Pub Date : 2016-10-01DOI: 10.1109/RADAR.2016.8059129
Ligang Wang, Lulu Tan
Oceanology is playing an important role in economy and social development. Ocean surveillance is of great importance for protecting maritime interests, marine pollution monitoring and shipping management. Microwave sensing of the ocean using synthetic aperture radar (SAR) is effective and of great interest because of the high spatial resolution, high precision information extraction capability and the almost instantaneous observation potential of large ocean areas. Airborne SAR can implement instantaneous detection to specific area, which is very valuable for emphasis marine area and emergency surveillance. In this paper, an airborne ocean surveillance SAR system is introduced and its application experiment results are demonstrated. Experiment results show the great potential of SAR in ocean applications.
{"title":"An airborne ocean surveillance SAR system and preliminary experiments","authors":"Ligang Wang, Lulu Tan","doi":"10.1109/RADAR.2016.8059129","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059129","url":null,"abstract":"Oceanology is playing an important role in economy and social development. Ocean surveillance is of great importance for protecting maritime interests, marine pollution monitoring and shipping management. Microwave sensing of the ocean using synthetic aperture radar (SAR) is effective and of great interest because of the high spatial resolution, high precision information extraction capability and the almost instantaneous observation potential of large ocean areas. Airborne SAR can implement instantaneous detection to specific area, which is very valuable for emphasis marine area and emergency surveillance. In this paper, an airborne ocean surveillance SAR system is introduced and its application experiment results are demonstrated. Experiment results show the great potential of SAR in ocean applications.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"64 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":"126661490","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.2016.8059570
Wang Luoshengbin, Xu Zhenhai, L. Xinhua, D. Chong
Detection of unresolved targets is an important prerequisite to the resolution of unresolved targets. This paper points out the difference of monopulse ratio between a single target and unresolved targets. After approximate analysis of the monopulse ratio distribution, unresolved targets detector for plane array radar is put forward. Numerical experiment results demonstrate the performance of the proposed method.
{"title":"Detection of unresolved targets for plane array radar based on monopulse ratio","authors":"Wang Luoshengbin, Xu Zhenhai, L. Xinhua, D. Chong","doi":"10.1109/RADAR.2016.8059570","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059570","url":null,"abstract":"Detection of unresolved targets is an important prerequisite to the resolution of unresolved targets. This paper points out the difference of monopulse ratio between a single target and unresolved targets. After approximate analysis of the monopulse ratio distribution, unresolved targets detector for plane array radar is put forward. Numerical experiment results demonstrate the performance of the proposed method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"117 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":"126781187","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.2016.8059261
Gaoru Xue, Yan Liang, Wenchao Zhan, Yanan Yong, Ping Qiao
This paper considers the highly maneuvering target tracking as a discrete-time stochastic system with generalized unknown disturbance input, which can represent an arbitrary linear combination of dynamic, random, and deterministic disturbance inputs. The proposed filter based on upper bound filter (UBF) can adaptively optimize adjust factor to find the globally optimal solution of covariance matrices of the state predictions, innovation and estimates. To reduce the linearization error, a iterative optimization frame is designed. The experiment on "S maneuver" of anti-ship missile shows that the proposed filter can significantly reduce the peak estimation errors due to maneuvers.
