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Open set HRRP recognition based on convolutional neural network

Open set HRRP recognition based on convolutional neural netw...

引用

IET International Radar Conference 2018, IRC 2018

作者： Chen, Wei Wang, Yanhua Song, Jia Li, Yang School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China

Most existing algorithms in high-resolution range profile recognition focus on the closed set cases, where the test sample is from a known class. However, a sample could be drawn from unknown classes in realistic scenario, which is named as open set recognition. Here, open set HRRP recognition is achieved by incorporating extreme value theory into convolutional neural network. The softmax layer is replaced by a so-called openmax layer which estimates probabilities of the test sample belonging to known and unknown classes. Experimental results demonstrate that the proposed method outperforms the state-of-art algorithms such as NN, 1-vs-set machine, and W-SVM in terms of correct rejection rate. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Convolution

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Long-term tracking with fast scale estimation and efficient re-detection

Long-term tracking with fast scale estimation and efficient ...

引用

IET International Radar Conference 2018, IRC 2018

作者： Zengshuo, Zhang Linbo, Tang Yuqi, Han Jinghong, Nan Baojun, Zhao School of Information and Electronic Beijing Institute of Technology China Beijing Key laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing100081 China

In long-term tracking applications, occlusion and scale variation are common attributes which cause performance degradation. Existing solutions use heavy calculation to deal with these problems, without considering the real-time implementation. Therefore, the authors propose a novel long-term tracker with fast scale estimation and efficient re-detection scheme to maintain real-time speed and favourable accuracy. Specifically, the authors integrate a distance metric method into correlation filter-based tracker to realise fast translation calculation and scale estimation. In addition, the authors advocate a keypoint-matching based confidence indicator to verify the tracking result and activate the re-detection module when the occlusion happens. The authors test our approach on challenging sequences with scale variation and occlusion. Experiments demonstrate that our proposed tracker procures preferable effect than state-of-the-art methods in the aspect of both speed and accuracy. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： real time control

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Compressed spatial-spectral feature representation for hyperspectral ground classification

Compressed spatial-spectral feature representation for hyper...

引用

IET International Radar Conference 2018, IRC 2018

作者： Shichao, Zhou Baojun, Zhao Linbo, Tang Wenzheng, Wang School of Information and Electronic Beijing Institute of Technology China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China

The difficulty of classification tasks in hyperspectral imagery (HSI) strongly depends on the representation of spectral or spatial information. Vast amounts of approaches have been proposed to deal with spectral and spatial feature extraction, respectively. However, most of the methods neglect the inherent relationships between them. Inspired by the extreme learning machine (ELM) theory, the authors propose a new fusion-ELM framework for multiple sources representation learning and fusion. The resultant features are utilised to deal with HSI classification. With the multiple network channels and aggregation layers, the presented scheme could achieve spatial and spectral feature representations of inputs, respectively, and obtain optimal joint feature. Experimental results show that their fusion-model leads to decent improvements in classification accuracy over spectral-only, spatial-spectral-joint model and deep learning framework on two hyperspectral benchmarks. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Classification (of information)

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Feature Enhanced Centernet for Object Detection in Remote Sensing Images

Feature Enhanced Centernet for Object Detection in Remote Se...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Tong Zhang Guanqun Wang Yin Zhuang He Chen Hao Shi Liang Chen Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Multi-scale object detection in optical remote sensing imagery is a challenging task due to the varied object scales. Existed state-of-art object detection methods have achieved significant growth. However, most of the methods are based on default anchors, which need to be predefined. The multi-scale object detection accuracy still needs to be improved, especially for small and dense objects. To improve the robustness of the detection algorithm and the performance of multi-scale object detection, a novel anchor-free multi-scale object detection method Feature Enhanced CenterNet is proposed in this paper. First, we use the “encoder-decoder” structure and introduce horizontal connections to enhance feature representation capabilities. Second, an context-aware up-sampling method is proposed to obtain feature maps with suitable scale. To demonstrate the performance of the proposed method, we perform abundant experiments on the public remote sensing datasets. The experimental results demonstrate the robustness and effectiveness of the proposed method.

关键词： Object detection Feature extraction Detectors Robustness Optical imaging Convolution Semantics

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Point spread character based low SNR single pixel infrared target detection

Point spread character based low SNR single pixel infrared t...

引用

IET International Radar Conference 2018, IRC 2018

作者： Nan, Jinghong Zhao, Baojun Tang, Linbo Zhang, Zengshuo Tang, Wei Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

Robust and efficient low signal-to-noise ratio (SNR) single pixel infrared (IR) target detection has been a key technique in IR searching and tracking system. However, there exist two critical difficulties, i.e. noise disturbance and low contrast between target and background, influencing detection accuracy. A novel IR target detection method is proposed to overcome those difficulties, by utilising the point-spread character. Specifically, a point-spread indicator is advocated to protect the potential target with the median filter to suppress the noise. Afterwards, a two-step enhancement model is built to increase the contrast value between target region and surrounding background effectively. In the first step, a point-spread local contrast method is proposed to enhance targets and suppress background. In the second step, a high boost filter is introduced to further enhance the target. In addition, an adaptive segmentation method is exploited to extract targets from the enhanced image. Experimental results on testing sequences demonstrate that this method outperforms the other state-of-the-art methods in single pixel IR target detection with higher detection rate, lower false alarm rate and less time consuming. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Median filters

