Pub Date : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343736
Zuchun Ding, Wenying Mo
A novel algorithm to use vehicle sticker (or tag) features and encode the features is proposed. It can make the representation more precise and recognition more accurate. In vehicle recognition or searching, traditional algorithms will be limited because they focus only on the features extracted from colors, logos or sub-types that are not enough to identify a vehicle. Furthermore, the license plate (LP) can be forged easily so the LP is not reliable to identify a specified vehicle. Our algorithm solves this problem by sticker multi-feature encoding. Most vehicles have printed permission labels or certification symbols named vehicle stickers or tags mounted on the frontal glass. These stickers are a kind of special fingerprint features to identify a unique vehicle. Every driver has his own habit to paste different stickers. In this meaning these stickers form specified multi-feature including color, shape, position and amount. Our algorithm encodes the sticker multi-feature to construct structured feature presentation, i.e. the sticker code. In recognition stage, with the matrix distance of the multi-feature encoding, the detailed sticker code can be utilized to distinguish the vehicle types and colors reliably, and can recognize the tiny difference among vehicles with the same colors, logos and even sub-types. Our algorithm decreases the amount of vehicle candidates effectively by accurate feature coding. In our experiments, we coped with 10000 vehicle images taken by public traffic surveillance system to verify the effectiveness of this algorithm in vehicle sticker multi-feature encoding recognition.
{"title":"Vehicle sticker recognition based on multi-feature encoding and feature matrix distance","authors":"Zuchun Ding, Wenying Mo","doi":"10.1109/ICCSNT.2017.8343736","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343736","url":null,"abstract":"A novel algorithm to use vehicle sticker (or tag) features and encode the features is proposed. It can make the representation more precise and recognition more accurate. In vehicle recognition or searching, traditional algorithms will be limited because they focus only on the features extracted from colors, logos or sub-types that are not enough to identify a vehicle. Furthermore, the license plate (LP) can be forged easily so the LP is not reliable to identify a specified vehicle. Our algorithm solves this problem by sticker multi-feature encoding. Most vehicles have printed permission labels or certification symbols named vehicle stickers or tags mounted on the frontal glass. These stickers are a kind of special fingerprint features to identify a unique vehicle. Every driver has his own habit to paste different stickers. In this meaning these stickers form specified multi-feature including color, shape, position and amount. Our algorithm encodes the sticker multi-feature to construct structured feature presentation, i.e. the sticker code. In recognition stage, with the matrix distance of the multi-feature encoding, the detailed sticker code can be utilized to distinguish the vehicle types and colors reliably, and can recognize the tiny difference among vehicles with the same colors, logos and even sub-types. Our algorithm decreases the amount of vehicle candidates effectively by accurate feature coding. In our experiments, we coped with 10000 vehicle images taken by public traffic surveillance system to verify the effectiveness of this algorithm in vehicle sticker multi-feature encoding recognition.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123893766","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343749
P. He, Hongli Chang, Han Gao, ZiYi Wang
In the field of signal process, the real-time and rapidity requirements of signal processing become higher and higher. The filter has been used widely, such as used in detecting and predicting of the signal. Digital filter has many outstanding advantages such as high stability, high precision, design flexible, easy to implement. It can overcome the problems such as voltage drift and temperature drift and noise. With the development of digital technology, digital technology is used to implement filter function. It has gotten people's attention and been used widely.
{"title":"Design of IIR digital filter","authors":"P. He, Hongli Chang, Han Gao, ZiYi Wang","doi":"10.1109/ICCSNT.2017.8343749","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343749","url":null,"abstract":"In the field of signal process, the real-time and rapidity requirements of signal processing become higher and higher. The filter has been used widely, such as used in detecting and predicting of the signal. Digital filter has many outstanding advantages such as high stability, high precision, design flexible, easy to implement. It can overcome the problems such as voltage drift and temperature drift and noise. With the development of digital technology, digital technology is used to implement filter function. It has gotten people's attention and been used widely.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114199814","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343718
Xiao-jing Shi, Honglei Wang, S. Leung
In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l2-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.