{"title":"A novel adaptive filter for highly maneuvering target","authors":"Gaoru Xue, Yan Liang, Wenchao Zhan, Yanan Yong, Ping Qiao","doi":"10.1109/RADAR.2016.8059261","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059261","url":null,"abstract":"This paper considers the highly maneuvering target tracking as a discrete-time stochastic system with generalized unknown disturbance input, which can represent an arbitrary linear combination of dynamic, random, and deterministic disturbance inputs. The proposed filter based on upper bound filter (UBF) can adaptively optimize adjust factor to find the globally optimal solution of covariance matrices of the state predictions, innovation and estimates. To reduce the linearization error, a iterative optimization frame is designed. The experiment on \"S maneuver\" of anti-ship missile shows that the proposed filter can significantly reduce the peak estimation errors due to maneuvers.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"17 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":"122773719","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.2016.8059151
Jiadong Liang, Tianxian Zhang, Yichuan Yang, G. Cui, L. Kong, Xiaobo Yang, Jianyu Yang
In this paper, a preferential optimization problem of antenna placement for a distributed Multi-Input Multi-Output (MIMO) radar is studied. Considering multiple surveillance regions, the radar performances of preferential regions need to be improved and more choices of placement schemes for desired performance need to be provided. Therefore, we use the Particle Swarm Optimiztion (PSO) with reference point to solve the antenna placement problems. By setting reference points, the performance values of preferential surveillance regions will converge to reference points and reach our requirement. Then, we analyse the performance of proposed algorithm. Finally, numerical results are provided to verify the validity of the proposed algorithm.
{"title":"Preferential optimal antenna placement for MIMO radar under the situation of multiple surveillance regions","authors":"Jiadong Liang, Tianxian Zhang, Yichuan Yang, G. Cui, L. Kong, Xiaobo Yang, Jianyu Yang","doi":"10.1109/RADAR.2016.8059151","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059151","url":null,"abstract":"In this paper, a preferential optimization problem of antenna placement for a distributed Multi-Input Multi-Output (MIMO) radar is studied. Considering multiple surveillance regions, the radar performances of preferential regions need to be improved and more choices of placement schemes for desired performance need to be provided. Therefore, we use the Particle Swarm Optimiztion (PSO) with reference point to solve the antenna placement problems. By setting reference points, the performance values of preferential surveillance regions will converge to reference points and reach our requirement. Then, we analyse the performance of proposed algorithm. Finally, numerical results are provided to verify the validity of the proposed algorithm.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"186 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":"114171857","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.2016.8059229
Xiangyang Liu, Jianhang Zhang, Xiaoting Li, Haiyan Zhao, Jing Wang
In this paper, the method of sparse sampling and compressed sensing imaging for forward-looking array SAR is proposed. It is shown that the number of the scatterers in the altitude direction is finite for every observation scene, but the sparse sampling method is designed along the along-track direction in this paper, which is proved to be effective for forward-looking array SAR. Meanwhile, the compressed sensing imaging method is presented to reconstruct the 3D image using the sparse sampling data. The results of simulation experiments validate the effectivity furtherly.
{"title":"The sparse sampling and compressed sensing imaging for forward-looking array SAR","authors":"Xiangyang Liu, Jianhang Zhang, Xiaoting Li, Haiyan Zhao, Jing Wang","doi":"10.1109/RADAR.2016.8059229","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059229","url":null,"abstract":"In this paper, the method of sparse sampling and compressed sensing imaging for forward-looking array SAR is proposed. It is shown that the number of the scatterers in the altitude direction is finite for every observation scene, but the sparse sampling method is designed along the along-track direction in this paper, which is proved to be effective for forward-looking array SAR. Meanwhile, the compressed sensing imaging method is presented to reconstruct the 3D image using the sparse sampling data. The results of simulation experiments validate the effectivity furtherly.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"33 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":"122085261","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.2016.8059551
Ling Huang, Yu Zhang, Changyong Pan, Jian Song
Integrated radar and communication system is a new concept that traditionally independent radar and communication functions can be merged into one hardware platform, which can substantially solve problems like high cost, complicated electromagnetic environment and inefficient information processing and so on. However, most papers concentrate on realising the integration function based existing phased array radar, while digital array radar is the main trend of future applications. Based on digital array radar, the signal detection scheme in conventional communications is not applicable any more for the sharply increased antennas. In this paper, we proposed a Gaussian approximate message passing based algorithm to detect the signal. The proposed method is naturally suitable for large-scale problems, which solves the issues by estimating the expectation and the variance. By just multiplication operations, the proposed algorithm exhibits fast convergence characteristics. Simulation results show that the proposed algorithm can effectively solve the digital array radar based signal detection problem with reduced complexity, and outperforms the conventional linear minimum mean square error (LMMSE) detector by 3dB-6dB.
