Aiming at the requirements of accurate target positioning and autonomous capability for adapting to the environmental changes of unmanned aerial vehicle(UAV),a new method for wind estimation and airspeed calibration i...Aiming at the requirements of accurate target positioning and autonomous capability for adapting to the environmental changes of unmanned aerial vehicle(UAV),a new method for wind estimation and airspeed calibration is proposed.The method is implemented to obtain both wind speed and wind direction based on the information from a GPS receiver,an air data computer and a magnetic compass,combining with the velocity vector triangle relationships among ground speed,wind speed and air speed.Considering the installation error of Pitot tube,cubature Kalman filter(CKF)is applied to determine proportionality calibration coefficient of true airspeed,thus improving the accuracy of wind field information further.The entire autonomous flight simulation is performed in a constant 2-D wind using a digital simulation platform for UAV.Simulation results show that the wind speed and wind direction can be accurately estimated both in straight line and in turning segment during the path tracking by using the proposed method.The measurement accuracies of the wind speed and wind direction are 0.62 m/s and2.57°,respectively.展开更多
In this paper, we consider median unbiased estimation of bivariate predictive regression models with non-normal, heavy-tailed or heteroscedastic errors. We construct confidence intervals and median unbiased estimator ...In this paper, we consider median unbiased estimation of bivariate predictive regression models with non-normal, heavy-tailed or heteroscedastic errors. We construct confidence intervals and median unbiased estimator for the parameter of interest. We show that the proposed estimator has better predictive potential than the usual least squares estimator via simulation. An empirical application to finance is given. And a possible extension of the estimation procedure to cointegration models is also described.展开更多
研究了一种新型的空速测量方法。通过引入大气声学中的有效声速概念,建立了稳定气流作用下声矢量传感器阵列的近场输出模型,模型的阵列流形矢量中包含了待估计的空速信息。在此基础上提出了一种基于多重信号分类(multiple signal classi...研究了一种新型的空速测量方法。通过引入大气声学中的有效声速概念,建立了稳定气流作用下声矢量传感器阵列的近场输出模型,模型的阵列流形矢量中包含了待估计的空速信息。在此基础上提出了一种基于多重信号分类(multiple signal classification,MUSIC)的空速估计(airspeed estimation,ASE)算法,该算法可用于对空速的高精度估计。为了降低计算复杂度,进一步提出了一种快速的空速估计(fast airspeed estimation,FASE)算法,该算法虽然在ASE的精度上不如MUSIC-ASE算法,但无需谱搜索,具有更强的实时性。最后,对算法的估计性能进行分析,推导了ASE的克拉美-罗界表达式。仿真实验验证了算法的有效性。展开更多
信道估计对于VRVP-MQAM系统的整体性能至关重要,论述了VRVP-MQAM方法在实际应用中遇到的问题,针对假定CSI已知的传统研究方法,该文通过采用MMSE算法进行信道估计,研究了MMSE估计误差对VRVP-MQAM方法的ASE性能影响,并在Rayleigh衰落信道...信道估计对于VRVP-MQAM系统的整体性能至关重要,论述了VRVP-MQAM方法在实际应用中遇到的问题,针对假定CSI已知的传统研究方法,该文通过采用MMSE算法进行信道估计,研究了MMSE估计误差对VRVP-MQAM方法的ASE性能影响,并在Rayleigh衰落信道下进行了仿真,仿真结果表明：与信道状态已知（ρ=1）相比,MMSE估计误差（ρ=0.9时）会产生1~3 d B左右的ASE性能差距;当平均SNR为20 d B时,MMSE算法下信道状态的平均频谱效率为0.3 bps/Hz,比理想信道状态的平均频谱效率低。因此,VRVP-MQAM方法的应用将会越来越广泛。展开更多
