Pub Date : 2014-05-19DOI: 10.1109/RADAR.2014.6875742
L. Li, Haiguang Yang, G. Cui, L. Kong, Xiaobo Yang
This paper considers a radar system capable of adaptively adjusting its transmitted waveform, by which the system is able to dynamically mitigate the interference of the clutter, thus improve the detection performance. The key feature of the adaptive mechanism is the optimum waveform design, which is a complex multi-dimension optimizing problem and such a problem in this particular application has not yet been fully studied. Based on the structure of the general likelihood ration test (GLRT) detector and the compound-Gaussian (CG) clutter model, we derive the design objective function for the optimal phase modulated (PM) waveform. Then we simplify the objective function and propose an efficient iterative approach to solve this problem based on the pattern search algorithm. Numerical simulations confirm that the proposed algorithm is efficient to produce optimized waveforms for clutter mitigation in various conditions.
{"title":"Phase-modulated waveform design for target detection in clutter","authors":"L. Li, Haiguang Yang, G. Cui, L. Kong, Xiaobo Yang","doi":"10.1109/RADAR.2014.6875742","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875742","url":null,"abstract":"This paper considers a radar system capable of adaptively adjusting its transmitted waveform, by which the system is able to dynamically mitigate the interference of the clutter, thus improve the detection performance. The key feature of the adaptive mechanism is the optimum waveform design, which is a complex multi-dimension optimizing problem and such a problem in this particular application has not yet been fully studied. Based on the structure of the general likelihood ration test (GLRT) detector and the compound-Gaussian (CG) clutter model, we derive the design objective function for the optimal phase modulated (PM) waveform. Then we simplify the objective function and propose an efficient iterative approach to solve this problem based on the pattern search algorithm. Numerical simulations confirm that the proposed algorithm is efficient to produce optimized waveforms for clutter mitigation in various conditions.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131839663","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875693
S. Gogineni, M. Rangaswamy, B. Rigling, A. Nehorai
Mobile communications systems are being increasingly deployed and the favorable ambiguity function properties of these signals make them useful for passive bistatic radar applications. Further, simultaneously using multiple illuminators of opportunity in a multistatic configuration will enhance the radar performance, providing spatial diversity and increased resolution. We compute modified Cramer-Rao lower bounds (MCRLB) for the target parameter estimation error using universal mobile telecommunications system (UMTS) signals as illuminators of opportunity for passive multistatic radar systems.
{"title":"Cramer-Rao bound analysis for passive multistatic radar using UMTS signals","authors":"S. Gogineni, M. Rangaswamy, B. Rigling, A. Nehorai","doi":"10.1109/RADAR.2014.6875693","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875693","url":null,"abstract":"Mobile communications systems are being increasingly deployed and the favorable ambiguity function properties of these signals make them useful for passive bistatic radar applications. Further, simultaneously using multiple illuminators of opportunity in a multistatic configuration will enhance the radar performance, providing spatial diversity and increased resolution. We compute modified Cramer-Rao lower bounds (MCRLB) for the target parameter estimation error using universal mobile telecommunications system (UMTS) signals as illuminators of opportunity for passive multistatic radar systems.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131892243","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875793
Yue Ai, Wei Yi, G. Cui, L. Kong
This paper addresses the multi-target localization problem for noncoherent multiple-input multiple-output (MIMO) radar with widely separated antennas. To this end, we first adopt a high-dimensional parameter vector, which is the concatenation of the parameters to be estimated for individual targets, and then propose a novel multi-target localization algorithm by estimating the high-dimensional parameter vector based on maximum-likelihood estimation (MLE). However, this solution is usually computationally intractable for most realistic problems as it is involved with a high-dimensional joint maximization. Therefore we also propose a suboptimum algorithm which allows trading better localization accuracy for a much lower implementation complexity. Numerical examples are provided to assess and compare the performances of the proposed multi-target localization algorithms.
