35 results on '"Hongmeng Chen"'
Search Results
2. Data-driven airborne bayesian forward-looking superresolution imaging based on generalized Gaussian distribution
- Author
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Hongmeng Chen, Zeyu Wang, Yingjie Zhang, Xing Jin, Wenquan Gao, and Jizhou Yu
- Abstract
Airborne forward-looking radar (AFLR) has been more and more impoatant due to its wide application in the military and civilian fields, such as automatic driving, sea surveillance, airport surveillance and guidance. Recently, sparse deconvolution technique has been paid much attention in AFLR. However, the azimuth resolution performance gradually decreases with the complexity of the imaging scene. In this paper, a data-driven airborne Bayesian forward-looking superresolution imaging algorithm based on generalized gaussian distribution (GGD- Bayesian) for complex imaging scene is proposed. The generalized gaussian distribution is utilized to describe the sparsity information of the imaging scene, which is quite essential to adaptively fit different imaging scenes. Moreover, the mathematical model for forward-looking imaging was established under the maximum a posteriori (MAP) criterion based on the Bayesian framework. To solve the above optimization problem, quasi-Newton algorithm is derived and used. The main contribution of the paper is the automatic selection for the sparsity parameter in the process of forward-looking imaging. The performance assessment with simulated data has demonstrated the effectiveness of our proposed GGD- Bayesian algorithm under complex scenarios.
- Published
- 2023
3. Distribution and Protection of Chinese Beech under the Background of Climate Change
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Li Xiang, Hong Wang, Lei Liu, Haoxiang Zhao, Yi Huang, Hongmeng Chen, Yueqin Ma, Ying Mao, Liantong Hu, and Jinyao Hu
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Environmental Chemistry ,General Environmental Science - Published
- 2022
4. Real Aperture Radar Forward-Looking Imaging Based on Variational Bayesian in Presence of Outliers
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Weixin Li, Ming Li, Lei Zuo, Hongmeng Chen, and Yan Wu
- Subjects
General Earth and Planetary Sciences ,Electrical and Electronic Engineering - Published
- 2022
5. Bayesian Forward-Looking Superresolution Imaging Using Doppler Deconvolution in Expanded Beam Space for High-Speed Platform
- Author
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Yachao Li, Zhang Wenjie, Jizhou Yu, Liang Guo, Gao Wenquan, Hanwei Sun, and Hongmeng Chen
- Subjects
Noise (signal processing) ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Laplace distribution ,law.invention ,Convolution ,symbols.namesake ,law ,Convex optimization ,Singular value decomposition ,symbols ,General Earth and Planetary Sciences ,Deconvolution ,Electrical and Electronic Engineering ,Radar ,Doppler effect ,Algorithm - Abstract
Deconvolution technique can be utilized in the forward-looking radar (FLR). However, the forward-looking imaging performance degenerates greatly due to the effect of high-speed movement of the platform. In this article, an efficient Bayesian forward-looking superresolution imaging algorithm based on Doppler deconvolution in expanded beam space is proposed. First, the Doppler phase information caused by the high-speed platform is fully exploited and the Doppler matrix is integrated with the antenna pattern. The Doppler convolution model of the echo signal for forward-looking is derived in this article. Then, the Doppler phase information is adopted to perform the Doppler deconvolution. Moreover, an expanded beam space is constructed to enhance the sparsity of the imaging scene. The complex Gaussian distribution and the Laplace distribution have been used to model the distribution characteristics of noise and targets in the imaging scene, respectively. Finally, based on the Bayesian framework, the forward-looking imaging problem is converted into the convex optimization problem. The performance assessment based on simulated and experimental data, also in comparison to the conventional real beam, truncated singular value decomposition (TSVD), iterative adaptive approach (IAA) methods, has demonstrated the effectiveness of our proposed algorithm under high-speed platform scenarios.
- Published
- 2022
6. Sparse Superresolution Imaging for Airborne Forward-Looking Radar with Multiple Frames Space
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Hongmeng Chen, Wenquan Gao, Pei Wang, Jizhou Yu, and Yachao Li
- Published
- 2022
7. Adaptive Persymmetric Subspace Detectors in the Partially Homogeneous Environment
- Author
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Zeyu Wang, Gang Li, and Hongmeng Chen
- Subjects
Training set ,Covariance matrix ,Computer science ,Mathematics::Number Theory ,Detector ,020206 networking & telecommunications ,02 engineering and technology ,Constant false alarm rate ,law.invention ,Robustness (computer science) ,Homogeneous ,law ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Radar ,Algorithm ,Subspace topology - Abstract
This paper addresses the adaptive detection of subspace signals in the noise whose covariance matrix is unknown. The partially homogeneous scenario, where the primary data have the same noise covariance matrix with the training data up to an unknown scaling factor is considered. We exploit the persymmetric structure of the noise covariance matrix to enhance the matched detection performance in the case of limited number of training data. Three persymmetric subspace detectors are proposed by applying the generalized likelihood ratio (GLR), Rao and Wald design criteria, respectively. It is proved that the three persymmetric subspace detectors can ensure the constant false alarm rate (CFAR) property. Experimental results show that the new persymmetric subspace detectors significantly outperform the conventional subspace detector in terms of the matched detection performance. Compared with the persymmetric rank-one signal detectors, the proposed persymmetric subspace detectors are more robust in the mismatched signal case.