该文研究基于声传感器阵列的单快拍气流速度估计问题。首先,根据声波在亚音速和超音速气流中的传播特性,针对特定的测量装置,建立了声传感器线性阵列的输出模型。在此基础上,提出一种稀疏协方差矩阵迭代的单快拍(Sparse Covariance Matr...该文研究基于声传感器阵列的单快拍气流速度估计问题。首先,根据声波在亚音速和超音速气流中的传播特性,针对特定的测量装置,建立了声传感器线性阵列的输出模型。在此基础上,提出一种稀疏协方差矩阵迭代的单快拍(Sparse Covariance Matrix Iteration with a Single Snapshot,SCMISS)气流速度估计算法,与其他稀疏估计方法相比,该文提出的SCMISS算法无需正则化参数选择,计算量更低,具有更强的实时性,且只需单快拍采样数据就可对亚音速和超音速气流速度进行统一估计。最后,为了评价所提算法的估计性能,推导了气流速度估计的克拉美-罗界(Cramér-Rao Bound,CRB)表达式。仿真实验验证了该算法的有效性。展开更多
基金supported by the Pre-research Foundation of Chinese People's Liberation Army General Equipment Department(No.51325010601)
文摘Aiming at the requirements of accurate target positioning and autonomous capability for adapting to the environmental changes of unmanned aerial vehicle(UAV),a new method for wind estimation and airspeed calibration is proposed.The method is implemented to obtain both wind speed and wind direction based on the information from a GPS receiver,an air data computer and a magnetic compass,combining with the velocity vector triangle relationships among ground speed,wind speed and air speed.Considering the installation error of Pitot tube,cubature Kalman filter(CKF)is applied to determine proportionality calibration coefficient of true airspeed,thus improving the accuracy of wind field information further.The entire autonomous flight simulation is performed in a constant 2-D wind using a digital simulation platform for UAV.Simulation results show that the wind speed and wind direction can be accurately estimated both in straight line and in turning segment during the path tracking by using the proposed method.The measurement accuracies of the wind speed and wind direction are 0.62 m/s and2.57°,respectively.
基金The NNSF(10571073)of china,and 985 project of Jilin University.
文摘In this paper, we consider median unbiased estimation of bivariate predictive regression models with non-normal, heavy-tailed or heteroscedastic errors. We construct confidence intervals and median unbiased estimator for the parameter of interest. We show that the proposed estimator has better predictive potential than the usual least squares estimator via simulation. An empirical application to finance is given. And a possible extension of the estimation procedure to cointegration models is also described.
文摘信道估计对于VRVP-MQAM系统的整体性能至关重要,论述了VRVP-MQAM方法在实际应用中遇到的问题,针对假定CSI已知的传统研究方法,该文通过采用MMSE算法进行信道估计,研究了MMSE估计误差对VRVP-MQAM方法的ASE性能影响,并在Rayleigh衰落信道下进行了仿真,仿真结果表明：与信道状态已知（ρ=1）相比,MMSE估计误差（ρ=0.9时）会产生1~3 d B左右的ASE性能差距;当平均SNR为20 d B时,MMSE算法下信道状态的平均频谱效率为0.3 bps/Hz,比理想信道状态的平均频谱效率低。因此,VRVP-MQAM方法的应用将会越来越广泛。
文摘该文研究基于声传感器阵列的单快拍气流速度估计问题。首先,根据声波在亚音速和超音速气流中的传播特性,针对特定的测量装置,建立了声传感器线性阵列的输出模型。在此基础上,提出一种稀疏协方差矩阵迭代的单快拍(Sparse Covariance Matrix Iteration with a Single Snapshot,SCMISS)气流速度估计算法,与其他稀疏估计方法相比,该文提出的SCMISS算法无需正则化参数选择,计算量更低,具有更强的实时性,且只需单快拍采样数据就可对亚音速和超音速气流速度进行统一估计。最后,为了评价所提算法的估计性能,推导了气流速度估计的克拉美-罗界(Cramér-Rao Bound,CRB)表达式。仿真实验验证了该算法的有效性。