{"title":"Multi-target localization for noncoherent MIMO radar with widely separated antennas","authors":"Yue Ai, Wei Yi, G. Cui, L. Kong","doi":"10.1109/RADAR.2014.6875793","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875793","url":null,"abstract":"This paper addresses the multi-target localization problem for noncoherent multiple-input multiple-output (MIMO) radar with widely separated antennas. To this end, we first adopt a high-dimensional parameter vector, which is the concatenation of the parameters to be estimated for individual targets, and then propose a novel multi-target localization algorithm by estimating the high-dimensional parameter vector based on maximum-likelihood estimation (MLE). However, this solution is usually computationally intractable for most realistic problems as it is involved with a high-dimensional joint maximization. Therefore we also propose a suboptimum algorithm which allows trading better localization accuracy for a much lower implementation complexity. Numerical examples are provided to assess and compare the performances of the proposed multi-target localization algorithms.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131902267","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875669
R. Raj
We apply our recently developed concept of mutual exclusivity [1] in the context of discriminative coding, to the problem of learning dictionary for representing signals drawn from N classes in a way that optimizes their discriminability. We first briefly review our mutual-exclusivity concept and then deploy it a simple discriminative dictionary learning algorithm that directly generalizes the well-known KSVD algorithm which is addressed for the traditional problem of signal coding. We demonstrate performance improvements over traditional KSVD based feature extraction schemes and conclude by describing avenues for future research.
{"title":"Discriminative dictionary learning via mutual exclusion","authors":"R. Raj","doi":"10.1109/RADAR.2014.6875669","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875669","url":null,"abstract":"We apply our recently developed concept of mutual exclusivity [1] in the context of discriminative coding, to the problem of learning dictionary for representing signals drawn from N classes in a way that optimizes their discriminability. We first briefly review our mutual-exclusivity concept and then deploy it a simple discriminative dictionary learning algorithm that directly generalizes the well-known KSVD algorithm which is addressed for the traditional problem of signal coding. We demonstrate performance improvements over traditional KSVD based feature extraction schemes and conclude by describing avenues for future research.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134112085","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875783
Bailu Wang, G. Cui, Wei Yi, Suqi Li, L. Kong
This paper considers the target detection problem using the distributed polarimetric MIMO (P-MIMO) radar in the presence of spatially heterogeneous clutter. The polarimetric covariance matrices (PCMs) of the primary and the secondary data are assumed to be random with partial priori knowledge of the environment, sharing some appropriate joint distribution. Two-step strategy is employed to design adaptive detector. Specifically, we first obtain the generalized likelihood ratio test (GLRT) detector by assuming the known PCMs. Then, we derive the maximum posteriori (MAP) estimator of the PCMs by exploiting the priori information, and replace the exact PCMs with their MAP estimates. Finally, we evaluate the proposed adaptive detector via numerical simulations.
{"title":"Adaptive Bayesian detection using polarimetric MIMO radar in spatially heterogeneous clutter","authors":"Bailu Wang, G. Cui, Wei Yi, Suqi Li, L. Kong","doi":"10.1109/RADAR.2014.6875783","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875783","url":null,"abstract":"This paper considers the target detection problem using the distributed polarimetric MIMO (P-MIMO) radar in the presence of spatially heterogeneous clutter. The polarimetric covariance matrices (PCMs) of the primary and the secondary data are assumed to be random with partial priori knowledge of the environment, sharing some appropriate joint distribution. Two-step strategy is employed to design adaptive detector. Specifically, we first obtain the generalized likelihood ratio test (GLRT) detector by assuming the known PCMs. Then, we derive the maximum posteriori (MAP) estimator of the PCMs by exploiting the priori information, and replace the exact PCMs with their MAP estimates. Finally, we evaluate the proposed adaptive detector via numerical simulations.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115936112","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875787
S. Villeval, I. Bilik, Sevgi Zübeyde Gürbuz
Pedestrian safety is one of the major tasks of automotive radars. Pedestrian detection in practical urban scenarios is challenging task due to the strong vertical and horizontal multipath phenomena from the asphalt roads and surrounding buildings, proximity to other obstacles with highradar cross section, and high probability of blockage by other targets. This work addresses the problem of joint pedestrian detection and classification in a practical urban environment by a 24 GHz FMCW automotive radar. The urban RF environment consisting of the asphalt road, vehicles and pedestrian was simulated. Micro-Doppler analysis was used to discriminate between pedestrians, vehicles, and animals. A variety of human activities, including mixed motion sequences were tested in target classification simulations.
