Research On The Target Radiation Detection By Spatial Spectrum Algorithm

The passivity detection technology based on microwave thermal radiation plays more and more important role in the field of detecting stealthy target, since it is difficult to be detected by hostile and interfered by atrocious weather or the dust in war field. In order to improve the spatial resolution, the spatial spectrum estimation is applied to exceed the spatial resolution limitation of antenna array dimension. In this article, the principle of the microwave thermal radiation detection technology based on spatial spectrum estimation is researched, and its capability analysis model is built.Firstly in this article, the signal characteristic of the microwave thermal radiation detection is analyzed, and the principle of the microwave thermal radiation detection based on spatial spectrum estimation is researched. Then, the feasibility of the microwave thermal radiation detection based on spatial spectrum estimation is proved.The capability analysis model of the microwave thermal radiation detection based on spatial spectrum estimation is built, and the detection capability is analyzed and compared with other detection algorithms'. The result indicates the sensitivity of spatial spectrum estimation algorithm is same with others, but its spatial resolution is better.The Microwave Thermal Radiation Detection Simulation System is established with VC, and the spatial spectrum estimation signal processing module is realized. Then, the algorithm's capabilities are simulated, and the result proves validity of the capability analysis model.Finally, using the 16 units 8mm antenna array of microwave thermal radiation detection system, single noise source and double noise source detection experiments in short distance are introduced. The result proves validity of the capability analysis model.In this article, the results indicate that the detection algorithm based on spatial spectrum estimation can catch the targets in the certain distance. And compared with traditional signal process methods, it can distinguish closer targets because of its super spatial resolution capability.