Pub Date : 2015-10-05DOI: 10.1109/SSPD.2015.7288506
Abhinoy Kumar Singh, S. Bhaumik
In this paper, an improved filter has been proposed for solving the nonlinear estimation problem. The intractable integral appeared while solving the nonlinear estimation problem is decomposed into two parts, namely the surface and the line integrals. The surface integral is solved by using the arbitrary odd degree spherical cubature rule and the line integral is solved with any order Gauss-Laguerre quadrature rule. The proposed filter is named as Improved high-degree cubature Kalman filter (IHDCKF). The filter is applied to estimate the states of a nonlinear system and it shows enhanced accuracy compared to the cubature Kalman filter (CKF), the cubature quadrature Kalman filter (CQKF) and the high- degree cubature Kalman filter (HDCKF).
{"title":"Improved High-Degree Cubature Kalman Filter","authors":"Abhinoy Kumar Singh, S. Bhaumik","doi":"10.1109/SSPD.2015.7288506","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288506","url":null,"abstract":"In this paper, an improved filter has been proposed for solving the nonlinear estimation problem. The intractable integral appeared while solving the nonlinear estimation problem is decomposed into two parts, namely the surface and the line integrals. The surface integral is solved by using the arbitrary odd degree spherical cubature rule and the line integral is solved with any order Gauss-Laguerre quadrature rule. The proposed filter is named as Improved high-degree cubature Kalman filter (IHDCKF). The filter is applied to estimate the states of a nonlinear system and it shows enhanced accuracy compared to the cubature Kalman filter (CKF), the cubature quadrature Kalman filter (CQKF) and the high- degree cubature Kalman filter (HDCKF).","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128529464","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288508
Yuanyi Zhao, M. Johnston, C. Tsimenidis, Li Chen
Physical-Layer Network Coding (PNC) employed on a conventional two-way relay channel (TWRC) is an active research area due to the potential doubling of the throughput compared with traditional routing. In this paper, we investigate the effects of impulsive noise added at the relay of a TWRC employing link-by-link coded PNC, where the coding scheme of interest is the turbo code. The Gaussian mixture model is chosen to model the impulsive noise and its effect on the performance of rate 1/2 and rate 1/3 turbo codes on the TWRC is evaluated through simulation results and extrinsic information transfer (ExIT) charts. An error floor analysis is also presented for different mixtures, α, of impulsive noise and theoretical bounds are derived that explain the source of the error floors exhibited in the simulation results.
{"title":"Link-By-Link Coded Physical Layer Network Coding on Impulsive Noise Channels","authors":"Yuanyi Zhao, M. Johnston, C. Tsimenidis, Li Chen","doi":"10.1109/SSPD.2015.7288508","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288508","url":null,"abstract":"Physical-Layer Network Coding (PNC) employed on a conventional two-way relay channel (TWRC) is an active research area due to the potential doubling of the throughput compared with traditional routing. In this paper, we investigate the effects of impulsive noise added at the relay of a TWRC employing link-by-link coded PNC, where the coding scheme of interest is the turbo code. The Gaussian mixture model is chosen to model the impulsive noise and its effect on the performance of rate 1/2 and rate 1/3 turbo codes on the TWRC is evaluated through simulation results and extrinsic information transfer (ExIT) charts. An error floor analysis is also presented for different mixtures, α, of impulsive noise and theoretical bounds are derived that explain the source of the error floors exhibited in the simulation results.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125876182","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288499
Doğan Yildiz, S. Karagol, O. Ozgonenel, Satish Tadiparthi, M. Bikdash
This paper presents a modification of 3N Time of Arrival (TOA) and a reliable Time Difference of Arrival (TDOA) based localization algorithms. TDOA is formulated using the parametric equations of the hyperbolas whose intersections are candidate locations for the nodes to be localized. The TDOA algorithm is guaranteed to find all possible relevant solutions, even when implemented on a computational node with limited capability. Monte- Carlo simulations were used to assess the performance for both algorithms.
