1临床资料男性,75岁,主因阵发性心悸、头晕1周入院。患者既往有明确高血压病史,近7年来反复出现胸闷、气短,与活动无明显关系,2015年4月19日12时患者无明显诱因出现胸闷、气短,无明显心前区疼痛,无大汗,就诊于解放军总医院门诊,急查心...1临床资料男性,75岁,主因阵发性心悸、头晕1周入院。患者既往有明确高血压病史,近7年来反复出现胸闷、气短,与活动无明显关系,2015年4月19日12时患者无明显诱因出现胸闷、气短,无明显心前区疼痛,无大汗,就诊于解放军总医院门诊,急查心肌酶未见明显异常,测血压200/110 mm Hg。展开更多
The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands...The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands. However, the spectra discontinuity of the signal gets rise to high range sidelobes when matching the reflected echo, which is much more difficult for targets detection. So it is indispensable to investigate the technique for sidelobes suppression of the range profile when RIS signal is utilized, This paper introduced a new processing technique based on time domain filtering to lower the range sidelobes. A robust and effetive algorithm is adopted to solve the coefficients of the filter, and the restriction on the desired response of the filter is derived. The simulation results show that the peak range sidelobe can be reduced to -27 dB from -9.5 dB while the frequency band span (FBS) is 200 kHz.展开更多
Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Fir...Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.展开更多
This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local...This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.展开更多
文摘The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands. However, the spectra discontinuity of the signal gets rise to high range sidelobes when matching the reflected echo, which is much more difficult for targets detection. So it is indispensable to investigate the technique for sidelobes suppression of the range profile when RIS signal is utilized, This paper introduced a new processing technique based on time domain filtering to lower the range sidelobes. A robust and effetive algorithm is adopted to solve the coefficients of the filter, and the restriction on the desired response of the filter is derived. The simulation results show that the peak range sidelobe can be reduced to -27 dB from -9.5 dB while the frequency band span (FBS) is 200 kHz.
基金Supported by the National Natural Science Foundation(NNSF)of China under Grant(No.61300214)the Science and Technology Innovation Team Support Plan of Education Department of Henan Province(No.13IRTSTHN021)+5 种基金the Science and Technology Research Key Project of Education Department of Henan Province(No.13A413066)the Basic and Frontier Technology Research Plan of Henan Province(No.132300410148)the Funding Scheme of Young Key Teacher of Henan Province Universities(No.2013GGJS-026)the Key Project of Teaching Reform Research of Henan University(No.HDXJJG2013-07)the Postdoctoral Science Fund of Henan Province(No.2013029)the Postdoctoral Science Fund of China(No.2014M551999)
文摘Aiming at the adverse effect caused by limited detecting probability of sensors on filtering preci- sion of a nonlinear system state, a novel muhi-sensor federated unscented Kalman filtering algorithm is proposed. Firstly, combined with the residual detection strategy, effective observations are cor- rectly identified. Secondly, according to the missing characteristic of observations and the structural feature of unscented Kalman filter, the iterative process of the single-sensor unscented Kalman filter in intermittent observations is given. The key idea is that the state estimation and its error covariance matrix are replaced by the state one-step prediction and its error covariance matrix, when the phe- nomenon of observations missing occurs. Finally, based on the realization mechanism of federated filter, a new fusion framework of state estimation from each local node is designed. And the filtering precision of system state is improved further by the effective management of observations missing and the rational utilization of redundancy and complementary information among multi-sensor observa- tions. The theory analysis and simulation results show the feasibility and effectiveness of the pro- posed algorithm.
基金supported by the National Natural Science Foundation of China under Grant Nos.60934009, 60901037 and 61004138
文摘This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.
