Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059327
Deqing Mao, Yin Zhang, Yongchao Zhang, Yulin Huang, Jianyu Yang
The deconvolution methods are the effective approaches to realize high cross-range resolution of real-beam scanning radar. However, the computational time of these algorithms cannot meet the real-time requirements of radar imaging, which is a key limitation to apply this technology into engineering application. In order to overcome this problem, we propose a parallel processing plan based on Graphics Processing Unit (GPU) frame to achieve the real-time imaging by the Bayesian deconvolution algorithm. Because of the processing of each range bin is independent, the characteristics of GPU parallel computing can be used to settle the problem of large computation burden. In this paper, the method to realize parallel computing on GPU frame will be explained in detail. At last, the Poisson-based maximum a posteriori (MAP) algorithm [11] is taken as an example to compare the efficiency of the GPU frame with Central Processing Unit (CPU).
{"title":"Realization of airborne forward-looking radar super-resolution algorithm based on GPU frame","authors":"Deqing Mao, Yin Zhang, Yongchao Zhang, Yulin Huang, Jianyu Yang","doi":"10.1109/RADAR.2016.8059327","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059327","url":null,"abstract":"The deconvolution methods are the effective approaches to realize high cross-range resolution of real-beam scanning radar. However, the computational time of these algorithms cannot meet the real-time requirements of radar imaging, which is a key limitation to apply this technology into engineering application. In order to overcome this problem, we propose a parallel processing plan based on Graphics Processing Unit (GPU) frame to achieve the real-time imaging by the Bayesian deconvolution algorithm. Because of the processing of each range bin is independent, the characteristics of GPU parallel computing can be used to settle the problem of large computation burden. In this paper, the method to realize parallel computing on GPU frame will be explained in detail. At last, the Poisson-based maximum a posteriori (MAP) algorithm [11] is taken as an example to compare the efficiency of the GPU frame with Central Processing Unit (CPU).","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134629194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059456
Chunsheng Luo, Guochao Wang, Guanghua Lu, Dongjin Wang
A novel imaging method based on temporal-spatial stochastic radiation field is a super-resolution imaging technique without the limitation of relative motion between the target and radar. For the novel microwave staring coincidence imaging of the moving target, in addition to the distribution of the target scattering coefficient, we also need to estimate the target velocity. When the target movement information is ignored or failing to estimate, the imaging result will appear serious defocusing and affect the imaging resolution performance. Inspired by dictionary learning, we use sparse representation-based classifier (SRC) to assess a velocity from the target velocity range in the compressed sensing framework. We propose PSO-SRC algorithm which utilize Particle Swarm optimization (PSO) to find the optimal velocity which is assessed by SRC algorithm. The simulations that the target velocity is within the speed of sound illustrate the effectiveness of the proposed method.
{"title":"Recovery of moving targets for a novel super-resolution imaging radar with PSO-SRC","authors":"Chunsheng Luo, Guochao Wang, Guanghua Lu, Dongjin Wang","doi":"10.1109/RADAR.2016.8059456","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059456","url":null,"abstract":"A novel imaging method based on temporal-spatial stochastic radiation field is a super-resolution imaging technique without the limitation of relative motion between the target and radar. For the novel microwave staring coincidence imaging of the moving target, in addition to the distribution of the target scattering coefficient, we also need to estimate the target velocity. When the target movement information is ignored or failing to estimate, the imaging result will appear serious defocusing and affect the imaging resolution performance. Inspired by dictionary learning, we use sparse representation-based classifier (SRC) to assess a velocity from the target velocity range in the compressed sensing framework. We propose PSO-SRC algorithm which utilize Particle Swarm optimization (PSO) to find the optimal velocity which is assessed by SRC algorithm. The simulations that the target velocity is within the speed of sound illustrate the effectiveness of the proposed method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132102670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059534
Ke Jin, Tao Lai, Ting Wang, Tongxin Dang, Yongjun Zhao
The nonlinearity in the transmitted signal of the Frequency-modulated continuous-wave (FMCW) radar has become a bottleneck to its utilization. This paper presents a new method to conduct nonlinearity correction for wideband FMCW radars. The nonlinearity is first modeled as a polynomial phase function, whose coefficients are then estimated with the proposed polynomial regression algorithm (PRA). Combined with the Match Fourier Transform, the nonlinearity is finally corrected. Simulation results show the feasibility of the proposed algorithm. Echo processing result of an X-band FMCW radar indicates that the nonlinearity can be eliminated effectively. SAR images further validate the effectiveness of the proposed algorithm.