{"title":"Iterative sparse channel estimator based on SpaRSA approach","authors":"Xiao-jing Shi, Honglei Wang, S. Leung","doi":"10.1109/ICCSNT.2017.8343718","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343718","url":null,"abstract":"In this paper, an iterative sparse channel estimation for orthogonal frequency division multiplex (OFDM) communication system is investigated based on the sparse reconstruction by separable approximation (SpaRSA), which is regarded as one of the fastest algorithms for l2-lj problem and can obtain its global optimal solution. The proposed estimator comprised of thresholding is applied to detect channel taps. Then, a modified SpaRSA with adaptive regularization parameter is used to refine the estimation of nonzero channel taps. Simulation results for typical sparse channels show effectiveness of the proposed algorithm over other existing methods.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130162614","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343733
L. Deng, Yuefeng Zheng, P. Jia, Sichen Lu, Jiuting Yang
Hyperspectral Images (HSI) have strong spectral correlation compared with ordinary 2D images. Distributed compressed sensing (DCS) happens to exploit both intra-and inter-signal correlation structures among multiple nodes and lends itself well to hyperspectral image compression. In this paper, we propose a new algorithm of adaptive grouping for HSI compression based on the first joint sparsity model (JSM-1) of DCS. This algorithm adaptively divides one hyperspectral image into several groups of bands (GOBs) in accordance with its spectral correlation firstly, to ensure that each group of bands has strong spectral correlation. Every group of bands contains a reference band and the remaining non-reference bands, and then subtracts the reference band from each of the non-reference bands in the same group which makes the structure conform JSM-1. Then the distributed compressed sensing JSM-1 model is applied to hyperspectral image compression, encoding every residual image using CS coding. We use a joint recovery algorithm to reconstruct at the decoder. In this algorithm, the spectral similarity of high spectral images is used to get the data more sparse and improve the reconstruction effect of the compressed image, and the better compression efficiency is obtained. Experiments show the feasibility of the proposed algorithm.
{"title":"Adaptively group based on the first joint sparsity models distributed compressive sensing of hyperspectral image","authors":"L. Deng, Yuefeng Zheng, P. Jia, Sichen Lu, Jiuting Yang","doi":"10.1109/ICCSNT.2017.8343733","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343733","url":null,"abstract":"Hyperspectral Images (HSI) have strong spectral correlation compared with ordinary 2D images. Distributed compressed sensing (DCS) happens to exploit both intra-and inter-signal correlation structures among multiple nodes and lends itself well to hyperspectral image compression. In this paper, we propose a new algorithm of adaptive grouping for HSI compression based on the first joint sparsity model (JSM-1) of DCS. This algorithm adaptively divides one hyperspectral image into several groups of bands (GOBs) in accordance with its spectral correlation firstly, to ensure that each group of bands has strong spectral correlation. Every group of bands contains a reference band and the remaining non-reference bands, and then subtracts the reference band from each of the non-reference bands in the same group which makes the structure conform JSM-1. Then the distributed compressed sensing JSM-1 model is applied to hyperspectral image compression, encoding every residual image using CS coding. We use a joint recovery algorithm to reconstruct at the decoder. In this algorithm, the spectral similarity of high spectral images is used to get the data more sparse and improve the reconstruction effect of the compressed image, and the better compression efficiency is obtained. Experiments show the feasibility of the proposed algorithm.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129089067","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343756
Qusen Chen, R. Xi, Xiaolin Meng, Weiping Jiang
In this paper, we analysed the performance of real-time BDS monitoring system to determine the deformations and vibration of a cable-stayed bridge in Wuhan, China. Two experiments were carried out using reference stations at 2 km to the middle span of the bridge, and the monitoring points placed on the top of the tower, directly at the middle span of the bridge and at the bridge pier. Based on these sites, the precision of BDS deformation monitoring can be assessed and the structural vibration monitoring effect can also be analysed. The experiments demonstrate that, the precision of BDS-based deformation monitoring can be comparable with GPS, and the modal frequency of the bridge obtained by BDS vibration test is very close to the design value. The paper concludes that BDS is capable of providing high precision deflection and accurate modal frequency information in real-time bridge deformation monitoring.
{"title":"Analysis of bridge deformations using real-time BDS measurements","authors":"Qusen Chen, R. Xi, Xiaolin Meng, Weiping Jiang","doi":"10.1109/ICCSNT.2017.8343756","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343756","url":null,"abstract":"In this paper, we analysed the performance of real-time BDS monitoring system to determine the deformations and vibration of a cable-stayed bridge in Wuhan, China. Two experiments were carried out using reference stations at 2 km to the middle span of the bridge, and the monitoring points placed on the top of the tower, directly at the middle span of the bridge and at the bridge pier. Based on these sites, the precision of BDS deformation monitoring can be assessed and the structural vibration monitoring effect can also be analysed. The experiments demonstrate that, the precision of BDS-based deformation monitoring can be comparable with GPS, and the modal frequency of the bridge obtained by BDS vibration test is very close to the design value. The paper concludes that BDS is capable of providing high precision deflection and accurate modal frequency information in real-time bridge deformation monitoring.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128720994","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343667
Yaoting Yue, Shunfang Wang
Discriminated dimensionality reduction algorithm and informative feature representation are equal importance for improving prediction accuracy of protein subnuclear. Based on this thought, this paper simultaneously proposed an effective fused kernel function and an integrated feature expression for predicting protein subnuclear location. To obtain their optimal fusion parameter respectively, the particle swarm optimization (PSO) algorithm was employed to search them during the fusing processes. To verify the feasibility of our proposed approach, a standard public dataset was adopted to carry out the numerical experiment with k-nearest neighbors (KNN) as the classifier. The last results of Jackknife test method can be as high as 94.6779% with our fused kernel and representation, which undoubtedly reveals that our proposed integration method is of efficiency in protein subnuclear localization to a large extent.
