A novel and efficient method for decomposing a signal into a set of intrinsic mode functions （IMFs） and a trend is proposed. Unlike the original empirical mode decomposition （EMD）, which uses spline fits to extrac...A novel and efficient method for decomposing a signal into a set of intrinsic mode functions （IMFs） and a trend is proposed. Unlike the original empirical mode decomposition （EMD）, which uses spline fits to extract variations from the signal by separating the local mean from the fluctuations in the decomposing process, this new method being proposed takes advantage of the theory of variable finite impulse response （FIR） filtering where filter coefficients and breakpoint frequencies can be adjusted to track any peak-to-peak time scale changes. The IMFs are results of a multiple variable frequency response FIR filtering when signals pass through the filters. Numerical examples validate that in contrast with the original EMD, the proposed method can fine-tune the frequency resolution and suppress the aliasing effectively.展开更多
A light field modulated imaging spectrometer （LFMIS） can acquire the spatial-spectral datacube of targets of interest or a scene in a single shot. The spectral information of a point target is imaged on the pixels c...A light field modulated imaging spectrometer （LFMIS） can acquire the spatial-spectral datacube of targets of interest or a scene in a single shot. The spectral information of a point target is imaged on the pixels covered by a microlens. The pixels receive spectral information from different spectral filters to the diffraction and misalignments of the optical components. In this paper, we present a linear spectral multiplexing model of the acquired target spectrum. A calibration method is proposed for calibrating the center wavelengths and bandwidths of channels of an LFMIS system based on the liner-variable filter （LVF） and for determining the spectral multiplexing matrix. In order to improve the accuracy of the restored spectral data, we introduce a reconstruction algorithm based on the total least square （TLS） approach. Simulation and experimental results confirm the performance of the spectrum reconstruction algorithm and validate the feasibility of the proposed calibrating scheme.展开更多
针对薄膜体声波谐振腔(FBAR)滤波器测试夹具误差校准,提出一种改进的TRL校准方法,将三维电磁仿真和TRL计算结合,用于测试套件(夹具和TRL校准件)的前期设计与优化,确保TRL校准件达到足够精度。由于DUT(device under test,待测器件)参数未...针对薄膜体声波谐振腔(FBAR)滤波器测试夹具误差校准,提出一种改进的TRL校准方法,将三维电磁仿真和TRL计算结合,用于测试套件(夹具和TRL校准件)的前期设计与优化,确保TRL校准件达到足够精度。由于DUT(device under test,待测器件)参数未知,实测中采用四种不同结构的测试套件,校准前各组测试结果差异较大,但TRL校准后高度吻合,通带内的差异小于0.2 dB,不但精准确定DUT真实参数,而且表明本TRL校准方法对于不同结构夹具去嵌入的有效性。该仿真计算不仅可以设计高精度测试套件,避免过度依靠实测,并且可与实测相互验证,并可推广到其他微波器件的测量,节省测试成本。展开更多
In the forthcoming 5G systems, new technologies, such as amorphous networks and non-orthogonal filter bank multicarriers(FBMC), provide an effective way to accommodate high-rate transmissions. Meanwhile, the prototype...In the forthcoming 5G systems, new technologies, such as amorphous networks and non-orthogonal filter bank multicarriers(FBMC), provide an effective way to accommodate high-rate transmissions. Meanwhile, the prototype filter affects the adjacent channel interference, and therefore is important for FBMC systems. Besides, once the amorphous network is taken into account, the requirement for interference controlmust be much stricter. Accordingly, this paper focuses on the design of prototype filter with better ability of interference controlling, where we exploit the nonlinear phase FIR filter(NLPFF) instead of traditional linear phase FIR filter(LPFF) to achieve more optimization spaces under a small sacrifice of linear phase. In ourdesigns, both the amplitude and phase responsesare handled independently to approach the stopband performance enhancements, in while the nearly perfect reconstruction(NPR) conditionsare relaxed by pre-specified thresholds. Computer simulations confirm the effectiveness of the NLPFF designs, and demonstrate the advantages of the proposed NLPFF in FBMC applications.展开更多
In order to solve the rainfall estimation error caused by various noise factors such as clutter,super refraction,and raindrops during the detection process of Doppler weather radar.This paper proposes to improve the r...In order to solve the rainfall estimation error caused by various noise factors such as clutter,super refraction,and raindrops during the detection process of Doppler weather radar.This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter.After data preprocessing,the radar data should be classified according to the precipitation intensity.And then,they are respectively substituted into the improved filter for calibration.The state noise variance Q(k)and the measurement noise variance R(k)can be adaptively calculated and updated according to the input observation data during this process.Then the optimal parameter value of each type of precipitation intensity can be obtained.The state noise variance Q(k)and the measurement noise variance R(k)could be assigned optimal values when filtering the remaining data.This rainfall estimation based on semiadaptive Kalman filter calibration not only improves the accuracy of rainfall estimation,but also greatly reduces the amount of calculation.It avoids errors caused by repeated calculations,and improves the efficiency of the rainfall estimation at the same time.展开更多
基金supported by the National Natural Science Foundation of China (60472021).
