Biblio

Compressive Covariance Sampling (CCS) is a strategy used to recover the covariance matrix (CM) directly from compressive measurements. Several works have proven the advantages of CSS in Compressive Spectral Imaging (CSI) but most of these algorithms require multiple random projections of the scene to obtain good reconstructions. However, several low-resolution copies of the scene can be captured in a single snapshot through a lenslet array. For this reason, this paper proposes a sensing protocol and a single snapshot CCS optical architecture using a lenslet array based on the Dual Dispersive Aperture Spectral Imager(DD-CASSI) that allows the recovery of the covariance matrix with a single snapshot. In this architecture uses the lenslet array allows to obtain different projections of the image in a shot due to the special coded aperture. In order to validate the proposed approach, simulations evaluated the quality of the recovered CM and the performance recovering the spectral signatures against traditional methods. Results show that the image reconstructions using CM have PSNR values about 30 dB, and reconstructed spectrum has a spectral angle mapper (SAM) error less than 15° compared to the original spectral signatures.

With the vastly growing need for secure communication, quantum key distribution (QKD) has been developed to provide high security for communications against potential attacks from the fast-developing quantum computers. Among different QKD protocols, continuous variable (CV-) QKD employing Gaussian modulated coherent states has been promising for its complete security proof and its compatibility with current communication systems in implementation with homodyne or heterodyne detection. Since satellite communication has been more and more important in developing global communication networks, there have been concerns about the security in satellite communication and how we should evaluate the security of CV-QKD in such scenarios. To better analyse the secure key rate (SKR) in this case, in this invited paper we investigate the CV-QKD SKR lower bounds under realistic assumptions over a satellite-to-satellite channel. We also investigate the eavesdropper's best strategy to apply in these scenarios. We demonstrate that for these channel conditions with well-chosen carrier centre frequency and receiver aperture size, based on channel parameters, we can optimize SKR correspondingly. The proposed satellite-based QKD system provides high security level for the coming 5G and beyond networks, the Internet of things, self-driving cars, and other fast-developing applications.

We propose a novel hybrid imaging system to acquire 4D high-speed hyperspectral (HSHS) videos with high spatial and spectral resolution. The proposed system consists of two branches: one branch performs Nyquist sampling in the temporal dimension while integrating the whole spectrum, resulting in a high-frame-rate panchromatic video; the other branch performs compressive sampling in the spectral dimension with longer exposures, resulting in a low-frame-rate hyperspectral video. Owing to the high light throughput and complementary sampling, these two branches jointly provide reliable measurements for recovering the underlying HSHS video. Moreover, the panchromatic video can be used to learn an over-complete 3D dictionary to represent each band-wise video sparsely, thanks to the inherent structural similarity in the spectral dimension. Based on the joint measurements and the self-adaptive dictionary, we further propose a simultaneous spectral sparse (3S) model to reinforce the structural similarity across different bands and develop an efficient computational reconstruction algorithm to recover the HSHS video. Both simulation and hardware experiments validate the effectiveness of the proposed approach. To the best of our knowledge, this is the first time that hyperspectral videos can be acquired at a frame rate up to 100fps with commodity optical elements and under ordinary indoor illumination.

Visible light communication is a solution for high-security wireless data transmission. In this paper, we first analyze the potential vulnerability of the system from eavesdropping outside the room. By setting up a signal to noise ratio threshold, we define a vulnerable area outside of the room through a window. We compute the receiver aperture needed to capture the signal and what portion of the space is most vulnerable to eavesdropping. Based on the analysis, we propose a solution to improve the security by optimizing the modulation efficiency of each LED in the indoor lamp. The simulation results show that the proposed solution can improve the security considerably while maintaining the indoor communication performance.

This paper proposes an algorithm for multi-channel SAR ground moving target detection and estimation using the Fractional Fourier Transform(FrFT). To detect the moving target with low speed, the clutter is first suppressed by Displace Phase Center Antenna(DPCA), then the signal-to-clutter can be enhanced. Have suppressed the clutter, the echo of moving target remains and can be regarded as a chirp signal whose parameters can be estimated by FrFT. FrFT, one of the most widely used tools to time-frequency analysis, is utilized to estimate the Doppler parameters, from which the moving parameters, including the velocity and the acceleration can be obtained. The effectiveness of the proposed method is validated by the simulation.