Due to the limitation of high sampling rate and large coding matrix, it often takes a long time to decode and reconstruct millimeter-wave radiometric images, which becomes a difficult problem for Compressed Sensing (CS) theory in the field of millimeter-wave radiometric imaging. In order to effectively reconstruct millimeter-wave images within the framework of block-based CS, the adaptive sampling methods based on visual saliency and block information weight are proposed in this paper. In view of the irrationality of allocating the same amount of encoded data to different image blocks in the traditional block-based CS, both the adaptive sampling method based on visual saliency and local variance weighted adaptive allocation, and the adaptive sampling method based on visual saliency and two-dimensional information entropy weighted adaptive allocation, are put forward and compared with other allocation methods. Some experimental results demonstrate that the proposed method can effectively improve the PSNR value of the reconstructed image. In addition, the reconstructed images with a low sampling rate are also in conformity with human vision.
The nonlinear bias analysis and correction of receiving channels in Chinese FY-3C meteorological satellite Microwave Temperature Sounder (MWTS) is a key technology of data assimilation for satellite radiance data. The thermal-vacuum chamber calibration data acquired from the MWTS can be analyzed to evaluate the instrument performance, including radiometric temperature sensitivity, channel nonlinearity and calibration accuracy. Especially, the nonlinearity parameters due to imperfect square-law detectors will be calculated from calibration data and further used to correct the nonlinear bias contributions of microwave receiving channels. Based upon the operational principles and thermalvacuum chamber calibration procedures of MWTS, this paper mainly focuses on the nonlinear bias analysis and correction methods for improving the calibration accuracy of the important instrument onboard FY-3C meteorological satellite, from the perspective of theoretical and experimental studies. Furthermore, a series of original results are presented to demonstrate the feasibility and significance of the methods.
An efficient hybrid algorithm is proposed to analyze the electromagnetic scattering properties of metal objects in the lower terahertz (THz) frequency. The metal object can be viewed as perfectly electrical conducting object with a slightly rough surface in the lower THz region. Hence the THz scattered field from metal object can be divided into coherent and incoherent parts. The physical optics and truncated-wedge incremental-length diffraction coefficients methods are combined to compute the coherent part; while the small perturbation method is used for the incoherent part. With the MonteCarlo method, the radar cross section of the rough metal surface is computed by the multilevel fast multipole algorithm and the proposed hybrid algorithm, respectively. The numerical results show that the proposed algorithm has good accuracy to simulate the scattering properties rapidly in the lower THz region.
KEYWORDS: Extremely high frequency, Imaging systems, Antennas, Millimeter wave imaging, Detection and tracking algorithms, Metals, Explosives, Reflectivity, Temperature metrology, Ka band
The increasingly emerging terrorism attacks and violence crimes around the world have posed severe threats to public security, so carrying out relevant research on advanced experimental methods of personnel concealed contraband detection is crucial and meaningful. All of the advantages of imaging covertly, avoidance of interference with other systems, intrinsic property of being safe to persons under screening , and the superior ability of imaging through natural or manmade obscurants, have significantly combined to enable millimeter-wave (MMW) radiometric imaging to offer great potential in personnel concealed contraband detection. Based upon the current research status of MMW radiometric imaging and urgent demands of personnel security screening, this paper mainly focuses on the experimental methods of indoor MMW radiometric imaging. The reverse radiation noise resulting from super-heterodyne receivers seriously affects the image experiments carried out at short range, so both the generation mechanism and reducing methods of this noise are investigated. Then, the benefit of sky illumination no longer exists for the indoor radiometric imaging, and this leads to the decrease in radiometric temperature contrast between target and background. In order to enhance the radiometric temperature contrast for improving indoor imaging performance, the noise illumination technique is adopted in the indoor imaging scenario. In addition, the speed and accuracy of concealed contraband detection from acquired MMW radiometric images are usually restricted to the deficiencies in traditional artificial interpretation by security inspectors, thus an automatic recognition and location algorithm by integrating improved Fuzzy C-means clustering with moment invariants is put forward. A series of original results are also presented to demonstrate the significance and validity of these methods.
With advances in millimeter-wave technology, passive millimeter-wave (PMMW) imaging technology has received
considerable concerns, and it has established itself in a wide range of military and civil practical applications, such as in
the areas of remote sensing, blind landing, precision guidance and security inspection. Both the high transparency of
clothing at millimeter wavelengths and the spatial resolution required to generate adequate images combine to make
imaging at millimeter wavelengths a natural approach of screening people for concealed contraband detection. And at
the same time, the passive operation mode does not present a safety hazard to the person who is under inspection. Based
on the description to the design and engineering implementation of a W-band two-dimensional (2D) planar scanning
imaging system, a series of scanning methods utilized in PMMW imaging are generally compared and analyzed,
followed by a discussion on the operational principle of the mode of 2D planar scanning particularly. Furthermore, it is
found that the traditional radiometer uncertainty equation, which is derived from a moving platform, does not hold under
this 2D planar scanning mode due to the fact that there is no absolute connection between the scanning rates in
horizontal direction and vertical direction. Consequently, an improved radiometer uncertainty equation is carried out in
this paper, by means of taking the total time spent on scanning and imaging into consideration, with the purpose of
solving the problem mentioned above. In addition, the related factors which affect the quality of radiometric images are
further investigated under the improved radiometer uncertainty equation, and ultimately some original results are
presented and analyzed to demonstrate the significance and validity of this new methodology.
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