Spectrum Sensing is a cornerstone in cognitive radio which can detect the spectrum holes in order to raise spectrum utilization ratio. Traditional spectrum sensing detectors depend on some prior information or are restricted by low signal-to-noise ratio and computation complexity in practical application. A GoDec based spectrum sensing detector is proposed by combining covariance based method with low rank and sparse model theory. The proposed detector divides the received signal into two segments of equal length, and then decomposes the covariance matrix respectively by GoDec decomposition. The primary user exists if the difference between the low rank matrices is lower than a predefined threshold. Simulation results show that the proposed detector has high detection probability to detect primary signals with SNR as low as -14dB.
{"title":"Blind Spectrum Sensing with low rank and sparse model","authors":"Xushan Chen, Xiongwei Zhang, Jibin Yang, Meng Sun, Xinwei Zhang","doi":"10.1109/ICEDIF.2015.7280183","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280183","url":null,"abstract":"Spectrum Sensing is a cornerstone in cognitive radio which can detect the spectrum holes in order to raise spectrum utilization ratio. Traditional spectrum sensing detectors depend on some prior information or are restricted by low signal-to-noise ratio and computation complexity in practical application. A GoDec based spectrum sensing detector is proposed by combining covariance based method with low rank and sparse model theory. The proposed detector divides the received signal into two segments of equal length, and then decomposes the covariance matrix respectively by GoDec decomposition. The primary user exists if the difference between the low rank matrices is lower than a predefined threshold. Simulation results show that the proposed detector has high detection probability to detect primary signals with SNR as low as -14dB.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124652706","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280178
Hailun Wang, L. Meilei, Lu Zhang
The parameters plays an important role to the performance of support vector regression(SVR). In order to solve the problem of the Parameter optimization for SVR, first, we transform the problem of Parameter optimization into a problem of nonlinear system state estimation, then, we propose a novel algorithm based on Dual Recursive Variational Bayesian Adaptive Square-Cubature Kalman Filter (DRVB-ASCKF), and introduce DRVB-ASCKF to solve it. Considering that the prior statistics noise of a Kalman filter does not agree with its real behavior led to the decrease of the kalman filtering precision, this algorithm assumes that measurement noise variance and process noise variance are unknown in advance, but the function relations between the two kinds of variance are known. This algorithm consists of two iterative processes, during the inner loop using the process noise covariance estimate evaluate measurement noise covariance, and the outer loop using the measurement noise covariance feedback estimate evaluate process noise covariance. Using the DRVB-ASCKF algorithm, we still can get a higher accuracy parameter of SVR when process noise and measurement noise are unknown.
{"title":"Parameter optimization of SVR based on DRVB-ASCKF","authors":"Hailun Wang, L. Meilei, Lu Zhang","doi":"10.1109/ICEDIF.2015.7280178","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280178","url":null,"abstract":"The parameters plays an important role to the performance of support vector regression(SVR). In order to solve the problem of the Parameter optimization for SVR, first, we transform the problem of Parameter optimization into a problem of nonlinear system state estimation, then, we propose a novel algorithm based on Dual Recursive Variational Bayesian Adaptive Square-Cubature Kalman Filter (DRVB-ASCKF), and introduce DRVB-ASCKF to solve it. Considering that the prior statistics noise of a Kalman filter does not agree with its real behavior led to the decrease of the kalman filtering precision, this algorithm assumes that measurement noise variance and process noise variance are unknown in advance, but the function relations between the two kinds of variance are known. This algorithm consists of two iterative processes, during the inner loop using the process noise covariance estimate evaluate measurement noise covariance, and the outer loop using the measurement noise covariance feedback estimate evaluate process noise covariance. Using the DRVB-ASCKF algorithm, we still can get a higher accuracy parameter of SVR when process noise and measurement noise are unknown.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127397328","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280193
Zhiwei Zhang, Tuo Fu, M. Tang
To improve the performance of phased array radar for the weak object detection, accumulation process is required to be performed over time to gather sufficient energy. For this purpose, the coherent integration algorithm is studied in this paper. First, a quasi-random pulse train echo model is presented, which divides the pulse train into a few sub-pulse-trains (time is uniform within the sub-pulse-train, while nonuniform among sub-pulse-trains). Then, on account of the specific features of this model, two integration algorithms based on fast Fourier transform (FFT) are proposed. The first one is coherent integration algorithm and the second one is associated coherent-noncoherent integration algorithm. Both methods are analyzed in detail. Finally, we apply these two algorithms to the real data of a phased array radar and the result verifies their effectiveness in practical application.
