics and geometric features through support vector machine. The algorithm is based on the Faster R-CNN framework enabling nearly cost-free target detection.
关键词： real-time detection,scattering center model,electromagnetic characteristics,Faster R-CNN,target detection
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Target Detection Algorithm Based on Chamfer Distance Transform and Random Template
摘要： To complete the target detection task in the scene of a few target samples and low configuration software running environment, a target detection algorithm based on Chamfer distance transformation and random template is proposed in this paper. Firstly, construct the multi-level pyramids of the images to be searched, add random curve segments on the original template to make multiple random templates to train the SVM and use these random templates in the subsequent template matching process; Then, perform template matching from the top level, use SVM to determine whether the target position is a correct match; Finally, map the location to the next level for finer matching positioning, repeat the process until the bottom is reached. Test results show that this algorithm runs fast and has high accuracy in positioning, which make it competitive in real application.
关键词： edge extraction,support vector machine,target detection,chamfer distance transform,random template
更新于2025-09-23 15:22:29
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Infrared Small Target Detection via Non-Convex Rank Approximation Minimization Joint l2,1 Norm
摘要： To improve the detection ability of infrared small targets in complex backgrounds, a novel method based on non-convex rank approximation minimization joint l2,1 norm (NRAM) was proposed. Due to the defects of the nuclear norm and l1 norm, the state-of-the-art infrared image-patch (IPI) model usually leaves background residuals in the target image. To fix this problem, a non-convex, tighter rank surrogate and weighted l1 norm are instead utilized, which can suppress the background better while preserving the target efficiently. Considering that many state-of-the-art methods are still unable to fully suppress sparse strong edges, the structured l2,1 norm was introduced to wipe out the strong residuals. Furthermore, with the help of exploiting the structured norm and tighter rank surrogate, the proposed model was more robust when facing various complex or blurry scenes. To solve this non-convex model, an efficient optimization algorithm based on alternating direction method of multipliers (ADMM) plus difference of convex (DC) programming was designed. Extensive experimental results illustrate that the proposed method not only shows superiority in background suppression and target enhancement, but also reduces the computational complexity compared with other baselines.
关键词： infrared image,structured norm,non-convex rank approximation minimization,small target detection
更新于2025-09-23 15:22:29