{"title":"A Novel Self Localization Approach for Sensors","authors":"Doğan Yildiz, S. Karagol, O. Ozgonenel, Satish Tadiparthi, M. Bikdash","doi":"10.1109/SSPD.2015.7288499","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288499","url":null,"abstract":"This paper presents a modification of 3N Time of Arrival (TOA) and a reliable Time Difference of Arrival (TDOA) based localization algorithms. TDOA is formulated using the parametric equations of the hyperbolas whose intersections are candidate locations for the nodes to be localized. The TDOA algorithm is guaranteed to find all possible relevant solutions, even when implemented on a computational node with limited capability. Monte- Carlo simulations were used to assess the performance for both algorithms.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122268161","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288511
Murat Uney, B. Mulgrew, Daniel E. Clark
In this work, we consider the front-end processing for an active sensor. We are interested in estimating signal amplitude and noise power based on the outputs from filters that match transmitted waveforms at different ranges and bearing angles. These parameters identify the distributions in, for example, likelihood ratio tests used by detection algorithms and characterise the probability of detection and false alarm rates. Because they are observed through measurements induced by a (hidden) target process, the associated parameter likelihood has a time recursive structure which involves estimation of the target state based on the filter outputs. We use a track-before-detect scheme for maintaining a Bernoulli target model and updating the parameter likelihood. We use a maximum likelihood strategy and demonstrate the efficacy of the proposed approach with an example.
{"title":"Maximum Likelihood Signal Parameter Estimation via Track Before Detect","authors":"Murat Uney, B. Mulgrew, Daniel E. Clark","doi":"10.1109/SSPD.2015.7288511","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288511","url":null,"abstract":"In this work, we consider the front-end processing for an active sensor. We are interested in estimating signal amplitude and noise power based on the outputs from filters that match transmitted waveforms at different ranges and bearing angles. These parameters identify the distributions in, for example, likelihood ratio tests used by detection algorithms and characterise the probability of detection and false alarm rates. Because they are observed through measurements induced by a (hidden) target process, the associated parameter likelihood has a time recursive structure which involves estimation of the target state based on the filter outputs. We use a track-before-detect scheme for maintaining a Bernoulli target model and updating the parameter likelihood. We use a maximum likelihood strategy and demonstrate the efficacy of the proposed approach with an example.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132678180","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 : 2015-10-05DOI: 10.1049/iet-spr.2014.0331
H. Ruan, R. D. Lamare
This paper proposes low-complexity robust adaptive beamforming (RAB) techniques based on shrinkage methods. We firstly briefly review a Low- Complexity Shrinkage-Based Mismatch Estimation (LOCSME) batch algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is also estimated with a recursive matrix shrinkage method. Then we develop low complexity adaptive robust version of the conjugate gradient (CG) algorithm to both estimate the steering vector mismatch and update the beamforming weights. A computational complexity study of the proposed and existing algorithms is carried out. Simulations are conducted in local scattering scenarios and comparisons to existing RAB techniques are provided.
{"title":"Low-Complexity Robust Adaptive Beamforming Algorithms Exploiting Shrinkage for Mismatch Estimation","authors":"H. Ruan, R. D. Lamare","doi":"10.1049/iet-spr.2014.0331","DOIUrl":"https://doi.org/10.1049/iet-spr.2014.0331","url":null,"abstract":"This paper proposes low-complexity robust adaptive beamforming (RAB) techniques based on shrinkage methods. We firstly briefly review a Low- Complexity Shrinkage-Based Mismatch Estimation (LOCSME) batch algorithm to estimate the desired signal steering vector mismatch, in which the interference-plus-noise covariance (INC) matrix is also estimated with a recursive matrix shrinkage method. Then we develop low complexity adaptive robust version of the conjugate gradient (CG) algorithm to both estimate the steering vector mismatch and update the beamforming weights. A computational complexity study of the proposed and existing algorithms is carried out. Simulations are conducted in local scattering scenarios and comparisons to existing RAB techniques are provided.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127804653","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288525
Sidharth Shukla, V. Bhatia
Wireless mesh networks (WMN) are the networks of the future which are flexible, easy to deploy and can support high data rate triple play (voice, video and data) services. WMNs are ideal for future defense networks. WMN can operate on multi protocols ranging from WiFi, WiMax and LTE. To enable the support of high data rate services WMN should incorporate optimum traffic scheduling algorithms which will improve the performance of the WMN in highly loaded traffic scenarios for a combat communication network. In this paper, we propose an efficient traffic scheduling algorithms to improve the overall blocking probability of the WMN employed for defense networks and the same is substantiated by the simulation results.
