给出一种有效的噪声压缩算法,提供了高分辨率的掩蔽感知模型,并对K a lm an滤波模型进行了改进。算法通过计算噪声掩蔽参数,可以适时更新数据参数,压缩信号噪声。实验表明,本文算法没有延迟,语音质量感知评估(Perceptua l eva luation o...给出一种有效的噪声压缩算法,提供了高分辨率的掩蔽感知模型,并对K a lm an滤波模型进行了改进。算法通过计算噪声掩蔽参数,可以适时更新数据参数,压缩信号噪声。实验表明,本文算法没有延迟,语音质量感知评估(Perceptua l eva luation of speech qua lity scores,PESQ)值高,对窄带及宽带信号噪声的压缩均有满意效果。展开更多
By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets ...By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets of multi-measurements of the same ESG in different noise environments are ＂mapped＂ into a sensor network,and DKF with embedded consensus filters is then used to preprocess the data sets. After transforming the preprocessed results into the trained input and the desired output of neural network,BPNN with the learning rate and the momentum term is further utilized to identify the ESG bias. As demonstrated in the experiment,the proposed approach is effective for the model identification of the ESG bias.展开更多
In this study, we propose the use of the Degree of Alignment(DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical f...In this study, we propose the use of the Degree of Alignment(DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing(FPS), Returns to Scale(RTS), Inverted Sequence Recursive Estimation(ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.展开更多
CIFER software is used to identify steering and roll dynamics of a container ship. In this software, advanced features such as the Chirp-Z transform(CZT) and composite window optimization are applied to the time histo...CIFER software is used to identify steering and roll dynamics of a container ship. In this software, advanced features such as the Chirp-Z transform(CZT) and composite window optimization are applied to the time history of steering and roll dynamics to extract high quality frequency responses. From the extracted frequency responses, two linear transfer functions of Nomoto model are fitted for yaw and roll dynamics of the vessel. Based on the identified Nomoto model, a PID heading controller and a Kalman filter observer are constructed. The simulation results of heading controller for line of sight(LOS) waypoint guidance show excellent tracking of pilot inputs in the presence of wave induced motions and forces.展开更多
The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffi...The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffic guidance for travelers and relieves traffic jams. In this paper, a real-time road traffic state prediction based on autoregressive integrated moving average （ARIMA） and the Kalman filter is proposed. First, an ARIMA model of road traffic data in a time series is built on the basis of historical road traffic data. Second, this ARIMA model is combined with the Kalman filter to construct a road traffic state prediction algorithm, which can acquire the state, measurement, and updating equations of the Kalman filter. Third, the optimal parameters of the algorithm are discussed on the basis of historical road traffic data. Finally, four road segments in Beijing are adopted for case studies. Experimental results show that the real-time road traffic state prediction based on ARIMA and the Kalman filter is feasible and can achieve high accuracy.展开更多
文摘给出一种有效的噪声压缩算法,提供了高分辨率的掩蔽感知模型,并对K a lm an滤波模型进行了改进。算法通过计算噪声掩蔽参数,可以适时更新数据参数,压缩信号噪声。实验表明,本文算法没有延迟,语音质量感知评估(Perceptua l eva luation of speech qua lity scores,PESQ)值高,对窄带及宽带信号噪声的压缩均有满意效果。
文摘By combining the distributed Kalman filter （DKF） with the back propagation neural network （BPNN）,a novel method is proposed to identify the bias of electrostatic suspended gyroscope （ESG）. Firstly,the data sets of multi-measurements of the same ESG in different noise environments are ＂mapped＂ into a sensor network,and DKF with embedded consensus filters is then used to preprocess the data sets. After transforming the preprocessed results into the trained input and the desired output of neural network,BPNN with the learning rate and the momentum term is further utilized to identify the ESG bias. As demonstrated in the experiment,the proposed approach is effective for the model identification of the ESG bias.
基金Supported by the National Natural Science Foundation of China （61633008）, the National Natural Science Foundation of China （61203225）, the Natural Science Foundation of Heilongjiang Province of China（QC2014C069）, the Special fund for the Central Universities （HEUCF160401）, and Provincial Postdoctoral Scientific Research Foundation （LBH-Q 15032）.
文摘In this study, we propose the use of the Degree of Alignment(DOA) in engineering applications for evaluating the precision of and identifying the transfer alignment on a moving base. First, we derive the statistical formula on the basis of estimations. Next, we design a scheme for evaluating the transfer alignment on a moving base, for which the attitude error cannot be directly measured. Then, we build a mathematic estimation model and discuss Fixed Point Smoothing(FPS), Returns to Scale(RTS), Inverted Sequence Recursive Estimation(ISRE), and Kalman filter estimation methods, which can be used when evaluating alignment accuracy. Our theoretical calculations and simulated analyses show that the DOA reflects not only the alignment time and accuracy but also differences in the maneuver schemes, and is suitable for use as an integrated evaluation index. Furthermore, all four of these algorithms can be used to identify the transfer alignment and evaluate its accuracy. We recommend RTS in particular for engineering applications. Generalized DOAs should be calculated according to the tactical requirements.
文摘CIFER software is used to identify steering and roll dynamics of a container ship. In this software, advanced features such as the Chirp-Z transform(CZT) and composite window optimization are applied to the time history of steering and roll dynamics to extract high quality frequency responses. From the extracted frequency responses, two linear transfer functions of Nomoto model are fitted for yaw and roll dynamics of the vessel. Based on the identified Nomoto model, a PID heading controller and a Kalman filter observer are constructed. The simulation results of heading controller for line of sight(LOS) waypoint guidance show excellent tracking of pilot inputs in the presence of wave induced motions and forces.
基金Project supported by the National Science &Technology Pillar Program(No.2014BAG01B02)
文摘The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffic guidance for travelers and relieves traffic jams. In this paper, a real-time road traffic state prediction based on autoregressive integrated moving average （ARIMA） and the Kalman filter is proposed. First, an ARIMA model of road traffic data in a time series is built on the basis of historical road traffic data. Second, this ARIMA model is combined with the Kalman filter to construct a road traffic state prediction algorithm, which can acquire the state, measurement, and updating equations of the Kalman filter. Third, the optimal parameters of the algorithm are discussed on the basis of historical road traffic data. Finally, four road segments in Beijing are adopted for case studies. Experimental results show that the real-time road traffic state prediction based on ARIMA and the Kalman filter is feasible and can achieve high accuracy.