文摘A novel and efficient method for decomposing a signal into a set of intrinsic mode functions （IMFs） and a trend is proposed. Unlike the original empirical mode decomposition （EMD）, which uses spline fits to extract variations from the signal by separating the local mean from the fluctuations in the decomposing process, this new method being proposed takes advantage of the theory of variable finite impulse response （FIR） filtering where filter coefficients and breakpoint frequencies can be adjusted to track any peak-to-peak time scale changes. The IMFs are results of a multiple variable frequency response FIR filtering when signals pass through the filters. Numerical examples validate that in contrast with the original EMD, the proposed method can fine-tune the frequency resolution and suppress the aliasing effectively.
基金Project supported by the National Natural Science Foundation of China(Grant No.61307020)Beijing Natural Science Foundation(Grant No.4172038)the Qingdao Opto-electronic United Foundation,China
文摘A light field modulated imaging spectrometer （LFMIS） can acquire the spatial-spectral datacube of targets of interest or a scene in a single shot. The spectral information of a point target is imaged on the pixels covered by a microlens. The pixels receive spectral information from different spectral filters to the diffraction and misalignments of the optical components. In this paper, we present a linear spectral multiplexing model of the acquired target spectrum. A calibration method is proposed for calibrating the center wavelengths and bandwidths of channels of an LFMIS system based on the liner-variable filter （LVF） and for determining the spectral multiplexing matrix. In order to improve the accuracy of the restored spectral data, we introduce a reconstruction algorithm based on the total least square （TLS） approach. Simulation and experimental results confirm the performance of the spectrum reconstruction algorithm and validate the feasibility of the proposed calibrating scheme.
文摘针对薄膜体声波谐振腔(FBAR)滤波器测试夹具误差校准,提出一种改进的TRL校准方法,将三维电磁仿真和TRL计算结合,用于测试套件(夹具和TRL校准件)的前期设计与优化,确保TRL校准件达到足够精度。由于DUT(device under test,待测器件)参数未知,实测中采用四种不同结构的测试套件,校准前各组测试结果差异较大,但TRL校准后高度吻合,通带内的差异小于0.2 dB,不但精准确定DUT真实参数,而且表明本TRL校准方法对于不同结构夹具去嵌入的有效性。该仿真计算不仅可以设计高精度测试套件,避免过度依靠实测,并且可与实测相互验证,并可推广到其他微波器件的测量,节省测试成本。
基金supported by National Natural Science Foundation of China under Grants No.61471322
文摘In the forthcoming 5G systems, new technologies, such as amorphous networks and non-orthogonal filter bank multicarriers(FBMC), provide an effective way to accommodate high-rate transmissions. Meanwhile, the prototype filter affects the adjacent channel interference, and therefore is important for FBMC systems. Besides, once the amorphous network is taken into account, the requirement for interference controlmust be much stricter. Accordingly, this paper focuses on the design of prototype filter with better ability of interference controlling, where we exploit the nonlinear phase FIR filter(NLPFF) instead of traditional linear phase FIR filter(LPFF) to achieve more optimization spaces under a small sacrifice of linear phase. In ourdesigns, both the amplitude and phase responsesare handled independently to approach the stopband performance enhancements, in while the nearly perfect reconstruction(NPR) conditionsare relaxed by pre-specified thresholds. Computer simulations confirm the effectiveness of the NLPFF designs, and demonstrate the advantages of the proposed NLPFF in FBMC applications.
基金This work was supported by the National Natural Science Foundation of China(Grant No.42075007)the Open Grants of the State Key Laboratory of Severe Weather(No.2021LASW-B19).
文摘In order to solve the rainfall estimation error caused by various noise factors such as clutter,super refraction,and raindrops during the detection process of Doppler weather radar.This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter.After data preprocessing,the radar data should be classified according to the precipitation intensity.And then,they are respectively substituted into the improved filter for calibration.The state noise variance Q(k)and the measurement noise variance R(k)can be adaptively calculated and updated according to the input observation data during this process.Then the optimal parameter value of each type of precipitation intensity can be obtained.The state noise variance Q(k)and the measurement noise variance R(k)could be assigned optimal values when filtering the remaining data.This rainfall estimation based on semiadaptive Kalman filter calibration not only improves the accuracy of rainfall estimation,but also greatly reduces the amount of calculation.It avoids errors caused by repeated calculations,and improves the efficiency of the rainfall estimation at the same time.