{"title":"A method for nonlinearity correction of wideband FMCW radar","authors":"Ke Jin, Tao Lai, Ting Wang, Tongxin Dang, Yongjun Zhao","doi":"10.1109/RADAR.2016.8059534","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059534","url":null,"abstract":"The nonlinearity in the transmitted signal of the Frequency-modulated continuous-wave (FMCW) radar has become a bottleneck to its utilization. This paper presents a new method to conduct nonlinearity correction for wideband FMCW radars. The nonlinearity is first modeled as a polynomial phase function, whose coefficients are then estimated with the proposed polynomial regression algorithm (PRA). Combined with the Match Fourier Transform, the nonlinearity is finally corrected. Simulation results show the feasibility of the proposed algorithm. Echo processing result of an X-band FMCW radar indicates that the nonlinearity can be eliminated effectively. SAR images further validate the effectiveness of the proposed algorithm.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059464
Jian Wang, W. Hu, Lefeng Zhang, Qing Xue, Wei Cao
In order to detect and track the moving weak multitarget through ubiquitous radar observations, this paper proposes a cardinalized probability hypothesis density (CPHD) filter based on sequential Monte Carlo (SMC) implementation. The traditional tracking method, such as joint probabilistic data association (JPDA) algorithm, suffers from computational problem in closely-spaced targets and low signal-to-noise ratio (SNR) environment. The CPHD filter is a multitarget moment approximation of the multitarget Bayes filter with both the detecting and tracking capability. The proposed method is designed for the general weak multitarget detecting scenarios with unknown parameters. In particular, the filter is derived by exploiting the tools of the finite set statistics (FISST) to solve the multisensory-multitarget computational problem of CPHD. Instead of processing in data level, the processing in signal level schemes alleviates the information loss, since the measurements of ubiquitous radar can be in in-phase and quadrature (I/Q) form. Simulation results show that the proposed filter yields stable cardinality and state estimates.
{"title":"Weak multitarget detection exploiting CPHD filter for ubiquitous radar","authors":"Jian Wang, W. Hu, Lefeng Zhang, Qing Xue, Wei Cao","doi":"10.1109/RADAR.2016.8059464","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059464","url":null,"abstract":"In order to detect and track the moving weak multitarget through ubiquitous radar observations, this paper proposes a cardinalized probability hypothesis density (CPHD) filter based on sequential Monte Carlo (SMC) implementation. The traditional tracking method, such as joint probabilistic data association (JPDA) algorithm, suffers from computational problem in closely-spaced targets and low signal-to-noise ratio (SNR) environment. The CPHD filter is a multitarget moment approximation of the multitarget Bayes filter with both the detecting and tracking capability. The proposed method is designed for the general weak multitarget detecting scenarios with unknown parameters. In particular, the filter is derived by exploiting the tools of the finite set statistics (FISST) to solve the multisensory-multitarget computational problem of CPHD. Instead of processing in data level, the processing in signal level schemes alleviates the information loss, since the measurements of ubiquitous radar can be in in-phase and quadrature (I/Q) form. Simulation results show that the proposed filter yields stable cardinality and state estimates.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132863549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059465
Xueli Pan, G. Liao, Zhiwei Yang
In this paper, we deal with range-distributed targets detection in Gaussian clutter plus subspace interference, we propose an adaptive Rao detector of range-distributed targets. In this paper, firstly, we assume that clutter covariance matrix is known, then substitute clutter covariance matrix for sample covariance matrix. The algorithm possesses the property of constant false alarm rate (CFAR) with respect to the covariance matrix. In this paper, the performance of the detector is assessed by Monte Carlo simulation, and is compared with generalized Likelihood ratio test (GLRT).