{"title":"Application of a 24 GHz FMCW automotive radar for urban target classification","authors":"S. Villeval, I. Bilik, Sevgi Zübeyde Gürbuz","doi":"10.1109/RADAR.2014.6875787","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875787","url":null,"abstract":"Pedestrian safety is one of the major tasks of automotive radars. Pedestrian detection in practical urban scenarios is challenging task due to the strong vertical and horizontal multipath phenomena from the asphalt roads and surrounding buildings, proximity to other obstacles with highradar cross section, and high probability of blockage by other targets. This work addresses the problem of joint pedestrian detection and classification in a practical urban environment by a 24 GHz FMCW automotive radar. The urban RF environment consisting of the asphalt road, vehicles and pedestrian was simulated. Micro-Doppler analysis was used to discriminate between pedestrians, vehicles, and animals. A variety of human activities, including mixed motion sequences were tested in target classification simulations.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125369725","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 : 2014-05-19DOI: 10.1109/RADAR.2014.7133687
H. Hou, X. Mao, Hong Hong, A. Liu
The high resolution multiple signal classification (MUSIC) algorithm provides an efficient way to estimate direction- of-arrival (DOA). However, it performs poorly when weak signals are accompanied with strong ones. To solve this problem, an oblique projection filtering based DOA estimation algorithm is proposed without using a priori knowledge of the sources, such as directions, strength, modulation modes, etc. Numerical results verify the effectiveness of the proposed algorithm. It is shown that a high resolution DOA estimation of the incident sources can be achieved. The detection performances for weak signals are more stable and superior than that of the MUSIC algorithm.
{"title":"An oblique projection filtering based DOA estimation algorithm without a priori knowledge","authors":"H. Hou, X. Mao, Hong Hong, A. Liu","doi":"10.1109/RADAR.2014.7133687","DOIUrl":"https://doi.org/10.1109/RADAR.2014.7133687","url":null,"abstract":"The high resolution multiple signal classification (MUSIC) algorithm provides an efficient way to estimate direction- of-arrival (DOA). However, it performs poorly when weak signals are accompanied with strong ones. To solve this problem, an oblique projection filtering based DOA estimation algorithm is proposed without using a priori knowledge of the sources, such as directions, strength, modulation modes, etc. Numerical results verify the effectiveness of the proposed algorithm. It is shown that a high resolution DOA estimation of the incident sources can be achieved. The detection performances for weak signals are more stable and superior than that of the MUSIC algorithm.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134555124","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875782
Yichuan Yang, G. Cui, Wei Yi, L. Kong, Xiaobo Yang, Jianyu Yang
We consider a moving target detection problem using distributed multiple-input multiple-out (MIMO) radar, where the Signal-to-Noise Ratios (SNRs) in each transmit-receive (T-R) channels are different. We propose two knowledge-based detectors based on the generalized likelihood ratio test (GLRT) rule, both of which require the knowledge of the SNRs relationship among T-R channels. Finally, we evaluate the performance of the derived detectors via computer simulations, and the results illustrate that they outperform conventional detection algorithm.