{"title":"Traffic Scheduling Algorithm for Wireless Mesh Networks Based Defense Networks Incorporating Centralized Scheduling Architecture","authors":"Sidharth Shukla, V. Bhatia","doi":"10.1109/SSPD.2015.7288525","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288525","url":null,"abstract":"Wireless mesh networks (WMN) are the networks of the future which are flexible, easy to deploy and can support high data rate triple play (voice, video and data) services. WMNs are ideal for future defense networks. WMN can operate on multi protocols ranging from WiFi, WiMax and LTE. To enable the support of high data rate services WMN should incorporate optimum traffic scheduling algorithms which will improve the performance of the WMN in highly loaded traffic scenarios for a combat communication network. In this paper, we propose an efficient traffic scheduling algorithms to improve the overall blocking probability of the WMN employed for defense networks and the same is substantiated by the simulation results.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115826592","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288498
S. Miller, Xue Zhang, A. Spanias
Multipath is the dominant error source in precise positioning Global Navigation Satellite Systems (GNSS) such as the United States Global Positioning System (GPS). These systems utilize the satellite signal time of arrival estimates to solve for position. Multipath corrupts the time of arrival estimates by distorting the signal tracking phase discriminator; which results in a slowly time- varying phase bias. This bias ranges from several centimeters to tens of meters. The submeter bias is the most problematic for centimeter positioning systems. Moreover, in addition to multipath, the GPS spread spectrum code is unbalanced for certain space vehicles which can lead to a code tracking phase bias. A new correlation kernel is proposed as part of a multipath mitigating delay-locked- loop code phase discriminator that does not suffer a tracking bias due to unbalanced spreading codes. This new algorithm performance is compared to existing techniques with respect to position bias and robustness.
{"title":"A New Asymmetric Correlation Kernel for GNSS Multipath Mitigation","authors":"S. Miller, Xue Zhang, A. Spanias","doi":"10.1109/SSPD.2015.7288498","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288498","url":null,"abstract":"Multipath is the dominant error source in precise positioning Global Navigation Satellite Systems (GNSS) such as the United States Global Positioning System (GPS). These systems utilize the satellite signal time of arrival estimates to solve for position. Multipath corrupts the time of arrival estimates by distorting the signal tracking phase discriminator; which results in a slowly time- varying phase bias. This bias ranges from several centimeters to tens of meters. The submeter bias is the most problematic for centimeter positioning systems. Moreover, in addition to multipath, the GPS spread spectrum code is unbalanced for certain space vehicles which can lead to a code tracking phase bias. A new correlation kernel is proposed as part of a multipath mitigating delay-locked- loop code phase discriminator that does not suffer a tracking bias due to unbalanced spreading codes. This new algorithm performance is compared to existing techniques with respect to position bias and robustness.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"155–156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116573344","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}
In multiple-input multiple-output radar, to estimate the reflection coefficient, spatial location, and Doppler shift of a target, a derived cost function is usually evaluated and optimized over a grid of points. The performance of such algorithms is directly affected by the size of the grid: increasing the number of points will enhance the resolution of the algorithm but exponentially increase its complexity. In this work, to estimate the parameters of a target, a reduced complexity super resolution algorithm is proposed. For off-the-grid targets, it uses a low order two dimensional fast Fourier transform to determine a suboptimal solution and then an iterative algorithm to jointly estimate the spatial location and Doppler shift. Simulation results show that the mean square estimation error of the proposed estimators achieve the Craḿer-Rao lower bound.
{"title":"Low Complexity Parameter Estimation For Off-the-Grid Targets","authors":"Seifallah Jardak, Sajid Ahmed, Mohamed-Slim Alouini","doi":"10.1109/SSPD.2015.7288509","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288509","url":null,"abstract":"In multiple-input multiple-output radar, to estimate the reflection coefficient, spatial location, and Doppler shift of a target, a derived cost function is usually evaluated and optimized over a grid of points. The performance of such algorithms is directly affected by the size of the grid: increasing the number of points will enhance the resolution of the algorithm but exponentially increase its complexity. In this work, to estimate the parameters of a target, a reduced complexity super resolution algorithm is proposed. For off-the-grid targets, it uses a low order two dimensional fast Fourier transform to determine a suboptimal solution and then an iterative algorithm to jointly estimate the spatial location and Doppler shift. Simulation results show that the mean square estimation error of the proposed estimators achieve the Craḿer-Rao lower bound.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123123536","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288502
Yang Liu, F. Guo, M. Zhang, Wenli Jiang
This paper investigates the problem of extracting the pulse repetition interval (PRI) of stationary pulsed radar emitter from noisy time of arrival(TOA) measurements with missing observations (incomplete) by the moving receiver. The relative motion between the receiver and emitter induces the large estimation bias to estimate PRI, we first discuss the conditions on which identifying the period integer numbers under the circumstance of relative movement, then propose two robust algorithms based on compensating delay of each observations on emitter's status space grids. The proposed algorithms can efficiently reduce the estimation bias introduced by model mismatch without the requirement of specific emitter location information. Simulation studies indicates that the proposed solutions can improve the PRI estimation accuracy.