- Published
- 2020
8. A High-Resolution Spotlight SAR Imaging Method Based on Two-Step Processing Approach
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Hao Zheng and Hongmeng Chen
- Published
- 2022
9. Weighted Iterative Adaptive Approach for Scanning Radar Imaging
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Weixin Li, Ming Li, Lei Zuo, Hongmeng Chen, Ran Zhang, and Hao Sun
- Published
- 2021
10. Adaptive Robust Radar Target Detector Based on Gradient Test
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Zeyu Wang, Jun Liu, Hongmeng Chen, and Wei Yang
- Subjects
General Earth and Planetary Sciences - Abstract
The exact knowledge of the signal steering vector is not always known, which may result in detection performance degradation when a signal mismatch occurs. In this paper, we discuss the problem of designing a robust radar target detector in the background of Gaussian noise whose covariance matrix is unknown. To improve robustness to mismatched signals, a random perturbation that follows the complex normal distribution is added under the alternative hypothesis. Since traditional detectors that divide complex parameters into real parts and imaginary parts are sometimes difficult to obtain, a new robust, complex parameter gradient test is derived directly from the complex data. Moreover, the CFAR property of the new detector is proven. The performance assessment indicates that the gradient detector exhibits suitable robustness to the mismatched signals.
- Published
- 2022
11. Efficient knowledge‐aided target relocation algorithm for airborne radar
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Heqiang Mu, Zeyu Wang, Jing Liu, Hongmeng Chen, Yaobing Lu, Xiaoli Yi, Hanwei Sun, and Ming Li
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Synthetic aperture radar ,search radar ,Computer science ,0211 other engineering and technologies ,Phase (waves) ,Energy Engineering and Power Technology ,02 engineering and technology ,mismatch model ,Radar systems ,phase estimation ,poor relocation performance ,Radiation pattern ,law.invention ,law ,0202 electrical engineering, electronic engineering, information engineering ,radar detection ,airborne radar ,Radar ,021101 geological & geomatics engineering ,channel phase estimation ,General Engineering ,antenna pattern information ,Ground moving target indication ,020206 networking & telecommunications ,receiving channel ,radar signal processing ,airborne radar experiments ,ideal target relocation model ,dual-channel radar system ,lcsh:TA1-2040 ,wide-area ground moving target ,efficient knowledge-aided target relocation algorithm ,target tracking ,lcsh:Engineering (General). Civil engineering (General) ,Relocation ,radar clutter ,Algorithm ,channel error model ,Software ,synthetic aperture radar ,Communication channel - Abstract
This letter addresses the problem of target relocation in wide-area ground moving target indication system. The antenna pattern information is exploited as prior knowledge to enhance the performance of airborne radar. Firstly, the ideal target relocation model for moving targets based on the dual-channel radar system is analysed and the mismatch model of the receiving channel is constructed. Then the reason for poor relocation performance is analysed and the channel error model is constructed. Based on this fact, the problem of target relocation is converted into a problem of channel phase estimation. Moreover, a least-squares method is utilised to estimate the phase error by exploiting the real antenna pattern information and a modified mono-pulse curve (MPC) is derived. Finally, the real geometry location of the moving target can be achieved with the modified MPC. Airborne radar experiments are given to verify the effectiveness of the proposed algorithm.
- Published
- 2019
12. Modified real‐time sub‐aperture processing algorithm for airborne high‐resolution SAR
- Author
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Congxin Li, Hongmeng Chen, Hanwei Sun, Jing Liu, and Jiahao Lin
- Subjects
Synthetic aperture radar ,measured airborne sar datasets ,Computer science ,Image quality ,Aperture ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,0211 other engineering and technologies ,Phase (waves) ,high azimuth sidelobes ,Energy Engineering and Power Technology ,02 engineering and technology ,edge aliasing problem ,algorithm minimises ,high-resolution sar ,airborne radar ,remote sensing by radar ,edge aliasing phenomenon ,conventional sub-aperture algorithm ,021101 geological & geomatics engineering ,real-time imaging ,modified sub-aperture processing algorithm ,Astrophysics::Instrumentation and Methods for Astrophysics ,General Engineering ,sar image quality ,synthetic aperture radar system ,radar imaging ,Azimuth ,Discontinuity (linguistics) ,lcsh:TA1-2040 ,Enhanced Data Rates for GSM Evolution ,Aliasing (computing) ,lcsh:Engineering (General). Civil engineering (General) ,Algorithm ,Software ,synthetic aperture radar - Abstract
The problem of real-time imaging in synthetic aperture radar (SAR) system is addressed here. Sub-aperture processing algorithm is usually used in the engineering applications. However, high azimuth sidelobes and edge aliasing problem usually occur in conventional sub-aperture algorithm, which degenerates the quality of the SAR image. To solve this problem, the reason for high azimuth sidelobes and edge aliasing problem is analysed, and a modified sub-aperture processing algorithm is proposed. The proposed algorithm minimises the effect of the phase discontinuity to improve the SAR image quality. Therefore, the azimuth sidelobes can be improved, and the edge aliasing phenomenon will be eliminated. Real measured airborne SAR datasets demonstrate the effectiveness of the proposed algorithm.
- Published
- 2019
13. Autofocus method for SAR image with multi‐blocks
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Hongmeng Chen, Wei Dong, Hanwei Sun, and Ruixue Zhou
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Synthetic aperture radar ,Energy gradient ,energy inflection point ,PGA method ,Computer science ,Energy Engineering and Power Technology ,02 engineering and technology ,image motion analysis ,law.invention ,Image (mathematics) ,0203 mechanical engineering ,law ,energy gradient factor ,Autofocus ,020301 aerospace & aeronautics ,Data processing ,synthetic aperture radar image-focus problem ,space-variant motion errors ,General Engineering ,radar imaging ,SAR image ,lcsh:TA1-2040 ,Inflection point ,Phase gradient ,partitioned phase gradient autofocus method ,lcsh:Engineering (General). Civil engineering (General) ,Algorithm ,gradient methods ,data processing ,Software ,Energy (signal processing) ,synthetic aperture radar - Abstract
In order to solve synthetic aperture radar image-focus problem when space-variant motion errors could not be ignored, this study proposes a partitioned phase gradient autofocus (PGA) method. In this method, it is most important whether the dominant scatters is in the partitioned images or not. In order to find the dominant scatters, energy gradient factor is defined and energy inflection point is determined. Then, the judgment is made by energy gradient factor and its threshold. Based on measured data processing, it is indicated that the method could distinguish the partitioned images with significant dominant scatters, un-significant dominant scatters, and without dominant scatters. PGA is implemented on all blocks with significant dominant scatters and partial blocks with un-significant dominant scatters. There is no need to use PGA for the blocks without dominant scatters.
