At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attri...At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attribute.The purpose is to characterize the temporal and spatial variation of the seismic data SNR.First,the local slope parameters of the seismic events are calculated using a plane wave decomposition filter.Then,the singular value decomposition method is used to calculate the local seismic data SNR,thereby obtaining it in time and space.The proposed method overcomes the insufficiency of a conventional global SNR to characterize any local seismic data features and uses the SNR as an attribute of seismic data to more accurately describe the signal-noise energy distribution characteristics of seismic data in time and space.The results of a theoretical model test and real data processing show that the SNR attribute can be used not only for seismic data quality evaluation but also for analysis and evaluation of denoising methods.展开更多
Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multi...Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo(particle) technique. Target detection was accomplished through the estimation of target's existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.展开更多
A novel memory efficient path metric update is proposed for Maximum A Posteriori(MAP) decoder of turbo codes to reduce the memory requirement of state metric information calcu-lation. For MAP decoder,the same memory c...A novel memory efficient path metric update is proposed for Maximum A Posteriori(MAP) decoder of turbo codes to reduce the memory requirement of state metric information calcu-lation. For MAP decoder,the same memory can be shared by the forward and backward metrics with this metric update scheme. The forward and backward metrics update can be performed at the same time. And all of the extrinsic information can be calculated at the end of metric update. Therefore,the latency and area in the implementation will be reduced with the proposed metric update method.展开更多
Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eig...Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eigen decomposition, using the sliding window technique to obtain the code synchronization, then use segmentation subspace tracking method estimate spreading sequence and splice in a certain order to achieve pseudo-code blind estimation. The results show that the algorithm can complete the accurate estimation of PN code sequence in low SNR conditions, reduce the amount of data storage and be easy hardware implementation展开更多
This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(...This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.展开更多
基金supported by National Natural Science Foundation of China(No.41604094)Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources(Yangtze University),Ministry of Education(No.K2018-13)
文摘At present,most signal-to-noise ratio(SNR)estimation methods can only calculate the global and not the local SNR of seismic data.This paper proposes a calculation method of a structure-oriented-based seismic SNR attribute.The purpose is to characterize the temporal and spatial variation of the seismic data SNR.First,the local slope parameters of the seismic events are calculated using a plane wave decomposition filter.Then,the singular value decomposition method is used to calculate the local seismic data SNR,thereby obtaining it in time and space.The proposed method overcomes the insufficiency of a conventional global SNR to characterize any local seismic data features and uses the SNR as an attribute of seismic data to more accurately describe the signal-noise energy distribution characteristics of seismic data in time and space.The results of a theoretical model test and real data processing show that the SNR attribute can be used not only for seismic data quality evaluation but also for analysis and evaluation of denoising methods.
基金Projects(61002022,61471370)supported by the National Natural Science Foundation of China
文摘Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo(particle) technique. Target detection was accomplished through the estimation of target's existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter.
文摘A novel memory efficient path metric update is proposed for Maximum A Posteriori(MAP) decoder of turbo codes to reduce the memory requirement of state metric information calcu-lation. For MAP decoder,the same memory can be shared by the forward and backward metrics with this metric update scheme. The forward and backward metrics update can be performed at the same time. And all of the extrinsic information can be calculated at the end of metric update. Therefore,the latency and area in the implementation will be reduced with the proposed metric update method.
文摘Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eigen decomposition, using the sliding window technique to obtain the code synchronization, then use segmentation subspace tracking method estimate spreading sequence and splice in a certain order to achieve pseudo-code blind estimation. The results show that the algorithm can complete the accurate estimation of PN code sequence in low SNR conditions, reduce the amount of data storage and be easy hardware implementation
基金supported by the 863 Program of China under Grant No.2015AA01A703the Fundamental Research Funds for the Central Universities under Grant No.2014ZD03-02+1 种基金the National Natural Science Foundation of China(NSFC,No.61171104,61571055)fund of State Key Laboratory of Millimeter Wave(SKL of MMW,No.K201501)
文摘This paper explores the multi-frequency independent channel interference alignment(MFC-IA) system of 3 channels and4 users,and single data stream transmit,i.e.(3×3,1)~4 system.We derive the analytic solution for(3×3,1)~4 MFC-IA system.Based on the analytic solution,an optimization problem is proposed aim at the optimal IA solution.Then based on such a math model,we propose a simulated annealing(SA) algorithm to search optimal IA solution.The simulation results show that the simulated annealing IA algorithm has a better sum rate performance than iterative maximize signal to interference plus noise ratio(Max-SINR) algorithm.This result can be extended to single data stream multi-antenna IA system with 3 antennas and4 users.