{"title":"Coherent integration of quasi-random pulse train based on phased array radar","authors":"Zhiwei Zhang, Tuo Fu, M. Tang","doi":"10.1109/ICEDIF.2015.7280193","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280193","url":null,"abstract":"To improve the performance of phased array radar for the weak object detection, accumulation process is required to be performed over time to gather sufficient energy. For this purpose, the coherent integration algorithm is studied in this paper. First, a quasi-random pulse train echo model is presented, which divides the pulse train into a few sub-pulse-trains (time is uniform within the sub-pulse-train, while nonuniform among sub-pulse-trains). Then, on account of the specific features of this model, two integration algorithms based on fast Fourier transform (FFT) are proposed. The first one is coherent integration algorithm and the second one is associated coherent-noncoherent integration algorithm. Both methods are analyzed in detail. Finally, we apply these two algorithms to the real data of a phased array radar and the result verifies their effectiveness in practical application.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122015635","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280209
Yi Liu, Bin Wu, Bo Wang
Researches on routing handover are getting more and more in recent years, which leads to several handover principles. A series of developments have been made in routing research field under a single principle. This article puts forward a new strategy ILDRHS (Improved LDRHS) based on LDRHS (Least Delay Routing Handover Strategy). The new one concentrates on the combination of connecting time, delay and load, which can better satisfy the whole satellites constellation.
{"title":"An improved satellites routing handover strategy","authors":"Yi Liu, Bin Wu, Bo Wang","doi":"10.1109/ICEDIF.2015.7280209","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280209","url":null,"abstract":"Researches on routing handover are getting more and more in recent years, which leads to several handover principles. A series of developments have been made in routing research field under a single principle. This article puts forward a new strategy ILDRHS (Improved LDRHS) based on LDRHS (Least Delay Routing Handover Strategy). The new one concentrates on the combination of connecting time, delay and load, which can better satisfy the whole satellites constellation.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128162746","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280194
Hong Wu, Shuang Mu, Baihao Jie
Coming of the Popular Science indicates the rapid development of information communication. It has brought great changes to our lives, but the subsequent problems of information security are bothering us. Looking for an efficient and safe way to protect the information security has become an important problem that needs to be solved urgently. In recent years, data encryption system based on chaotic sequence has been widely used and displayed advantages. This paper introduces an improved algorithm of Logistic chaotic encryption with unique input mode and a pseudo decryption algorithm. Information encryption and decryption based on FPGA are designed and implemented. The results show that this method is safe and reliable. It can meet the requirements of confidential communication.
{"title":"Design and implement of a Logistic chaotic encryption and pseudo decryption algorithm based on FPGA","authors":"Hong Wu, Shuang Mu, Baihao Jie","doi":"10.1109/ICEDIF.2015.7280194","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280194","url":null,"abstract":"Coming of the Popular Science indicates the rapid development of information communication. It has brought great changes to our lives, but the subsequent problems of information security are bothering us. Looking for an efficient and safe way to protect the information security has become an important problem that needs to be solved urgently. In recent years, data encryption system based on chaotic sequence has been widely used and displayed advantages. This paper introduces an improved algorithm of Logistic chaotic encryption with unique input mode and a pseudo decryption algorithm. Information encryption and decryption based on FPGA are designed and implemented. The results show that this method is safe and reliable. It can meet the requirements of confidential communication.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125689093","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280158
Lei Wang, Xianding He
This paper proposes a matching algorithm based on Delaunay Triangulation for accurate matching between affined images. This method is suitable for images rotated, scaled, translated and affined. During the matching process, triangle nets based on Delaunay theory are constructed from feature points extracted from the images. We try to find geometric invariants from the triangle nets when the images are affine transformed. The geometric relations of triangles in the nets are utilized for the matching task. The experimental results show that an ideal matching accuracy and correction rate can be achieved using this algorithm.
