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本文通过对红外和多光谱扫描物理机理的分析和典型实例计算,表明快速傅里叶变换解卷积方法能提高遥感系统的分辨率,较好地重现地面目标的真实分布。当扫描仪扫过一维排列的若干个目标时,系统的响应是瞬时视场和目标辐射分布的卷积。当地面目标间隔小于瞬时视场宽度时,地面目标的间隔越小,响应波形的交迭就越严重,以致不能分辨目标。借助计算机技术,对上述响应波形以一定的采样步长离散化,并截取有限长度的N个数值作原响应函数的近似,然后对此进行傅里叶变换,可得到响应波形的离散频谱,再经逆傅氏变换可求出地面目标的真实分布。为了改善高频收敛性,减小吉布斯振荡和漏谱现象,在解卷积过程中,N的取值要尽量大,步长应适当,而且还必须选取合适的窗函数。
In this paper, the physical mechanism of infrared and multispectral scanning is analyzed and the typical examples are calculated. It shows that the fast Fourier transform deconvolution method can improve the resolution of remote sensing system and reproduce the true distribution of ground targets well. When the scanner sweeps through several targets in a one-dimensional arrangement, the response of the system is the convolution of the instantaneous field of view and the target radiation distribution. When the ground target interval is less than the instantaneous field of view width, the smaller the ground target interval, the more severe the overlap of the response waveforms is, so that the target can not be distinguished. With the aid of computer technology, the above response waveforms are discretized with a certain sampling step size, and N numbers of finite length are intercepted for the approximation of the original response function, and then the Fourier transform is performed to obtain the discrete frequency spectrum of the response waveform The inverse Fourier transform can be obtained by the true distribution of ground targets. In order to improve the high-frequency convergence and reduce the Gibbs oscillation and drain spectrum, during the deconvolution process, the value of N should be as large as possible, the step size should be appropriate, and the appropriate window function must also be selected.