This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on ...This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.展开更多
Channel estimation is very important for MIMO (Multiple Input Multiple Output) OFDM (Or-thogonal Frequency Division Multiplexing) systems, but its precision is reduced due to the noise in channel. In this letter, circ...Channel estimation is very important for MIMO (Multiple Input Multiple Output) OFDM (Or-thogonal Frequency Division Multiplexing) systems, but its precision is reduced due to the noise in channel. In this letter, circularly slipping window is introduced to resist the noise. It can be proved by simulation that with the same channel model, optimal slipping window length is the same with different vehicle speed. MSE (Minimum Square Error) of channel is greatly reduced with circularly slipping window, and performance of the system is closed to that with correct channel estimation.展开更多
文摘This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.
文摘Channel estimation is very important for MIMO (Multiple Input Multiple Output) OFDM (Or-thogonal Frequency Division Multiplexing) systems, but its precision is reduced due to the noise in channel. In this letter, circularly slipping window is introduced to resist the noise. It can be proved by simulation that with the same channel model, optimal slipping window length is the same with different vehicle speed. MSE (Minimum Square Error) of channel is greatly reduced with circularly slipping window, and performance of the system is closed to that with correct channel estimation.