- Published
- 2019
14. Adaptive Subspace Signal Detection in Structured Interference Plus Compound Gaussian Sea Clutter
- Author
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Zeyu Wang, Jun Liu, Yachao Li, Hongmeng Chen, and Mugen Peng
- Subjects
General Earth and Planetary Sciences - Abstract
This paper discusses the problem of detecting subspace signals in structured interference plus compound Gaussian sea clutter with persymmetric structure. The sea clutter is represented by a compound Gaussian process wherein the texture obeys the inverse Gaussian distribution. The structured interference lies in a known subspace, which is independent with the target signal subspace. By resorting to the two-step generalized likelihood ratio test, two-step Rao, and two-step Wald design criteria, three adaptive subspace signal detectors are proposed. Moreover, the constant false-alarm rate property of the proposed detectors is proved. The experimental results based on IPIX real sea clutter data and simulated data illustrate that the proposed detectors outperform their counterparts.
- Published
- 2022
15. A study on the cubic range model for MEO SAR ground moving target imaging
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Yongkang Li, Hongmeng Chen, Lina Zeng, and Feng Wang
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Synthetic aperture radar ,Ground moving target ,Physics ,Computer Science::Graphics ,Coordinate system ,Range of a projectile ,Range (statistics) ,Ground moving target indication ,Moving target indication ,Remote sensing - Abstract
Due to the advantages of large coverage, and short revisit time, medium-earth-orbit (MEO) synthetic aperture radar (SAR) is an attractive tool for ground moving target indication (GMTI). This paper presents a study on the third-order Taylor approximated range model for MEO SAR ground moving target imaging. First, the coordinates of a ground accelerating target and MEO SAR in the earthcentered rotating coordinate system, as well as the target’s range equation are developed. Second, the third-order Taylor approximated range model is derived. Finally, the accuracy and the application scope of this cubic range model are investigated via simulations.
- Published
- 2020
16. Knowledge-aided Space Time Adaptive Processing for Airborne Radar in Heterogeneous Environments
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Hanwei Sun, Hongmeng Chen, Heqiang Mu, Yaobing Lu, Jing Liu, and Xiaoli Yi
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Property (programming) ,Computer science ,Covariance matrix ,Real-time computing ,law.invention ,Constant false alarm rate ,symbols.namesake ,Space-time adaptive processing ,law ,symbols ,Range (statistics) ,Clutter ,Radar ,Doppler effect - Abstract
Airborne radar can be used to surveillance wide area and monitor interesting targets, which makes it a good choice for military and civil applications. However, the ground clutter is spread over a region in Doppler due to the movement of the platform, and potential slowly moving target may be obscured by the heavy clutter. To solve this problem, a knowledge-aided Space-time Adaptive Processing (KA-STAP) algorithm is proposed. In particular, the prior knowledge of clutter range-variance property as well as the information extracted from the radar data have been fully utilized. Firstly, the blocked sample selection strategy in range is utilized to decrease the range-variance effect. Then, low threshold CFAR strategy is exploited to choose proper samples in the secondary data, which is quite useful to eliminate the potential targets or jammings. By exploiting this prior knowledge information, the accuracy of the estimated covariance matrix can be well improved. Therefore, the clutter suppression performance can be enhanced in heterogeneous environment. Finally, the performance of different clutter suppression methods are analyzed by resorting to airborne experimental results, which further confirms the effectiveness of the proposed algorithm.
- Published
- 2019
17. Forward-Looking Super-Resolution Imaging for Sea-Surface Target with Multi-Prior Bayesian Method
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Weixin Li, Ming Li, Lei Zuo, Hao Sun, Hongmeng Chen, and Yachao Li
- Subjects
forward-looking imaging ,Gaussian mixture model ,total variation ,sparse ,Science ,Computer Science::Computer Vision and Pattern Recognition ,sea-surface target ,General Earth and Planetary Sciences - Abstract
Traditional forward-looking super-resolution methods mainly concentrate on enhancing the resolution with ground clutter or no clutter scenes. However, sea clutter exists in the sea-surface target imaging, as well as ground clutter when the imaging scene is a seacoast.Meanwhile, restoring the contour information of the target has an important effect, for example, in the autonomous landing on a ship. This paper aims to realize the forward-looking imaging of a sea-surface target. In this paper, a multi-prior Bayesian method, which considers the environment and fuses the contour information and the sparsity of the sea-surface target, is proposed. Firstly, due to the imaging environment in which more than one kind of clutter exists, we introduce the Gaussian mixture model (GMM) as the prior information to describe the interference of the clutter and noise. Secondly, we fuse the total variation (TV) prior and Laplace prior, and propose a multi-prior to model the contour information and sparsity of the target. Third, we introduce the latent variable to simplify the logarithm likelihood function. Finally, to solve the optimal parameters, the maximum posterior-expectation maximization (MAP-EM) method is utilized. Experimental results illustrate that the multi-prior Bayesian method can enhance the azimuth resolution, and preserve the contour information of the sea-surface target.