{"title":"Affine image matching using Delaunay Triangles","authors":"Lei Wang, Xianding He","doi":"10.1109/ICEDIF.2015.7280158","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280158","url":null,"abstract":"This paper proposes a matching algorithm based on Delaunay Triangulation for accurate matching between affined images. This method is suitable for images rotated, scaled, translated and affined. During the matching process, triangle nets based on Delaunay theory are constructed from feature points extracted from the images. We try to find geometric invariants from the triangle nets when the images are affine transformed. The geometric relations of triangles in the nets are utilized for the matching task. The experimental results show that an ideal matching accuracy and correction rate can be achieved using this algorithm.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130522055","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280204
Li Jiang, Lin Li, Guoqing Zhao
With the increase of pulse density, signal sorting becomes extremely difficult for modern electronic reconnaissance, especially for pulse-compression radar signals. Blind source separation (BSS) is a new developed technology for separating signals from mixed observed data. In this paper, we propose various instantaneous mixing models of pulse-compression radar signals, including linear frequency modulation, polyphase code, phase-shift keying and frequency-hopping signals. The combinations of fast independent component analysis (FastICA) and joint diagonalization BSS algorithms are presented for radar signals. The performance index (PI) and signal-to-interference ratio (SIR) are adopted to analyze the separation performance at different signal-to-noise ratios. The experiment results demonstrate the validity and correctness of the proposed method.
{"title":"Pulse-compression radar signal sorting using the blind source separation algrithms","authors":"Li Jiang, Lin Li, Guoqing Zhao","doi":"10.1109/ICEDIF.2015.7280204","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280204","url":null,"abstract":"With the increase of pulse density, signal sorting becomes extremely difficult for modern electronic reconnaissance, especially for pulse-compression radar signals. Blind source separation (BSS) is a new developed technology for separating signals from mixed observed data. In this paper, we propose various instantaneous mixing models of pulse-compression radar signals, including linear frequency modulation, polyphase code, phase-shift keying and frequency-hopping signals. The combinations of fast independent component analysis (FastICA) and joint diagonalization BSS algorithms are presented for radar signals. The performance index (PI) and signal-to-interference ratio (SIR) are adopted to analyze the separation performance at different signal-to-noise ratios. The experiment results demonstrate the validity and correctness of the proposed method.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134156107","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280181
Yao Wang, Linbo Zhu, Jiwen Wang, Jianfeng Qiu
In this paper, we propose a novel swarm algorithm, called social spider algorithm (SSA), to solve the Flexible Job-Shop Scheduling Problem (FJSP). The SSA algorithm stresses the difference between the two different search agents (spiders): males and females [19]. Some strategies are utilized to generate the initial individual in order to ensure certain quality and diversity, such as global search (GS) and local search (LS) and so on. Moreover, instead of the original SSA algorithm, the improved SSA is combined with the selection, crossover and mutation operation to enhance the performance. The computational result shows that the proposed algorithm produces better results than other authors' algorithms [23].
