Distributed Multiband Synthetic Aperture Radar Image Fusion Based on Wavelet Transform in the Internet of Things Environment

Abstract

Abstract In order to improve the detection and recognition capabilities of distributed multiband synthetic aperture radar (SAR) images in the Internet of Things environment, a distributed multiband SAR image fusion algorithm based on wavelet transform is proposed for the Internet of Things environment. The multispectral/hyperspectral imager is used to detect and process the distributed multiband SAR image. The feature extraction method of fast spatial geographic water target range radar signal source is used to extract and segment the distributed multiband SAR image. The wavelet multiscale transform method is used to segment the SAR image, and the linear filtering and nonlinear filtering methods are used to detect the edge contour features. Using the distributed multiband SAR image fusion technology based on the calculation of high-frequency subband edge function and the segmentation of regional gray contour curve, the splitting and broadening of the peak spectrum of the target image of the radar signal source in the fast spatial geographical waters, as well as the radar target positioning parameters, the noise filtering, and anti-jamming detection of the distributed multiband SAR image are realized, and the distributed multiband SAR image fusion is realized combined with wavelet transform. The test results show that the output peak signal-to-noise ratio of distributed multiband SAR image fusion using this method is high, and the performance of detection and recognition of SAR imaging targets and the ability of edge contour feature extraction are good.