- Published
- 2021
18. Knowledge-Aided Ground Moving Target Relocation for Airborne Dual-Channel Wide-Area Radar by Exploiting the Antenna Pattern Information
- Author
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Yachao Li, Hongmeng Chen, Zeyu Wang, Gao Wenquan, Hanwei Sun, and Yaobing Lu
- Subjects
phase compensation ,Computer science ,Science ,Direction of arrival ,wide-area radar ,Least squares ,ground moving target relocation (GMTR) ,Expression (mathematics) ,law.invention ,Radiation pattern ,Azimuth ,law ,Monopulse radar ,General Earth and Planetary Sciences ,monopulse ,channel mismatch ,Radar ,Algorithm ,Communication channel - Abstract
This paper addresses the problem of ground moving target relocation (GMTR) for airborne dual-channel wide-area radar systems. The monopulse technique can be utilized to perform GMTR. However, in real conditions, the GMTR performance degrades greatly due to the effect of channel mismatch. To tackle this problem, prior knowledge of the antenna pattern information is fully utilized to improve the GMTR performance, and a knowledge-aided GMTR algorithm (KA-GMTR) for airborne dual-channel wide-area radar is proposed in this paper. First, the GMTR model for the two receiving channels is analyzed. The channel mismatch model is constructed, and its expression is derived. Then, the channel mismatch phase error is well estimated by exploiting the prior antenna pattern information based on the least squares (LS) method. Meanwhile, the knowledge-aided monopulse curve (KA-MPC) is derived to perform the direction of arrival (DOA) estimation for potential targets. Finally, KA-GMTR, based on the KA-MPC, is performed to estimate the azimuth offsets and relocate the geometry positions of the potential targets when channel mismatch occurs. Moreover, the target relocation performance is analyzed, and the intrinsic reason that degrades the target relocation accuracy is figured out. The performance assessment based on airborne real-data, also in comparison to the conventional GMTR method, has demonstrated that our proposed KA-GMTR algorithm offers preferable target relocation results under channel mismatch scenarios.
- Published
- 2021
19. Azimuth super-resolution of forward-looking imaging based on bayesian learning in complex scene
- Author
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Hao Sun, Ming Li, Xiaofei Lu, Weixin Li, Hongmeng Chen, and Lei Zuo
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Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,Bayesian inference ,law.invention ,law ,Joint probability distribution ,Expectation–maximization algorithm ,0202 electrical engineering, electronic engineering, information engineering ,Computer vision ,Electrical and Electronic Engineering ,Radar ,business.industry ,020206 networking & telecommunications ,Mixture model ,Azimuth ,Control and Systems Engineering ,Computer Science::Computer Vision and Pattern Recognition ,Signal Processing ,Clutter ,020201 artificial intelligence & image processing ,Computer Vision and Pattern Recognition ,Artificial intelligence ,Noise (video) ,business ,Software - Abstract
Azimuth super-resolution is an efficient method to enhance the angular resolution of scanning radar in forward-looking area. The existing super-resolution methods are limited in a simple scene, which mainly consider a single clutter environment. For some complex scenes, the distribution of clutter is more complex than single clutter, such as sea-surface scene or the junction scene of sea-surface and ground. In this paper, we present a sparse Bayesian learning method to promote the azimuth resolution in a complex forward-looking scene. First, we use the Gaussian mixture model (GMM) to express the statistical character of the clutter and noise in the complex scene. Second, we present Laplace hierarchical prior as the prior information to model the sparse target. Then, the joint distribution of the clutter and target is derived as an optimized problem under the Bayesian framework. Finally, the solution is solved by the expectation maximization (EM) based maximum a posterior (MAP) method. The simulation and semi-real data results show that the proposed algorithm provides better angular resolution than traditional methods in complex scene.
- Published
- 2021
20. Adaptive Detection of a Subspace Signal in Signal-Dependent Interference
- Author
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Peng Zhang, Hongmeng Chen, Zeyu Wang, Yan Wu, Ming Li, and Lei Zuo
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020301 aerospace & aeronautics ,Speech recognition ,Detector ,020206 networking & telecommunications ,02 engineering and technology ,Wald test ,Signal ,Constant false alarm rate ,0203 mechanical engineering ,Interference (communication) ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,Clutter ,False alarm ,Electrical and Electronic Engineering ,Algorithm ,Subspace topology ,Mathematics - Abstract
This paper deals with the problem of adaptive detection of subspace signals embedded in thermal noise and clutter that depends on the transmitted signal. To this end, at the design stage, we assume that the signal-dependent (SD) clutter shares the same subspace as the target signals. As customary, a set of secondary data, free of signal components, is also assumed available. Two adaptive detectors, referred to as the SD Rao and SD Wald, are proposed by resorting to the Rao test and Wald test design criteria. Unlike the classical Rao and Wald tests, which are derived by dividing the complex parameter into the real and imaginary parts, the proposed detectors treat the complex parameter as a single quantity to reduce the computational burden. Moreover, we derive the theoretical false alarm probabilities and detection probabilities and show that both the two proposed detectors exhibit the constant false alarm rate property. Numerical results show that the proposed detectors achieve a detection performance improvement over the conventional multidimensional detectors.