{"title":"Protein subnuclear location based on KLDA with fused kernel and effective fusion representation","authors":"Yaoting Yue, Shunfang Wang","doi":"10.1109/ICCSNT.2017.8343667","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343667","url":null,"abstract":"Discriminated dimensionality reduction algorithm and informative feature representation are equal importance for improving prediction accuracy of protein subnuclear. Based on this thought, this paper simultaneously proposed an effective fused kernel function and an integrated feature expression for predicting protein subnuclear location. To obtain their optimal fusion parameter respectively, the particle swarm optimization (PSO) algorithm was employed to search them during the fusing processes. To verify the feasibility of our proposed approach, a standard public dataset was adopted to carry out the numerical experiment with k-nearest neighbors (KNN) as the classifier. The last results of Jackknife test method can be as high as 94.6779% with our fused kernel and representation, which undoubtedly reveals that our proposed integration method is of efficiency in protein subnuclear localization to a large extent.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128043901","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343728
Qiang Lu, Bo Liu, Huaping Hu
As a kind of sharing platform for files, information and resources, Content Sharing Networks (CSNs) are faced with a serious security situation of swarming malicious files, illegal information and spywares, especially the mainstream P2P (Peer-to-Peer) CSNs. Apart from the familiar importance for the rapid development and wide application of CSNs, backbone nodes should have been paid more attention for their significance to monitor and mitigate malicious sharing contents. In this paper, we proposed a comprehensive and effective determining method named MED to distinguish backbone nodes during the longest ever tracking and in-depth analysis of CSNs for nearly four years.
{"title":"A long track on backbone nodes of content sharing networks","authors":"Qiang Lu, Bo Liu, Huaping Hu","doi":"10.1109/ICCSNT.2017.8343728","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343728","url":null,"abstract":"As a kind of sharing platform for files, information and resources, Content Sharing Networks (CSNs) are faced with a serious security situation of swarming malicious files, illegal information and spywares, especially the mainstream P2P (Peer-to-Peer) CSNs. Apart from the familiar importance for the rapid development and wide application of CSNs, backbone nodes should have been paid more attention for their significance to monitor and mitigate malicious sharing contents. In this paper, we proposed a comprehensive and effective determining method named MED to distinguish backbone nodes during the longest ever tracking and in-depth analysis of CSNs for nearly four years.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127698762","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}
Recommender system has become increasingly popular in recent years, since it is an effective way to solve the problem of information overload problem. But it is still subject to some inherent problems, such as data sparseness and cold start. Many studies show that the integration of social network information is a very effective way to solve such issues. The studies on recommendation methods that incorporate social relationships, not only take into account the preferences of the user for the item, but also the interaction between the users according to their behavior and the social relationships. And now, the application of social relationships has extended from the trust relationships to the distrust relationships. While the collaborative filtering is the most important and widely used recommendation method, there is little work on combining with trust and distrust social network relationships. So, this paper proposes the methods of integration the trust and distrust social relationships, TDUCF1 and TDUCF2, and with the improved cosine similarity, to improve the collaborative filtering recommendation algorithm, which combined the users' trust and distrust social relationships, and effectively alleviated the sparseness. The experimental results show that the proposed methods outperform the state-of-art algorithms.