{"title":"Digital array radar based Gaussian approximate message passing signal detection scheme for integrated radar and communication system","authors":"Ling Huang, Yu Zhang, Changyong Pan, Jian Song","doi":"10.1109/RADAR.2016.8059551","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059551","url":null,"abstract":"Integrated radar and communication system is a new concept that traditionally independent radar and communication functions can be merged into one hardware platform, which can substantially solve problems like high cost, complicated electromagnetic environment and inefficient information processing and so on. However, most papers concentrate on realising the integration function based existing phased array radar, while digital array radar is the main trend of future applications. Based on digital array radar, the signal detection scheme in conventional communications is not applicable any more for the sharply increased antennas. In this paper, we proposed a Gaussian approximate message passing based algorithm to detect the signal. The proposed method is naturally suitable for large-scale problems, which solves the issues by estimating the expectation and the variance. By just multiplication operations, the proposed algorithm exhibits fast convergence characteristics. Simulation results show that the proposed algorithm can effectively solve the digital array radar based signal detection problem with reduced complexity, and outperforms the conventional linear minimum mean square error (LMMSE) detector by 3dB-6dB.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"106 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":"116751266","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.2016.8059555
Yanwen Jiang, Hongqiang Wang, B. Deng, Yuliang Qin, Kang Liu
The random phase errors existing in the terahertz (THz) radar system, usually lead to the range profile broadened and defocused, which should be compensated. In this paper, a compensation method based on Bayesian compressive sensing (BCS) is proposed. Firstly, the reconstruction model containing the random phase errors is established. Subsequently, the phase errors is obtained using the maximum likelihood estimation, and then, the radar echo is compensated with the phase errors in time domain to focus the range profile. Experimental results based on simulation data demonstrated that the proposed method can produce a relatively well-focused range profile of target in terms of various signal to noise ratio (SNR) levels. Moreover, the comparison results indicate that the iteration number increased with the descending of SNR.
{"title":"A random phase compensation method for terahertz radar","authors":"Yanwen Jiang, Hongqiang Wang, B. Deng, Yuliang Qin, Kang Liu","doi":"10.1109/RADAR.2016.8059555","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059555","url":null,"abstract":"The random phase errors existing in the terahertz (THz) radar system, usually lead to the range profile broadened and defocused, which should be compensated. In this paper, a compensation method based on Bayesian compressive sensing (BCS) is proposed. Firstly, the reconstruction model containing the random phase errors is established. Subsequently, the phase errors is obtained using the maximum likelihood estimation, and then, the radar echo is compensated with the phase errors in time domain to focus the range profile. Experimental results based on simulation data demonstrated that the proposed method can produce a relatively well-focused range profile of target in terms of various signal to noise ratio (SNR) levels. Moreover, the comparison results indicate that the iteration number increased with the descending of SNR.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"50 3 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":"116823050","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.2016.8059390
K. Yu
Advanced monopulse processing techniques such as mainlobe cancellation, 2-target monopulse and an enhanced angle-estimation technique based on 2 sets of monopulse ratios make use of an additional delta-delta beam compared with the conventional monopulse system. The salient feature of the mainlobe cancellation technique is the maintenance of monopulse angle estimation accuracy while canceling a jammer within the main-beam. The technique is based on an orthogonal nulling concept where jamming is canceled in one angular domain and monopulse processing is carried out in another angular domain. This feature can also be described in terms of antenna product beam patterns where the common adapted beam patterns are canceled out leaving the monopulse ratios un-distorted. In this paper, we present some extensions of this technique for coping with multiple mainlobe and/or sidelobe jamming using the digital beamforming capability.