- Published
- 2017
21. Efficient forward-looking imaging via synthetic bandwidth azimuth modulation imaging radar for high-speed platform
- Author
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Yan Wu, Ming Li, Yaobing Lu, Xiaoli Yi, Hongmeng Chen, Heqiang Mu, Jing Liu, and Zeyu Wang
- Subjects
Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,02 engineering and technology ,law.invention ,symbols.namesake ,law ,Radar imaging ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Waveform ,Electrical and Electronic Engineering ,Radar ,020208 electrical & electronic engineering ,Bandwidth (signal processing) ,020206 networking & telecommunications ,Filter (signal processing) ,Azimuth ,Control and Systems Engineering ,Modulation ,Signal Processing ,Forward looking ,symbols ,Computer Vision and Pattern Recognition ,Frequency modulation ,Doppler effect ,Software - Abstract
This paper deals with the forward-looking imaging problem under high-speed platform for the airborne single-channel forward-looking radar (ASFLR). Biphase-based synthetic bandwidth azimuth modulation imaging radar (Bi-SBAMIR) can be used to increase the azimuth resolution. However, the performance degrades significantly when the velocity of the platform is high. To solve this problem, a more generalized SBAMIR framework based on linear frequency modulation (LFM) waveform (LFM-SBAMIR) is proposed. The LFM waveform is more Doppler tolerant than the biphase waveform, which makes it a good choice for high speed platform. In LFM-SBAMIR, the synthetic bandwidth of the received signal has two parts: the modulation bandwidth and the Doppler bandwidth. Therefore, large synthetic bandwidth can be achieved by increasing the modulation bandwidth even in the case of small Doppler bandwidth, and high azimuth resolution can be achieved after matched filtering. Moreover, it is firstly proved that the azimuth resolution is proportional to the time bandwidth product (TBP) of the modulated LFM waveform. Finally, the azimuth resolution performance under different TBPs, SNRs and velocities are analyzed. The performance assessment conducted by resorting to simulated data, also in comparison to the previously proposed Bi-SBAMIR method, has confirmed the effectiveness of the newly proposed algorithm in high-speed platform scenarios.
- Published
- 2017
22. Cross-Range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture-Extrapolated Sparse Representation
- Author
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Zeyu Wang, Yunlong Lu, Runqing Cao, Peng Zhang, Hongmeng Chen, Lei Zuo, Ming Li, and Yan Wu
- Subjects
Computer science ,business.industry ,Aperture ,0211 other engineering and technologies ,Extrapolation ,020206 networking & telecommunications ,02 engineering and technology ,Sharpening ,Sparse approximation ,Geotechnical Engineering and Engineering Geology ,Superresolution ,symbols.namesake ,Autoregressive model ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,Coherence (signal processing) ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Doppler effect ,021101 geological & geomatics engineering - Abstract
This letter addresses the problem of cross-range superresolution in Doppler beam sharpening (DBS). The coherence of echoes in the azimuth direction and the sparsity of the DBS image in the Doppler domain are fully exploited; thus, a superresolution DBS imaging framework using aperture-extrapolated sparse representation (SR) is proposed. In this framework, aperture extrapolation based on the autoregressive model is utilized to predict the forward and backward information in the azimuth direction, and SR is exploited to extract the Doppler spectrum information. In addition, the resolution ability with different coherent processing intervals is analyzed. The sharpening ratio in this proposed algorithm can be improved by a factor of two or four theoretically in comparison with the conventional DBS imaging method. Experimental results demonstrate that the proposed framework can lead to noticeable performance improvement.
- Published
- 2017
23. Efficient TR‐TBD algorithm for slow‐moving weak multi‐targets in heavy clutter environment
- Author
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Zeyu Wang, Ming Li, Yan Wu, Hongmeng Chen, and Yunlong Lu
- Subjects
020301 aerospace & aeronautics ,Computer science ,Plane (geometry) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,020206 networking & telecommunications ,02 engineering and technology ,Radar detection ,Object detection ,Reduction (complexity) ,Signal-to-noise ratio ,Operator (computer programming) ,0203 mechanical engineering ,Recovery method ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,Clutter ,Electrical and Electronic Engineering ,Algorithm - Abstract
In this study, the authors present an efficient time-dimension-reduced track-before-detect (TR-TBD) processor for slow-moving weak multi-targets detection in strong clutter environment. In their proposed framework, they elaborate observations from multiple frames (or scans) and resample them in time direction, then distinguish the slow-moving targets from the clutter in the radon parameter domain by exploiting the fact that different velocities of targets have different skewing angles corresponding to their tracks in the range-time (range-pulse) plane. To further enlarge the skewing angles differences between the slow-moving targets and the clutter, TR-TBD is proposed by incorporating the time-dimension reduction operator. This is very helpful to amplify the skewing angle of slow-moving targets, while the improvement is very small for the clutter. Therefore, it is much convenient to figure out the slow-moving weak targets from heavy clutter environment based on their amplified skewing angle differences by setting proper threshold. After detecting the targets, CLEAN-based track recovery method is proposed to eliminate the false tracks and recover the true tracks. Experimental results on real-data demonstrate that the proposed algorithm can detect the closely spaced targets and eliminate the false tracks under low signal-to-noise ratio and signal-to-clutter ratio.
- Published
- 2017
24. Synthetic bandwidth azimuth modulation imaging radar for airborne single-channel forward-looking imaging
- Author
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Runqing Cao, Hongmeng Chen, Yan Wu, Ming Li, Yunlong Lu, and Zeyu Wang
- Subjects
Computer science ,Acoustics ,Bandwidth (signal processing) ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,0211 other engineering and technologies ,020206 networking & telecommunications ,Side looking airborne radar ,02 engineering and technology ,Filter (signal processing) ,law.invention ,Azimuth ,Control and Systems Engineering ,Modulation ,law ,Radar imaging ,Signal Processing ,Forward looking ,0202 electrical engineering, electronic engineering, information engineering ,Electronic engineering ,Computer Vision and Pattern Recognition ,Electrical and Electronic Engineering ,Radar ,Nuclear Experiment ,Software ,021101 geological & geomatics engineering - Abstract
An efficient airborne single-channel forward-looking radar (ASFLR) imaging framework to improve the azimuth resolution performance with synthetic bandwidth azimuth modulation imaging radar (SBAMIR) is proposed. During the framework, we incorporate azimuth modulation to the transmitted signal with a coded sequence in azimuth direction, and derive the SBAMIR imaging model for the first time. In SBAMIR, the synthetic bandwidth of the received echo is not only determined by the Doppler bandwidth, but also by the modulation bandwidth. Even though the Doppler bandwidth has little contribution to the synthetic bandwidth in ASFLR, the modulation bandwidth can be utilized to increase the synthetic bandwidth. Accordingly, a high azimuth resolution can be achieved after azimuth matched filtering. Achievable azimuth resolution and performance to SNR are analyzed later. Simulation results are given to verify the effectiveness of the proposed algorithm. Synthetic bandwidth azimuth modulation imaging radar (SBAMIR) is proposed.Azimuth modulation will bring in additional modulation bandwidth.Synthetic bandwidth is determined by the Doppler bandwidth and modulation bandwidth.