{"title":"Rao test of range-distributed targets in homogeneous clutter plus subspace interference","authors":"Xueli Pan, G. Liao, Zhiwei Yang","doi":"10.1109/RADAR.2016.8059465","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059465","url":null,"abstract":"In this paper, we deal with range-distributed targets detection in Gaussian clutter plus subspace interference, we propose an adaptive Rao detector of range-distributed targets. In this paper, firstly, we assume that clutter covariance matrix is known, then substitute clutter covariance matrix for sample covariance matrix. The algorithm possesses the property of constant false alarm rate (CFAR) with respect to the covariance matrix. In this paper, the performance of the detector is assessed by Monte Carlo simulation, and is compared with generalized Likelihood ratio test (GLRT).","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132767975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059206
Zhao Ning, L. Jiaguo, Ge Jia-long, Yao Baidong
For space-borne P band Synthetic Aperture Radar (SAR) application, an airborne experimental circular&linear polarimetric SAR system is developed, this paper presents the instrument and airborne test result. Compared to linear polarization of P band, circular polarimetric SAR shows remarkable penetration efficacy in tropical jungle foliage covered region and subsurface targets detection. Besides, A new phenomenon of P band circular polarimetric SAR implies potential advantage in man-made linear object detection.
{"title":"Research of P band circular polarization SAR","authors":"Zhao Ning, L. Jiaguo, Ge Jia-long, Yao Baidong","doi":"10.1109/RADAR.2016.8059206","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059206","url":null,"abstract":"For space-borne P band Synthetic Aperture Radar (SAR) application, an airborne experimental circular&linear polarimetric SAR system is developed, this paper presents the instrument and airborne test result. Compared to linear polarization of P band, circular polarimetric SAR shows remarkable penetration efficacy in tropical jungle foliage covered region and subsurface targets detection. Besides, A new phenomenon of P band circular polarimetric SAR implies potential advantage in man-made linear object detection.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132936382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059543
Hu Xiang, Long Xiang, Guoqi Hu, Pengshu Dong
An improved ACCF iteratively method for promoting motion parameters estimation performance of maneuvering target is proposed in this paper. The principle of ACCF iteratively method is introduced firstly. Then parameters estimation error formulas via ACCF iteratively are deduced theoretically. Then according to the required precision for jerk and acceleration, reasonable L-point DFT and IDFT operations for the estimation of jerk and acceleration are adopted. As for the velocity estimation, the interpolation operation with 10 times is adopted. In this way, the parameters estimation precision can be controlled and the computational cost would be reduced further. The numerical experiment results validate the effectiveness of the proposed method.
{"title":"An improved method for promoting motion parameters estimation performance of maneuvering targets","authors":"Hu Xiang, Long Xiang, Guoqi Hu, Pengshu Dong","doi":"10.1109/RADAR.2016.8059543","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059543","url":null,"abstract":"An improved ACCF iteratively method for promoting motion parameters estimation performance of maneuvering target is proposed in this paper. The principle of ACCF iteratively method is introduced firstly. Then parameters estimation error formulas via ACCF iteratively are deduced theoretically. Then according to the required precision for jerk and acceleration, reasonable L-point DFT and IDFT operations for the estimation of jerk and acceleration are adopted. As for the velocity estimation, the interpolation operation with 10 times is adopted. In this way, the parameters estimation precision can be controlled and the computational cost would be reduced further. The numerical experiment results validate the effectiveness of the proposed method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122493562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059293
Sun Wei, He Kunxi, Ye Zhenyu, Sun Jinping
Terahertz Video Synthetic Aperture Radar (ViSAR) system can indicate target information continuously and actively with an image frame rate as high as infrared video, having advantages such as high resolution and good sensitivity in target motion detection. However, terahertz wavelength is rather short, and as a result, traditional dual-channel SAR motion target indication method gets a tiny blind velocity period which goes against target detection. Aimed at the problem, this paper provides a multi-channel terahertz ViSAR motion target detection method based on along track interferometry (ATI) technique. It selects several baselines of varying length and utilizes algebra coprime theory to enlarge blind velocity period so that the range of non-ambiguity velocity can be extended. Simulation results verify the effectiveness of the method.