{"title":"An improved social spider algorithm for the Flexible Job-Shop Scheduling Problem","authors":"Yao Wang, Linbo Zhu, Jiwen Wang, Jianfeng Qiu","doi":"10.1109/ICEDIF.2015.7280181","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280181","url":null,"abstract":"In this paper, we propose a novel swarm algorithm, called social spider algorithm (SSA), to solve the Flexible Job-Shop Scheduling Problem (FJSP). The SSA algorithm stresses the difference between the two different search agents (spiders): males and females [19]. Some strategies are utilized to generate the initial individual in order to ensure certain quality and diversity, such as global search (GS) and local search (LS) and so on. Moreover, instead of the original SSA algorithm, the improved SSA is combined with the selection, crossover and mutation operation to enhance the performance. The computational result shows that the proposed algorithm produces better results than other authors' algorithms [23].","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131896526","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280163
Qi Liu, Zi Huang, Fuqiao Hu
Convolution-based detection models (CDM) have achieved tremendous success in computer vision in last few years, such as deformable part-based models (DPM) and convolutional neural networks (CNN). The simplicity of these models allows for very large scale training to achieve higher robustness and recognition performance. However, the main bottleneck of those powerful state-of-the-art models is the unacceptable computational cost of the convolution in model training and evaluation, which has become a major limitation in many practical applications. In this paper, we accelerate the convolution-based detection models with the mathematic and parallel techniques. On one hand, the convolution operation in the spatial space is converted to the dot product operation in the frequency domain for less computational cost. On the other hand, the data and tasks parallelized on graphical process units (GPU) reduce the computational time further. Experimental results on the public dataset Pascal VOC demonstrate that we can use commodity GPU to speed up the whole convolution process by 2.13x to 4.31x, compared to the multithreaded implementation on CPU.
{"title":"Accelerating convolution-based detection model on GPU","authors":"Qi Liu, Zi Huang, Fuqiao Hu","doi":"10.1109/ICEDIF.2015.7280163","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280163","url":null,"abstract":"Convolution-based detection models (CDM) have achieved tremendous success in computer vision in last few years, such as deformable part-based models (DPM) and convolutional neural networks (CNN). The simplicity of these models allows for very large scale training to achieve higher robustness and recognition performance. However, the main bottleneck of those powerful state-of-the-art models is the unacceptable computational cost of the convolution in model training and evaluation, which has become a major limitation in many practical applications. In this paper, we accelerate the convolution-based detection models with the mathematic and parallel techniques. On one hand, the convolution operation in the spatial space is converted to the dot product operation in the frequency domain for less computational cost. On the other hand, the data and tasks parallelized on graphical process units (GPU) reduce the computational time further. Experimental results on the public dataset Pascal VOC demonstrate that we can use commodity GPU to speed up the whole convolution process by 2.13x to 4.31x, compared to the multithreaded implementation on CPU.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134283242","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 : 2015-10-01DOI: 10.1109/ICEDIF.2015.7280179
Jin Xue-bo, Shi Yan, Nie Chunxue
Due to the uncertainty of the Radio Frequency Identification (RFID) measurements and limit of the placement of the readers, it's necessary to use the estimation method to obtain more accurate trajectory in RFID indoor tracking system. The traditional recursive estimation from K to K+1 sampling point may fail, because the measurement of RFID system is irregular sampling due to the data-driven measurement mechanism. This paper develops the tracking method for indoor RFID system, including estimation dynamic model based on the estimated states and nonlinear fusion estimation algorithm for variable-irregular sampling measurements. Two estimation methods are given based on the Extended Kalman filter (EKF) and Unscented Kalman filter (UKF), respectively. The tracking performances are compared and the simulation results show that the performance of UKF can get better performance for indoor RFID tracking, especially in the low detection rate area.
{"title":"Tracking for indoor RFID system with UKF and EKF","authors":"Jin Xue-bo, Shi Yan, Nie Chunxue","doi":"10.1109/ICEDIF.2015.7280179","DOIUrl":"https://doi.org/10.1109/ICEDIF.2015.7280179","url":null,"abstract":"Due to the uncertainty of the Radio Frequency Identification (RFID) measurements and limit of the placement of the readers, it's necessary to use the estimation method to obtain more accurate trajectory in RFID indoor tracking system. The traditional recursive estimation from K to K+1 sampling point may fail, because the measurement of RFID system is irregular sampling due to the data-driven measurement mechanism. This paper develops the tracking method for indoor RFID system, including estimation dynamic model based on the estimated states and nonlinear fusion estimation algorithm for variable-irregular sampling measurements. Two estimation methods are given based on the Extended Kalman filter (EKF) and Unscented Kalman filter (UKF), respectively. The tracking performances are compared and the simulation results show that the performance of UKF can get better performance for indoor RFID tracking, especially in the low detection rate area.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133314258","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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