- Published
- 2017
25. Persymmetric detectors of distributed targets in partially homogeneous disturbance
- Author
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Yan Wu, Peng Zhang, Runqing Cao, Zeyu Wang, Lei Zuo, Ming Li, Yunlong Lu, and Hongmeng Chen
- Subjects
020301 aerospace & aeronautics ,Engineering ,Disturbance (geology) ,Covariance matrix ,business.industry ,Gaussian ,Detector ,020206 networking & telecommunications ,02 engineering and technology ,Covariance ,Wald test ,symbols.namesake ,0203 mechanical engineering ,Control and Systems Engineering ,Homogeneous ,Control theory ,Simulated data ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,Computer Vision and Pattern Recognition ,Electrical and Electronic Engineering ,business ,Software - Abstract
This paper deals with the problem of detecting distributed target in Gaussian disturbance with unknown but persymmetric structured covariance matrix. The partially-homogeneous environment is considered and two receivers based on the Rao test and the Wald test design criteria are derived at the design stage. The performance assessment conducted by resorting to both simulated data and real data, also in comparison to the previously proposed detectors, has confirmed the effectiveness of the newly proposed detectors. Two detectors based on the Rao and Wald tests are devised.The disturbance has unknown but persymmetric structured covariance matrix.The proposed detectors achieve matched detection performance improvement.
- Published
- 2016
26. Space Group Targets Detecting and Resolving Algorithm via Ultra-low Sidelobe Filtering
- Author
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Heqiang Mu, Hongmeng Chen, Jiahao Lin, Jing Liu, Yaobing Lu, Zeyu Wang, Hanwei Sun, and Xiaoli Yi
- Subjects
020301 aerospace & aeronautics ,Computer science ,0211 other engineering and technologies ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,02 engineering and technology ,Filter (signal processing) ,Space (mathematics) ,law.invention ,Signal-to-noise ratio ,0203 mechanical engineering ,law ,Limit (music) ,Key (cryptography) ,Range (statistics) ,Angular resolution ,Radar ,Algorithm ,021101 geological & geomatics engineering - Abstract
Detecting and resolving the space group targets in the main beam of radar is an urgent requirement for the air-defense and anti-missile radar system. Ground-based radar, as an important instrument for space surveillance, can be used to detect and track the space targets like grouped aircrafts, warheads and the decoys of the missiles. However, it is difficult to detect and resolve the dense targets due to the limit of the radar resolving power. To solve this problem, a space group targets detecting and resolving algorithm based on ultra-low sidelobe filtering is proposed. By exploiting the convex optimization into the pulse-Doppler radar, the problem of ultra-low sidelobe is converted into the problem of optimization. The key of this algorithm is to minimize the peak to sidelobe level (PSL) of the range sidelobes with a constraint of signal to noise ratio (SNR) loss. Then the ultra-low sidelobe filtering results are used to detect and resolve the space group targets in the main beam. Numerical and experimental results demonstrate the effectiveness of the proposed algorithm.
- Published
- 2019
27. Super‐resolution Doppler beam sharpening imaging via sparse representation
- Author
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Peng Zhang, Lei Zuo, Ming Li, Zeyu Wang, Hongmeng Chen, Wang Shuai, Yunlong Lu, and Yan Wu
- Subjects
business.industry ,Computer science ,Doppler radar ,0211 other engineering and technologies ,020206 networking & telecommunications ,02 engineering and technology ,Sharpening ,Sparse approximation ,law.invention ,Time–frequency analysis ,symbols.namesake ,law ,Radar imaging ,Frequency domain ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Doppler effect ,Image resolution ,021101 geological & geomatics engineering - Abstract
In Doppler beam sharpening (DBS) imaging, the imaging scene is characterised corresponding to the Doppler band, and the Doppler band occupies only a small part compared with the whole frequency domain. Accordingly, the DBS image is sparse in the frequency domain. Motivated by the sparsity, the authors propose a novel framework of DBS formation via sparse representation to perform super-resolution. In the framework, by exploiting the fact that the ground scene is sparse in frequency domain, they perform the super-resolution formation by incorporating the sparsity constraint with respect to a redundant time–frequency dictionary. The recovered sparse coefficients are utilised to form the final DBS image in frequency domain. Since the dictionary is redundant with more columns than rows, a thinner Doppler frequency resolution and a higher sharpening ratio can be achieved. Experimental results on real measured data verify the effectiveness of the new super-resolution algorithm.