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Hierarchical ship detection method for space-borne SAR image

Hierarchical ship detection method for space-borne SAR image

引用

IET International Radar Conference 2018, IRC 2018

作者： Tang, Wei Zhao, Baojun Tang, Linbo Nan, Jinghong Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

Ship detection from space-borne SAR image is a challenging task. The main challenges in this task include the disturbance of sea clutter, island, coastline, and variability in ship sizes. Here, the authors propose a novel hierarchical ship detection framework to overcome the above challenges. Initially, the edge-enhanced maximally stable extremal regions (E-MSER) is employed as ship candidates. Then, through some simple shape analysis, they can eliminate the obvious false alarms which are not conformed to the shape feature of ship. Finally, candidates are represented by an effective multiple features learning framework for discriminating true ship targets. Experimental results on numerous space-borne SAR images demonstrate their proposed scheme that outperforms other traditional methods with higher detection accuracy and lower false alarm. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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Imaging algorithm for multi-channel scan synthetic aperture radar with channel error estimation and compensation

Imaging algorithm for multi-channel scan synthetic aperture ...

引用

IET International Radar Conference 2018, IRC 2018

作者： Xiao, Feng Ding, Zegang Ke, Meng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Radar Research Lab. School of Information and Electronics Beijing Institute of Technology Beijing100081 China

The wide swath synthetic aperture radar (SAR) imaging with a fine resolution is fundamentally a contradiction in conventional SAR imaging. To meet the demand of high-resolution width swath (HRWS) imaging, multi-channel scan mode has received a great deal of attention as a promising concept to realise HRWS observation. In this article, based on extended Chirp Scaling algorithm, an imaging algorithm for multi-channel scan SAR is proposed. Furthermore, channel error estimation and compensation are the key point in multi-channel scan imaging and are integrated into the proposed imaging algorithm. The computer simulation is shown to verify the presented imaging algorithm. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Error compensation

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Parameter inversion algorithm of CSAR moving target based on PFA sub-aperture images

Parameter inversion algorithm of CSAR moving target based on...

引用

IET International Radar Conference 2018, IRC 2018

作者： Yao, Di Wang, Zhou Yang, Wengu Li, Feng Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

Circular SAR (CSAR) as a new kind of SAR imaging mode has the advantage of long-time observation. For the moving target, the corresponding parameters of the moving target can be calculated by using the position information from the apparent coordinates of the moving target in these CSAR sub-aperture images. The CSAR sub-aperture imaging algorithms include BP and PFA, and the existing parameter estimation model is established on those well-focused and localised images. However, they account for a substantial computation. Here, an improved algorithm for parameter estimation based on CSAR sub-aperture images obtained by PFA is proposed. The wave-front phase error compensation is abandoned, and a new parameter estimation model is established based on PFA images with geometric positioning error. The computational complexity of the whole process of the algorithm is reduced, and the practicability is improved. The point target simulation shows that the method is effective and accurate. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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Fast Digital Beamforming for Conformal Array

Fast Digital Beamforming for Conformal Array

引用

2019 IEEE International Conference on Signal, information and Data processing, ICSIDP 2019

作者： Lu, Yiling Xiang, Yin Zhao, Yikun DIng, Zegang School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9781728123455

The conventional digital beam forming (DBF) for conformal array needs to scan a series of look angles with small angular separation to obtain a high-resolution pattern. Inspired by the fast back projection algorithm (FBP)[3] for SAR imaging, a fast DBF algorithm for the conformal array is proposed in this paper. Firstly, the conformal array is divided into several subarrays, and the pattern of each subarray is formed in a coarse resolution. Then, the pattern of each subarray is interpolated to a high resolution one by FFT. Finally, all subarrays' high-resolution pattern is added together to form the pattern of the whole array. The simulation results have proved the efficiency and accuracy of the proposed algorithm. © 2019 IEEE.

关键词： Beamforming

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Rotation error analysis on slant 45° dual polarisation radar feature extraction

Rotation error analysis on slant 45° dual polarisation rada...

引用

IET International Radar Conference 2018, IRC 2018

作者： Zhang, Liang Wang, Yanhua Li, Yang Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing China

Polarisation is an inner property of electromagnetic wave. It has considerable significance to analyse the polarimetric feature of targets in target recognition and classification applications. Slant 45° dual polarisation measurement is widely used due to its low requirements on system complexity and data rate on the one hand, and good polarisation measure and anti-interference capabilities on the other. However, its performance is seriously affected by rotation angle of the polarisations in transmission and reception. Here, the impact of rotation error of the transmit-receive polarisations on feature extraction is assessed by theoretical derivation at first. The variations with rotation angles of the transmit-receive polarisations are then simulated using standard scatterers and ground targets data. This permits quantification of the resulting rotation error on slant 45° dual polarisation measurement. The impact of the rotation error on H/α and polarimetric similarity features is also quantified in results. Some practical advices on system design, calibration, and feature application are given at last. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Rotation

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