To bridge the performance gap between original probability data association (PDA) algorithm and the optimum maximum a posterior (MAP) algorithm for multi-input multi-output (MIMO) detection, a grouped PDA (GP-...To bridge the performance gap between original probability data association (PDA) algorithm and the optimum maximum a posterior (MAP) algorithm for multi-input multi-output (MIMO) detection, a grouped PDA (GP-PDA) detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability (APP) is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.展开更多
Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabili...Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabilistic data association(PDA),a novel probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update is proposed.Firstly,combining with the advantages of data assimilation handling observation uncertainty in EnKF,an observation iterated update strategy is used to realize optimization of EnKF in structure.And the object is to further improve state estimation precision of nonlinear system.Secondly,the above algorithm is introduced to the framework of PDA,and the object is to increase reliability and stability of candidate echo acknowledgement.In addition,in order to decrease computation complexity in the combination of improved EnKF and PDA,the maximum observation iterated update mechanism is applied to the iteration of PDA.Finally,simulation results verify the feasibility and effectiveness of the proposed algorithm by a typical target tracking scene in clutters.展开更多
本论文研究了基于同步DS-CDMA协作通信系统的迭代接收机性能,该系统在协作伙伴节点端和基站端均使用由随机数据联合检测器与LDPC译码器级联(PDA+LDPC,probabilistic data association+low density parity check codes)所组成的迭代接收...本论文研究了基于同步DS-CDMA协作通信系统的迭代接收机性能,该系统在协作伙伴节点端和基站端均使用由随机数据联合检测器与LDPC译码器级联(PDA+LDPC,probabilistic data association+low density parity check codes)所组成的迭代接收机,利用从该迭代接收机所提供的信息,提出了一种集中式协作伙伴节点选择策略。根据该策略,由于距离基站较近的节点与基站间通信能力相对较强,每个信源节点将优先选择距离基站近的节点作为其协作伙伴节点,仿真结果表明,本文所提出的集中式协作伙伴节点选择策略可取得较好的系统性能。展开更多
对含有系统误差的测量进行配准是准确进行数据关联的前提.实际中,许多不确定性因素导致系统误差,使其演化模型难以建立,从而导致传统配准方法不再适用.为此,提出一种基于优化SA-PSO(simulated annealing particle swarm optimization)...对含有系统误差的测量进行配准是准确进行数据关联的前提.实际中,许多不确定性因素导致系统误差,使其演化模型难以建立,从而导致传统配准方法不再适用.为此,提出一种基于优化SA-PSO(simulated annealing particle swarm optimization)的配准算法.由于传感器监视空域经常受到杂波的影响,在利用SA-PSO优化算法对系统误差进行配准时,不仅要考虑外界因素所引发系统误差的不确定性问题,还要考虑目标多个量测的归属问题.基于此,提出一种联合改进退火粒子群优化和概率数据关联的算法SA-PSO-PDA(simulated annealing and particle swarm optimization and probability data association),它综合考虑系统误差的随机性、寻优的最佳化和目标量测的多样性.仿真结果表明了所提算法具有可行性,且能较好地寻优系统误差参数.展开更多
针对同步DS-CDMA协作通信系统,本文考虑在转发节点端和基站端使用随机数据联合检测算法(probabilistic data association algorithm,PDA)与LDPC码译码器级联的迭代接收机PDA+LDPC,基于该迭代接收机结构,给出了一种分布式协作通信策略,...针对同步DS-CDMA协作通信系统,本文考虑在转发节点端和基站端使用随机数据联合检测算法(probabilistic data association algorithm,PDA)与LDPC码译码器级联的迭代接收机PDA+LDPC,基于该迭代接收机结构,给出了一种分布式协作通信策略,研究表明,该策略较集中式协作伙伴选择策略和传统的DAF协作通信策略可取得更好的系统性能。展开更多
基金Sponsored by the National Natural Science Foundation of China(60572120)
文摘To bridge the performance gap between original probability data association (PDA) algorithm and the optimum maximum a posterior (MAP) algorithm for multi-input multi-output (MIMO) detection, a grouped PDA (GP-PDA) detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability (APP) is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.
基金Supported by the National Nature Science Foundation of China(No.61300214)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+5 种基金the National Natural Science Foundation of Henan Province(No.132300410148)the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Postdoctoral Science Foundation of China(No.2014M551999)the Funding Scheme of Young Key Teacher of Henan Province Universities(No.2013GGJS-026)the Postdoctoral Fund of Henan Province(No.2013029)the Outstanding Young Cultivation Foundation of Henan University(No.0000A40366)
文摘Aiming at improving the observation uncertainty caused by limited accuracy of sensors,and the uncertainty of observation source in clutters,through the dynamic combination of ensemble Kalman filter(EnKF) and probabilistic data association(PDA),a novel probabilistic data association algorithm based on ensemble Kalman filter with observation iterated update is proposed.Firstly,combining with the advantages of data assimilation handling observation uncertainty in EnKF,an observation iterated update strategy is used to realize optimization of EnKF in structure.And the object is to further improve state estimation precision of nonlinear system.Secondly,the above algorithm is introduced to the framework of PDA,and the object is to increase reliability and stability of candidate echo acknowledgement.In addition,in order to decrease computation complexity in the combination of improved EnKF and PDA,the maximum observation iterated update mechanism is applied to the iteration of PDA.Finally,simulation results verify the feasibility and effectiveness of the proposed algorithm by a typical target tracking scene in clutters.
文摘本论文研究了基于同步DS-CDMA协作通信系统的迭代接收机性能,该系统在协作伙伴节点端和基站端均使用由随机数据联合检测器与LDPC译码器级联(PDA+LDPC,probabilistic data association+low density parity check codes)所组成的迭代接收机,利用从该迭代接收机所提供的信息,提出了一种集中式协作伙伴节点选择策略。根据该策略,由于距离基站较近的节点与基站间通信能力相对较强,每个信源节点将优先选择距离基站近的节点作为其协作伙伴节点,仿真结果表明,本文所提出的集中式协作伙伴节点选择策略可取得较好的系统性能。
文摘对含有系统误差的测量进行配准是准确进行数据关联的前提.实际中,许多不确定性因素导致系统误差,使其演化模型难以建立,从而导致传统配准方法不再适用.为此,提出一种基于优化SA-PSO(simulated annealing particle swarm optimization)的配准算法.由于传感器监视空域经常受到杂波的影响,在利用SA-PSO优化算法对系统误差进行配准时,不仅要考虑外界因素所引发系统误差的不确定性问题,还要考虑目标多个量测的归属问题.基于此,提出一种联合改进退火粒子群优化和概率数据关联的算法SA-PSO-PDA(simulated annealing and particle swarm optimization and probability data association),它综合考虑系统误差的随机性、寻优的最佳化和目标量测的多样性.仿真结果表明了所提算法具有可行性,且能较好地寻优系统误差参数.
文摘针对同步DS-CDMA协作通信系统,本文考虑在转发节点端和基站端使用随机数据联合检测算法(probabilistic data association algorithm,PDA)与LDPC码译码器级联的迭代接收机PDA+LDPC,基于该迭代接收机结构,给出了一种分布式协作通信策略,研究表明,该策略较集中式协作伙伴选择策略和传统的DAF协作通信策略可取得更好的系统性能。