- Published
- 2016
28. Knowledge‐aided mono‐pulse forward‐looking imaging for airborne radar by exploiting the antenna pattern information
- Author
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Heqiang Mu, Hongmeng Chen, Xiaoli Yi, Yaobing Lu, Jing Liu, Ming Li, and Zeyu Wang
- Subjects
Synthetic aperture radar ,Early-warning radar ,Scattering ,Computer science ,020208 electrical & electronic engineering ,020206 networking & telecommunications ,Side looking airborne radar ,02 engineering and technology ,Radar lock-on ,law.invention ,Radiation pattern ,Continuous-wave radar ,Bistatic radar ,Radar engineering details ,law ,Radar imaging ,0202 electrical engineering, electronic engineering, information engineering ,3D radar ,Electrical and Electronic Engineering ,Radar ,Algorithm ,Remote sensing - Abstract
A knowledge-aided mono-pulse forward-looking imaging algorithm to enhance the performance of airborne radar is proposed. Firstly, the ideal mono-pulse imaging model based on the dual-channel radar system is analysed and the mismatch model of the receiving channel is constructed. Then the mismatch phase error and a modified mono-pulse curve (MPC) are derived based on the least square (LS) method by taking advantage of a prior antenna pattern information. Finally, the modified MPC is utilised to perform the direction-of-arrival (DOA) estimation of each scattering centres in mono-pulse imaging. Real airborne radar data experiments are given to verify the effectiveness of the proposed algorithm.
- Published
- 2017
29. Resolution enhancement for Doppler beam sharpening imaging
- Author
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Ming Li, Hongmeng Chen, Yan Wu, Peng Zhang, Gaofeng Liu, and Lu Jia
- Subjects
business.industry ,Computer science ,Doppler radar ,Fast Fourier transform ,Spectral density estimation ,Sharpening ,Moving target indication ,law.invention ,symbols.namesake ,Optics ,law ,Side lobe ,Radar imaging ,symbols ,Electrical and Electronic Engineering ,business ,Doppler effect - Abstract
The efficient scan moving target indication (MTI) mode is implemented in the wide-area ground MTI systems for the purpose of wide-area surveillance. However, because of the scanning movement of the radar antenna, it is difficult to acquire enough coherent pulses in a single azimuth direction in the Doppler beam sharpening (DBS), so the sharpening ratio is greatly limited. To mitigate this problem, a combined super-resolution algorithm with aperture extrapolation for DBS imaging is proposed to enhance the sharpening ratio in this study. In this algorithm, aperture extrapolation technique is utilised to increase the data length in azimuth direction and the amplitude and phase estimation of a sinusoid, which can acquire accurate spectral estimation with much lower side lobes and narrower spectral peaks, is applied to replace the fast Fourier transform to perform the Doppler analysis. In this way, the sharpening ratio in the new algorithm could be enhanced by one time. Experimental results on simulation data and real data verify the effectiveness of the new super-resolution algorithm, and demonstrate that the proposed algorithm can provide sharp and clear scene information with lower side lobes and narrower peaks.
- Published
- 2015
30. SAR Image Change Detection Based on Iterative Label-Information Composite Kernel Supervised by Anisotropic Texture
- Author
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Hongmeng Chen, Peng Zhang, Lin An, Lu Jia, Ming Li, Yan Wu, and Gaofeng Liu
- Subjects
Synthetic aperture radar ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,Support vector machine ,symbols.namesake ,Kernel method ,Kernel (statistics) ,Radial basis function kernel ,Kernel smoother ,Gaussian function ,symbols ,General Earth and Planetary Sciences ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Change detection ,Mathematics - Abstract
Kernel methods with specifically designed kernel function are suitable for dealing with practical nonlinear problems. However, kernel methods have found limited applications to synthetic aperture radar (SAR) image change detection in that their performances are affected by the inherent multiplicative speckle noise of SAR images. It is known that the spatial-contextual information is helpful in suppressing the degrading effects of the noise. Therefore, a label-information composite kernel ( LIC kernel ) constructed on the basis of the spatial-contextual information is proposed in this paper for SAR image change detection. A typical spatial information, the output-space label-neighborhood information that is extracted using all labels in the neighborhood of each pixel, may enhance noise immunity, but with inaccurate edge locations simultaneously. Consequently, the anisotropic Gaussian kernel model is utilized for analyzing anisotropic textures of the bitemporal images, and then, a comparison scheme acting on the input-space textures of the bi-temporal images is proposed to supervise the extraction of the output-space label-neighborhood information in the construction of the LIC kernel . The constructed LIC kernel is of good preservation of edge locations of changed areas as well as strong noise immunity. The LIC kernel is updated iteratively with the newest change map outputted from the support vector machine, until the change map converges. Experiments on real SAR images demonstrate the effectiveness of the LIC kernel method and illustrate that it has both strong noise immunity and good preservation of edge locations of changed areas for SAR image change detection.
- Published
- 2015
31. Semisupervised SAR Image Change Detection Using a Cluster-Neighborhood Kernel
- Author
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Ming Li, Peng Zhang, Lu Jia, Yan Wu, Lin An, and Hongmeng Chen
- Subjects
Synthetic aperture radar ,Contextual image classification ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Pattern recognition ,Geotechnical Engineering and Engineering Geology ,Support vector machine ,ComputingMethodologies_PATTERNRECOGNITION ,Kernel method ,Kernel (image processing) ,Radial basis function kernel ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,Cluster analysis ,business ,Change detection ,Mathematics - Abstract
Change detection can be performed in a supervised manner. However, supervised methods for synthetic aperture radar (SAR) image change detection may suffer from lack of training samples. Therefore, in this letter, a semisupervised support vector machine classifier based on a cluster-neighborhood (CN) kernel is proposed for SAR image change detection. In the proposed method, samples are categorized into two neighborhoods with kernel k-means clustering algorithm. In addition, a CN kernel is constructed based on the composite-ratio kernel using the neighborhood-based statistical features. When a few labeled samples are available, the proposed CN kernel explores the information of unlabeled samples to enhance its discriminative ability and enhance its robustness against speckles. Experimental results on real SAR image change detection demonstrate the effectiveness of the proposed method when a few labeled samples are available.