{"title":"Orthogonal nulling of multiple jammers with monopulse preserving","authors":"K. Yu","doi":"10.1109/RADAR.2016.8059390","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059390","url":null,"abstract":"Advanced monopulse processing techniques such as mainlobe cancellation, 2-target monopulse and an enhanced angle-estimation technique based on 2 sets of monopulse ratios make use of an additional delta-delta beam compared with the conventional monopulse system. The salient feature of the mainlobe cancellation technique is the maintenance of monopulse angle estimation accuracy while canceling a jammer within the main-beam. The technique is based on an orthogonal nulling concept where jamming is canceled in one angular domain and monopulse processing is carried out in another angular domain. This feature can also be described in terms of antenna product beam patterns where the common adapted beam patterns are canceled out leaving the monopulse ratios un-distorted. In this paper, we present some extensions of this technique for coping with multiple mainlobe and/or sidelobe jamming using the digital beamforming capability.","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":"129567080","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.2016.8059511
Long Li, Zheng Liu
To identify the out-of-database targets in the process of radar ground target recognition with high resolution range profile, this paper proposes an improved radar ground target classifier based on the covariance distribution of the space of training features, namely Dual-SVDD classifier. In the training phase, a double correlate SVDD structure is constructed in feature space and a multi-region data description is obtained based on the covariance of target training database. The new classifier separates the training sets into several regions, which are independent identically uniform distributed. Then, the category determination of testing target data is based on the support vectors and the region radial of the SVDD method with the multi-region data description. This method can work without the template of out-of-database samples, which improves the effectiveness of target identification. Finally, the experiment based on the measured data verifies its excellent performance of identification.
{"title":"Radar high resolution range profile recognition via Dual-SVDD classifier","authors":"Long Li, Zheng Liu","doi":"10.1109/RADAR.2016.8059511","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059511","url":null,"abstract":"To identify the out-of-database targets in the process of radar ground target recognition with high resolution range profile, this paper proposes an improved radar ground target classifier based on the covariance distribution of the space of training features, namely Dual-SVDD classifier. In the training phase, a double correlate SVDD structure is constructed in feature space and a multi-region data description is obtained based on the covariance of target training database. The new classifier separates the training sets into several regions, which are independent identically uniform distributed. Then, the category determination of testing target data is based on the support vectors and the region radial of the SVDD method with the multi-region data description. This method can work without the template of out-of-database samples, which improves the effectiveness of target identification. Finally, the experiment based on the measured data verifies its excellent performance of identification.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"6 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":"129860570","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.2016.8059392
Lei Yu, Yinsheng Wei, Weiwei Ji
MIMO radar based on subarrays in transmission can achieve superior performance compared with the conventional phased-array radar and the MIMO radar with omni-directional transmission, since it combines the advantages of these two radars. In this paper we consider the wide transmit beamforming synthesis for the subarrays in MIMO radar. We propose an adaptive gradient algorithm to optimize the transmit beampattern for the subarrays. The resulted beampattern can cover the entire wide observation area in the mainlobe and simultaneously have low mainlobe ripple and low sidelobe level. Simulation results have been provided to verify the effectiveness of this proposed method.
{"title":"Wide transmit beamforming for the subarrays in MIMO radar","authors":"Lei Yu, Yinsheng Wei, Weiwei Ji","doi":"10.1109/RADAR.2016.8059392","DOIUrl":"https://doi.org/10.1109/RADAR.2016.8059392","url":null,"abstract":"MIMO radar based on subarrays in transmission can achieve superior performance compared with the conventional phased-array radar and the MIMO radar with omni-directional transmission, since it combines the advantages of these two radars. In this paper we consider the wide transmit beamforming synthesis for the subarrays in MIMO radar. We propose an adaptive gradient algorithm to optimize the transmit beampattern for the subarrays. The resulted beampattern can cover the entire wide observation area in the mainlobe and simultaneously have low mainlobe ripple and low sidelobe level. Simulation results have been provided to verify the effectiveness of this proposed method.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"52 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":"128229625","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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