{"title":"Recommendation based on trust and distrust social relationships","authors":"Zhenqian Fei, Wei Sun, Xiaoxin Sun, Guozhong Feng, Bangzuo Zhang","doi":"10.1109/ICCSNT.2017.8343698","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343698","url":null,"abstract":"Recommender system has become increasingly popular in recent years, since it is an effective way to solve the problem of information overload problem. But it is still subject to some inherent problems, such as data sparseness and cold start. Many studies show that the integration of social network information is a very effective way to solve such issues. The studies on recommendation methods that incorporate social relationships, not only take into account the preferences of the user for the item, but also the interaction between the users according to their behavior and the social relationships. And now, the application of social relationships has extended from the trust relationships to the distrust relationships. While the collaborative filtering is the most important and widely used recommendation method, there is little work on combining with trust and distrust social network relationships. So, this paper proposes the methods of integration the trust and distrust social relationships, TDUCF1 and TDUCF2, and with the improved cosine similarity, to improve the collaborative filtering recommendation algorithm, which combined the users' trust and distrust social relationships, and effectively alleviated the sparseness. The experimental results show that the proposed methods outperform the state-of-art algorithms.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127363303","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343687
Hanguang Zhang, Jin Bi, Jie Li, Ke Ma
In order to probe into the data acquisition method of radar echo navigation information technology, the radar unit constitution, the compression principle of sampling data of Lempel-Ziv-Welch (LZW) algorithm and two common compression algorithms are introduced. The influence of network transmission speed on radar echo data acquisition in VxWorks system is also studied. The flow chart of the compression implementation and the network transmission speed comparison diagram are analyzed. The experimental results show that the LZW compression algorithm can achieve a satisfactory compression rate when the radar echo navigation data acquisition is carried out. At the same time, users can use the memory file in VxWorks to read and write, which can speed up the network transmission. Based on the above finding, it is concluded that the data acquisition and research based on radar echo navigation information technology can speed up the network transmission by using the VxWorks system.
{"title":"Data acquisition and researches based on radar echo navigation information technology","authors":"Hanguang Zhang, Jin Bi, Jie Li, Ke Ma","doi":"10.1109/ICCSNT.2017.8343687","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343687","url":null,"abstract":"In order to probe into the data acquisition method of radar echo navigation information technology, the radar unit constitution, the compression principle of sampling data of Lempel-Ziv-Welch (LZW) algorithm and two common compression algorithms are introduced. The influence of network transmission speed on radar echo data acquisition in VxWorks system is also studied. The flow chart of the compression implementation and the network transmission speed comparison diagram are analyzed. The experimental results show that the LZW compression algorithm can achieve a satisfactory compression rate when the radar echo navigation data acquisition is carried out. At the same time, users can use the memory file in VxWorks to read and write, which can speed up the network transmission. Based on the above finding, it is concluded that the data acquisition and research based on radar echo navigation information technology can speed up the network transmission by using the VxWorks system.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134399507","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343713
Cancan Sun, Ronghua Zhou, Hangcheng Han, Xiangyuan Bu
Satellite to ground laser uplink is seriously affected by atmospheric environment, resulting in greater power attenuation than downlink. Uplink is used to transmit low speed instructions and control signals. In order to improve the sensitivity of satellite to ground uplink, and reduce the influence of large frequency offset on receiver, coherent heterodyne detection and spread spectrum technique are applied to uplink. To cut down the consumption of resources on the satellite, the inverse sparse Fourier transform (ISFT) is used to reduce the computational complexity of the frequency offset estimation algorithm. The frequency offset estimation algorithm based on ISFT is theoretically analyzed and validated by simulation. The simulation results reveal that compared with the direct detection of 16PPM, the sensitivity of spread spectrum coherent heterodyne detection is improved by 16dB when the error rate is 10−8. In the high signal-to-noise ratio environment at satellite to ground uplink, ISFT can estimate the frequency offset as accurate as IFFT while saving computational complexity.
{"title":"Frequency offset estimation algorithm of spread spectrum coherent heterodyne based on ISFT","authors":"Cancan Sun, Ronghua Zhou, Hangcheng Han, Xiangyuan Bu","doi":"10.1109/ICCSNT.2017.8343713","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343713","url":null,"abstract":"Satellite to ground laser uplink is seriously affected by atmospheric environment, resulting in greater power attenuation than downlink. Uplink is used to transmit low speed instructions and control signals. In order to improve the sensitivity of satellite to ground uplink, and reduce the influence of large frequency offset on receiver, coherent heterodyne detection and spread spectrum technique are applied to uplink. To cut down the consumption of resources on the satellite, the inverse sparse Fourier transform (ISFT) is used to reduce the computational complexity of the frequency offset estimation algorithm. The frequency offset estimation algorithm based on ISFT is theoretically analyzed and validated by simulation. The simulation results reveal that compared with the direct detection of 16PPM, the sensitivity of spread spectrum coherent heterodyne detection is improved by 16dB when the error rate is 10−8. In the high signal-to-noise ratio environment at satellite to ground uplink, ISFT can estimate the frequency offset as accurate as IFFT while saving computational complexity.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131313346","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：