{"title":"Extraction of Pulse Repetition Interval Based on Incomplete, Noisy TOA Measurements by the Moving Passive Receiver","authors":"Yang Liu, F. Guo, M. Zhang, Wenli Jiang","doi":"10.1109/SSPD.2015.7288502","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288502","url":null,"abstract":"This paper investigates the problem of extracting the pulse repetition interval (PRI) of stationary pulsed radar emitter from noisy time of arrival(TOA) measurements with missing observations (incomplete) by the moving receiver. The relative motion between the receiver and emitter induces the large estimation bias to estimate PRI, we first discuss the conditions on which identifying the period integer numbers under the circumstance of relative movement, then propose two robust algorithms based on compensating delay of each observations on emitter's status space grids. The proposed algorithms can efficiently reduce the estimation bias introduced by model mismatch without the requirement of specific emitter location information. Simulation studies indicates that the proposed solutions can improve the PRI estimation accuracy.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115343933","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 : 2015-10-05DOI: 10.1109/SSPD.2015.7288500
M. Contu, M. Bucciarelli, P. Lombardo, F. Madia, Rossella Stallone, Marco Massardo
In this paper some potential system and processing advantages of conformal cone shaped digital array radar have been investigated, in particular in relation to potential alternative approaches for angle estimation with respect to the traditional monopulse. First of all potential benefit in terms of reduction of the number of radiating elements is shown when a conical array is considered with respect to a traditional system formed by four planar arrays, if a coverage of 360° must be assured. Secondly, having in mind an innovative digital array system where the received signals are analog to digital converted at element level and the corresponding data are possibly transferred to a central elaboration unit, an alternative approach is investigated for angular estimation. In this paper we derive the theoretical expression of the Cramer Rao Lower Bound for elevation angle estimation using a cluster of beams; we compare the limit performance of the traditional approach for angle estimation based on Sum and Difference beams with the approach based on a crowded cluster of RX beams properly spaced. The approaches show approximately equivalent performance, making the second particularly interesting for those situations where monopulse is known to experience performance degradation, as low elevation angle estimation; in this particular case an example of cluster design is shown, where the direct signal from a low altitude target must compete with a specular multipath.
{"title":"Direction of Arrival Estimation Using a Cluster of Beams in a Cone-Shaped Digital Array Radar","authors":"M. Contu, M. Bucciarelli, P. Lombardo, F. Madia, Rossella Stallone, Marco Massardo","doi":"10.1109/SSPD.2015.7288500","DOIUrl":"https://doi.org/10.1109/SSPD.2015.7288500","url":null,"abstract":"In this paper some potential system and processing advantages of conformal cone shaped digital array radar have been investigated, in particular in relation to potential alternative approaches for angle estimation with respect to the traditional monopulse. First of all potential benefit in terms of reduction of the number of radiating elements is shown when a conical array is considered with respect to a traditional system formed by four planar arrays, if a coverage of 360° must be assured. Secondly, having in mind an innovative digital array system where the received signals are analog to digital converted at element level and the corresponding data are possibly transferred to a central elaboration unit, an alternative approach is investigated for angular estimation. In this paper we derive the theoretical expression of the Cramer Rao Lower Bound for elevation angle estimation using a cluster of beams; we compare the limit performance of the traditional approach for angle estimation based on Sum and Difference beams with the approach based on a crowded cluster of RX beams properly spaced. The approaches show approximately equivalent performance, making the second particularly interesting for those situations where monopulse is known to experience performance degradation, as low elevation angle estimation; in this particular case an example of cluster design is shown, where the direct signal from a low altitude target must compete with a specular multipath.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115858651","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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