{"title":"Distributed MIMO radar detection with channel evaluation and selection strategy","authors":"Yichuan Yang, G. Cui, Wei Yi, L. Kong, Xiaobo Yang, Jianyu Yang","doi":"10.1109/RADAR.2014.6875782","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875782","url":null,"abstract":"We consider a moving target detection problem using distributed multiple-input multiple-out (MIMO) radar, where the Signal-to-Noise Ratios (SNRs) in each transmit-receive (T-R) channels are different. We propose two knowledge-based detectors based on the generalized likelihood ratio test (GLRT) rule, both of which require the knowledge of the SNRs relationship among T-R channels. Finally, we evaluate the performance of the derived detectors via computer simulations, and the results illustrate that they outperform conventional detection algorithm.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134373311","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875762
Pilei Yin, Xiaopeng Yang, Q. Liu, T. Long
The distributed coherent aperture radar (DCAR) consisting of several cooperating small aperture radars and a control center is proposed to replace the traditional large aperture radar, which is more easily to transport and less expensive to build. In this paper, the constitution and workflow of DCAR are described at first. In the following, the estimation methods of coherent parameters are introduced. And then, a robust full coherent technology based on step frequency signal is proposed to reduce the effect of time synchronization error. At last, the simulations are carried out to verify the proposed methods.
{"title":"Wideband distributed coherent aperture radar","authors":"Pilei Yin, Xiaopeng Yang, Q. Liu, T. Long","doi":"10.1109/RADAR.2014.6875762","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875762","url":null,"abstract":"The distributed coherent aperture radar (DCAR) consisting of several cooperating small aperture radars and a control center is proposed to replace the traditional large aperture radar, which is more easily to transport and less expensive to build. In this paper, the constitution and workflow of DCAR are described at first. In the following, the estimation methods of coherent parameters are introduced. And then, a robust full coherent technology based on step frequency signal is proposed to reduce the effect of time synchronization error. At last, the simulations are carried out to verify the proposed methods.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132151","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 : 2014-05-19DOI: 10.1109/RADAR.2014.6875737
M. Ezeoke, K. Tong, Kenneth Mubea
A method to characterize the electromagnetic (EM) signature of barefaced terrain using 3D computer electromagnetic models (CEM) for radar applications is presented. Five barefaced terrain types with different electrical, physical and chemical properties were investigated. They include both homogeneous and heterogeneous terrain types particularly beach sand, gravel and pebble acquired locally and oil sands from Nigeria. The approach develops CEMs using reflectance spectroscopy and dielectric permittivity data. First geochemical signatures were determined using reflectance spectroscopy in the Near Infrared region while dielectric properties were experimentally determined at L-, C- and X-band for multi-frequency radar. Both viscous and hard oil sand indicated resonance effects in the upper C-band. The results provide new information on the complex electrical permittivity ε*(co) and loss tangent, tan ö. Finally a laboratory based approach to measure the relationship between sensor configuration and terrain backscatter for 0.013m3 of terrain samples using microwave measurement techniques in an anechoic chamber is outlined.
{"title":"Electromagnetic characterisation of terrain for unconventional petroleum exploration","authors":"M. Ezeoke, K. Tong, Kenneth Mubea","doi":"10.1109/RADAR.2014.6875737","DOIUrl":"https://doi.org/10.1109/RADAR.2014.6875737","url":null,"abstract":"A method to characterize the electromagnetic (EM) signature of barefaced terrain using 3D computer electromagnetic models (CEM) for radar applications is presented. Five barefaced terrain types with different electrical, physical and chemical properties were investigated. They include both homogeneous and heterogeneous terrain types particularly beach sand, gravel and pebble acquired locally and oil sands from Nigeria. The approach develops CEMs using reflectance spectroscopy and dielectric permittivity data. First geochemical signatures were determined using reflectance spectroscopy in the Near Infrared region while dielectric properties were experimentally determined at L-, C- and X-band for multi-frequency radar. Both viscous and hard oil sand indicated resonance effects in the upper C-band. The results provide new information on the complex electrical permittivity ε*(co) and loss tangent, tan ö. Finally a laboratory based approach to measure the relationship between sensor configuration and terrain backscatter for 0.013m3 of terrain samples using microwave measurement techniques in an anechoic chamber is outlined.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116494782","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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