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Frequency diversity array (FDA) has been widely studied due to its nature of range-angle-dependent. However, the basic FDA generates an S-shaped range-angle coupled beampattern, which limits its application in target detection and localization. Recently, the FDA with sinusoidal frequency offset (Sin-FDA) has been proposed, which provides a narrow pencil beampattern, but at the cost of high sidelobes. In this letter, the FDA with modified sinusoidal frequency offset (MSin-FDA) is proposed. In MSin-FDA, the frequency offset of Msin-FDA can be flexibly adjusted by introducing extra configuration parameters. In addition, we use genetic algorithm to optimize the configuration parameters so as to obtain an enhanced beampattern. Simulation results demonstrate that, compared with the existing FDA schemes with nonuniform frequency offset, the proposed method has better spatial focusing, sidelobe suppression, and array resolution performance under the same total frequency offset.

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 Microwave Atmospheric Temperature and Humidity Sounder (MATHS) is a 20-channel cross-track scanning microwave radiometer that can be utilized for sounding the atmospheric temperature and humidity profiles from an airplane with a maximum fight altitude of 5km. The design scheme of MATHS is demonstrated, including the system configuration, operational bands, multi-band antenna, receiver types, and calibration methods. In addition, some inflight sounding results are also presented to verify the instrument’s significance.

The single-pixel imaging (SPI) technique enables the tracking of moving targets at a high frame rate. However, when extended to the problem of multi-target tracking, there is no effective solution using SPI yet. Thus, a multi-target tracking method using windowed Fourier single-pixel imaging (WFSI) is proposed in this paper. The WFSI technique uses a series of windowed Fourier basis patterns to illuminate the target. This method can estimate the displacements of K independently moving targets by implementing 6K measurements and calculating 2K windowed Fourier coefficients, which is a measurement method with low redundancy. To enhance the capability of the proposed method, we propose a joint estimation approach for multi-target displacement, which solves the problem where different targets in close proximity cannot be distinguished. Using the independent and joint estimation approaches, multi-target tracking can be implemented with WFSI. The accuracy of the proposed multi-target tracking method is verified by numerical simulation to be less than 2 pixels. The tracking effectiveness is analyzed by a video experiment. This method provides, for the first time, an effective idea of multi-target tracking using SPI.

Millimetre-wave (MMW) radiometric imaging has established itself in a wide range of military and civil applications, but the fact that the radiometric temperature contrast between different objects indoors is low restricts the commercial application of MMW radiometric imaging to some extent. Based on the particular analysis of MMW radiometric imaging model suitable for concealed contraband detection on personnel, the method of adopting MMW noise source to illuminate the scene of being imaged to improve the radiometric temperature contrast, just like the flash lamp of camera, is proposed in this study. In addition, the choice of both the ways of illumination and the excess noise ratio (ENR) of the noise source is analysed. Then the image degradation model is discussed and the projection onto the convex sets (POCS) algorithm for MMW radiometric image super-resolution restoration is depicted in detail. In addition, a series of experiments are carried out both indoors and outdoors, with the dual-channel radiometric imaging system that has been implemented at W-band with the mode of two-dimensional planar scanning. The experimental results are presented and analysed to validate the significance of the imaging model and it is indicated that the radiometric imaging system is capable of detecting metal objects hidden underneath clothing, and the method of adopting noise illumination can improve the quality of radiometric images.