- Published
- 2014
32. Knowledge-Aided Doppler Beam Sharpening Super-Resolution Imaging by Exploiting the Spatial Continuity Information
- Author
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Heqiang Mu, Zeyu Wang, Yaobing Lu, Jing Liu, Xiaoli Yi, Hongmeng Chen, Hanwei Sun, and Ming Li
- Subjects
Computer science ,0211 other engineering and technologies ,super-resolution ,02 engineering and technology ,lcsh:Chemical technology ,Biochemistry ,Article ,Analytical Chemistry ,law.invention ,Coherent processing interval ,law ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:TP1-1185 ,Computer vision ,Electrical and Electronic Engineering ,Radar ,Instrumentation ,021101 geological & geomatics engineering ,business.industry ,020206 networking & telecommunications ,Superresolution ,Atomic and Molecular Physics, and Optics ,Spatial coherence ,Autoregressive model ,Artificial intelligence ,wide-area surveillance ,business ,Doppler beam sharpening - Abstract
This paper deals with the problem of high cross-range resolution Doppler beam sharpening (DBS) imaging for airborne wide-area surveillance (WAS) radar under short dwell time situations. A knowledge-aided DBS (KA-DBS) imaging algorithm is proposed. In the proposed KA-DBS framework, the DBS imaging model for WAS radar is constructed and the cross-range resolution is analyzed. Since the radar illuminates the imaging scene continuously through the scanning movement of the antenna, there is strong spatial coherence between adjacent pulses. Based on this fact, forward and backward pulse information can be predicted, and the equivalent number of pulses in each coherent processing interval (CPI) will be doubled based on the autoregressive (AR) technique by taking advantage of the spatial continuity property of echoes. Finally, the predicted forward and backward pulses are utilized to merge with the initial pulses, then the newly merged pulses in each CPI are utilized to perform the DBS imaging. Since the number of newly merged pulses in KA-DBS is twice larger than that in the conventional DBS algorithm with the same dwell time, the cross-range resolution in the proposed KA-DBS algorithm can be improved by a factor of two. The imaging performance assessment conducted by resorting to real airborne data set, has verified the effectiveness of the proposed algorithm.
- Published
- 2019
33. Unsupervised SAR Image Segmentation Using a Hierarchical TMF Model
- Author
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Lu Jia, Ming Li, Gaofeng Liu, Peng Zhang, Yan Wu, and Hongmeng Chen
- Subjects
Synthetic aperture radar ,business.industry ,Segmentation-based object categorization ,Computer science ,Generalized gamma distribution ,Scale-space segmentation ,Pattern recognition ,Image segmentation ,Geotechnical Engineering and Engineering Geology ,Bayesian inference ,law.invention ,law ,Computer Science::Computer Vision and Pattern Recognition ,Quadtree ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,Radar ,business ,Physics::Atmospheric and Oceanic Physics - Abstract
The triplet Markov field (TMF) model recently proposed is suitable for tackling the nonstationary image segmentation. In this letter, we propose a hierarchical TMF (HTMF) model for unsupervised synthetic aperture radar (SAR) image segmentation. In virtue of the Bayesian inference on the quadtree, the HTMF model captures the global and local image characteristics more precisely in the bottom-up and top-down probability computations. In this way, the underlying spatial structure information is effectively propagated. To model the SAR data related to radar backscattering sources, generalized Gamma distribution is utilized. The effectiveness of the proposed HTMF model is demonstrated by application to simulated data and real SAR image segmentation.
- Published
- 2013
34. A DBS image stitching algorithm based on affine transformation
- Author
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Yan Wu, Ming Li, Yunlong Lu, and Hongmeng Chen
- Subjects
Offset (computer science) ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,law.invention ,Image stitching ,law ,Computer vision ,Artificial intelligence ,Affine transformation ,Radar ,business ,Algorithm ,Doppler beam sharpening - Abstract
The stitching quality of Doppler Beam Sharpening (DBS) image will be greatly affected due to the non-ideal movement of the radar platform. A novel method based on affine transformation is proposed, which can correct and stitch the DBS image effectively. The change of attitude of the carrier aircraft could be corrected with rotation angle and the change of position of the carrier aircraft could be corrected with offset with the help of the affine transformation. Processing results of measured data show effectiveness of the method. (4 pages)
- Published
- 2013
35. Tri‐band rectangle‐loaded monopole antenna with inverted‐L slot for WLAN/WiMAX applications
- Author
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Jianxin Wu, Ying Zeng Yin, Hongmeng Chen, Xin Yang, and Y.-M. Cai
- Subjects
Physics ,business.industry ,Electrical engineering ,WiMAX ,law.invention ,Radiation pattern ,Optics ,law ,Etching (microfabrication) ,Radiator (engine cooling) ,Wi-Fi ,Rectangle ,Electrical and Electronic Engineering ,Antenna (radio) ,business ,Monopole antenna - Abstract
A novel coplanar waveguide-fed tri-band monopole antenna with a compact radiator (10 × 23 mm2) for WLAN/WiMAX applications is presented. By etching properly an inverted-L slot on the straight strip loaded with a rectangular tuning patch and further adjusting the dimensions and positions of these structures, three distinct wide bands can be achieved. The measured and simulated results show that the proposed antenna has 10 dB impedance bandwidth of 470 MHz (2.38–2.85 GHz), 360 MHz (3.36–3.72 GHz) and 890 MHz (4.98–5.87 GHz) to cover all the 2.4/5.2/5.8 GHz WLAN bands and 2.5/3.5/5.5 GHz WiMAX bands. Also, the proposed antenna produces good dipole-like radiation pattern over the covering bands.
- Published
- 2013
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