{"title":"Multi-channel terahertz ViSAR motion target indication based on ATI technique","authors":"Sun Wei, He Kunxi, Ye Zhenyu, Sun Jinping","doi":"10.1109/RADAR.2016.8059293","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059293","url":null,"abstract":"Terahertz Video Synthetic Aperture Radar (ViSAR) system can indicate target information continuously and actively with an image frame rate as high as infrared video, having advantages such as high resolution and good sensitivity in target motion detection. However, terahertz wavelength is rather short, and as a result, traditional dual-channel SAR motion target indication method gets a tiny blind velocity period which goes against target detection. Aimed at the problem, this paper provides a multi-channel terahertz ViSAR motion target detection method based on along track interferometry (ATI) technique. It selects several baselines of varying length and utilizes algebra coprime theory to enlarge blind velocity period so that the range of non-ambiguity velocity can be extended. Simulation results verify the effectiveness of the method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"269 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122084326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059601
Ying Yin, Shunsheng Zhang, F. Wu, Zhulin Zong, Wei Zhang
Passive radar system exploits illuminators of opportunity (IOs), such as television and radio, to detect and track moving targets. In this paper, we propose a new passive radar detection scheme with DVB-T signals. A large time-bandwidth-product signal is first generated by using multiple channels DVB-T signals. Then, a Radon-Fourier transform (RFT) algorithm is applied to achieve long-time coherent integration. In doing so, the moving target can be detected in low signal-to-noise ratio (SNR) situation. Simulation results validate the effectiveness of the proposed scheme.
{"title":"Passive radar detection with DVB-T signals","authors":"Ying Yin, Shunsheng Zhang, F. Wu, Zhulin Zong, Wei Zhang","doi":"10.1109/RADAR.2016.8059601","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059601","url":null,"abstract":"Passive radar system exploits illuminators of opportunity (IOs), such as television and radio, to detect and track moving targets. In this paper, we propose a new passive radar detection scheme with DVB-T signals. A large time-bandwidth-product signal is first generated by using multiple channels DVB-T signals. Then, a Radon-Fourier transform (RFT) algorithm is applied to achieve long-time coherent integration. In doing so, the moving target can be detected in low signal-to-noise ratio (SNR) situation. Simulation results validate the effectiveness of the proposed scheme.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121456493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059244
Yuanbin Ma, Zhaocheng Yang, Jingxiong Huang, Jianjun Huang, Li Kang
In this paper, motivated by the success of coprime array in the direction-of-arrival (DOA) estimation, we introduce the idea of coprime pulse repetition interval (PRI) into the space-time adaptive processing (STAP) airborne radar. Through transmitting and receiving the pulses with coprime PRI, we can reduce the transmitting energy and improve the capabilities of electronic counter-countermeasures (ECCM). We use the lags between the receiving pulses to construct virtual pulses. By using the virtual pulses, we can obtain a new snapshot with a larger dimension than the real one. The constructed snapshots are exploited to estimate the clutter-plus-noise covariance matrix and then to form the STAP filter. Simulation results show that the proposed coprime PRI strategy STAP radar can achieve a good performance with reduced pulses.
{"title":"Space-time adaptive processing airborne radar with coprime pulse repetition interval","authors":"Yuanbin Ma, Zhaocheng Yang, Jingxiong Huang, Jianjun Huang, Li Kang","doi":"10.1109/RADAR.2016.8059244","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059244","url":null,"abstract":"In this paper, motivated by the success of coprime array in the direction-of-arrival (DOA) estimation, we introduce the idea of coprime pulse repetition interval (PRI) into the space-time adaptive processing (STAP) airborne radar. Through transmitting and receiving the pulses with coprime PRI, we can reduce the transmitting energy and improve the capabilities of electronic counter-countermeasures (ECCM). We use the lags between the receiving pulses to construct virtual pulses. By using the virtual pulses, we can obtain a new snapshot with a larger dimension than the real one. The constructed snapshots are exploited to estimate the clutter-plus-noise covariance matrix and then to form the STAP filter. Simulation results show that the proposed coprime PRI strategy STAP radar can achieve a good performance with reduced pulses.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115223263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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