Passive Millimeter Wave Fast Algorithm Research

Passive Millimeter-wave(PMMW)imaging,as a new tool,has important research significance in the field of scene detection.It can be used to understand the radiation properties of target objects and explain radiation phenomena through the bright temperature distribution of bright temperature images,which can provide theoretical support for practical detection work and also serve as a verification of detection results.At present,the research work on imaging simulation has made some progress,but the efficiency of imaging needs to be further improved.Based on this,this thesis investigates passive millimeter wave simulated imaging,and the specific research results are as follows:1.A tracking model for rays from smooth and rough surfaces and an inversion model for bright temperature are outlined,a detailed model for the calculation of emissivity is presented,and the problems of the traditional passive millimeter wave simulation imaging method in terms of computational efficiency are investigated.In addition,this thesis finds that the conventional ray emission method determines the direction of ray emission by uniform division of the pitch and azimuth angles,and the radiation bright temperature map obtained by this method leads to distortion of the position information of the objects in the map.To solve this problem,this thesis proposes a new method of ray emission which uses a fixed azimuthal emission method on the bottom surface,which can more accurately describe the position information of the object,thus extending the applicability of passive millimeter wave radiation simulation.2.To address the relatively low computational efficiency of the multilayer bright-temperature tracking method,a fast algorithm for region densification is proposed,which uses the densification of rays in a specific region to achieve the effect of improving the computational efficiency.The results show that the proposed fast algorithm for region densification can reduce the number of rays required for sub-layers while maintaining the relative error,thus significantly reducing the computation time and improving the computation efficiency while meeting the accuracy requirements.The factors affecting the optimal densification region of a rough surface are subsequently investigated and it is found that the optimal densification region of a rough surface is influenced by the roughness of the surface.