Passive millimeter-wave imaging is one of the most important approaches for personnel security inspection to detect concealed objects hidden under clothing. Many imaging systems have been constructed and tried out experimentally in various real scenarios. However, plenty of imaging results show that some hidden objects placed on the body edge areas may have low contrast and are difficult to detect. There are different contrasts in different polarization images. In this article, we propose a physically-based subregional polarization fusion method by modulating multipolarization information to enhance the contrast between edge objects and the body background. The physical model and polarization properties of edge objects are investigated by theoretical calculation and simulation analysis. By dividing the body area into four typical subregions based on the second and third Stokes components ( $T_{Q}$ and $T_{U}$ ), four linear polarization images are automatically fused to directly generate an enhancement image. Without complicated parameter adjustment, the proposed method can adaptively realize the global optimal contrast by fusing the local optimal regions of different polarization images at the pixel level. Simulation and measurement results demonstrate the effectiveness of the method. By comparing with three traditional fusion methods, differential signal noise ratio, receiver operating characteristic curve, and segmentation metric are utilized to quantitatively evaluate the superior performance of our fusion method.

Passive millimeter-wave imaging (PMMW) is one of the important approaches for remote sensing and target detection in the ocean background. In general, seawater always fluctuates under the influence of factors such as wind, earthquakes, tidal forces, and ship movements. The undulating waves produce many bright or dark spots of brightness temperature (TB). This complex background may increase the difficulty of object detection for observers and post-processing algorithms. In this paper, we comprehensively assess the polarization properties of PMMW imaging for sea scene observation, both theoretically and experimentally. According to the millimeter-wave radiation propagation model, the TB difference characteristics between ship and seawater under various conditions are calculated and analyzed. Based on the simulated and measured experimental data, the polarization TB and the multi-polarization parameter images are qualitatively and quantitatively discussed using performance metrics such as statistical histograms, differential signal-to-noise ratio (DSNR), receiver operating characteristic (ROC) curves, and survey scoring. The analysis results show that vertical polarization is usually the optimal polarization observation mode under most conditions. For the long observation distance or very small angle of incidence, different polarization responses might be comparable. In addition, if the system can obtain multi-polarization images at the same time, polarization fusion can bring more advantages for target enhancement, detection, and recognition.

Exploiting physical (PHY)-layer characteristics for authentication has great potential to provision underlying trust for low-ended Internet of things (IoT) devices with limited computation resources. In this paper, we propose an online learning aided adaptive PHY-layer authentication framework for enhanced authenticity provisioning. Instead of relying on some preset PHY-layer signatures with scenario-sensitive ?thresholds?, multiple PHY-layer attributes are jointly considered by the proposed scheme to improve the reliability and robustness of PHY-layer authentication. Such a dimension extension on PHY-layer signatures can effectively deteriorate the spoofing capability of malicious attackers. However, it also complicates the predicting and authenticating procedure of the legitimate receiver. Therefore, artificial intelligence aided search algorithms are formulated to facilitate adaptive selection of the Most Effective PHY-layer Attributes (MEA) through learning their historical authenticity performance. To be specific, the attributes which are predicted to be effective in maximizing the authentication capability, in terms of low false alarm rate and low miss detection rate, will be dynamically selected by the authenticator in an autonomous manner. Theoretical analysis shows that the proposed learning algorithm achieves asymptotically diminishing regret. Moreover, extensive experiments are conducted using Universal Software Radio Peripherals (USRPs) in a laboratory environment, which further validates the efficiency of the proposed scheme.

To address the bandwidth limitations encountered by existing decoupling methods during the global integration process of base station antennas, a radiative deep-subwavelength frequency selective surface (RFSS)-based cross-band decoupling method is proposed. The RFSS is formed by a deep-subwavelength FSS whose external profile is defined by a well-optimized narrow frame. It is implemented to not only be transparent for high-band (HB) electromagnetic waves, but also effectively radiates low-band (LB) ones. To validate this concept, a dual-band base station antenna which comprises an RFSS-based LB antenna and a 2×2 HB sub-array is proposed. Furthermore, we conduct a detailed analysis of the operational mechanism underlying the proposed RFSS-based LB antenna. In addition, a proof-of-concept prototype is fabricated and measured. The results demonstrate that the LB antenna operates within a relatively wideband of 1.4-2.7GHz (63.4%), featuring a low profile of 0.25λ _lc (at the center frequency of LB), and the HB antenna operates at 3.3-4.2GHz (24%).

A compact, low-profile, two-port dual-band circularly polarized (CP) stacked patch antenna for radio-frequency identification (RFID) multiple-input-multiple-output (MIMO) readers is proposed, which employs the shared-aperture technique. The proposed antenna adopts a 1.524 mm thickness Rogers Ro4350b substrate with relative permittivity of 3.48. Two pairs of isolated ports are working at two microwave- (MW-) RFID bands (2.4–2.485 GHz and 5.725–5.875 GHz) with high port isolation of 25 dB and 30 dB, respectively. A shared metal slot layer is designed to separate two feeding structures of the lower band and upper band for port isolation enhancement as well as saving space. Corner-truncated square slot and patch configurations have been designed to obtain CP modes. In the lower and upper MW-RFID bands, the relative impedance bandwidths are 12.2% and 5.7%, and the maximum realized gains are higher than 7.3 dBic. Moreover, two-element configurations have been combined for an RFID MIMO system that occupies a dimension of 119 mm × 119 mm × 12.9 mm. The MIMO antenna performance of envelope correlation coefficient (ECC) is lower than 0.03, and diversity gain is close to 10 dB.

Due to the fast scanning capabilities and sparse arrangement, multiple-input multiple-output (MIMO) arrays have gained widespread use in millimeter-wave (MMW) holographic imaging. The traditional image reconstruction for arbitrary MIMO arrays relies on the digital focusing (DF) method, which involves extensive phase compensating calculations. To overcome this challenge, we present an accelerated DF method based on dimension reduction (DR) and fast Fourier transform (FFT), which reduces computational complexity from $O(N^{6})$ to $O(N^{3}\log N)$ . Simulation and measurement experimental results demonstrate that our proposed method can achieve a 109-fold speedup for cross-orthogonal array scanning simulation and a 433-fold speedup for 1-D MIMO array scanning experiment compared to the original DF method while containing almost no image quality loss.