To improve the performance of multiple-input-multiple-output (MIMO) radar, various sparse arrays have been employed. However, the angular resolution of existing non-uniform arrays optimized by either combinatorial algorithms or heuristic ones is limited by the Rayleigh criterion, which is strictly related to the aperture size. Based on the angular ambiguity function (AAF) analysis, two new models are established in this work for directly optimizing the sidelobe level (SLL) or the main lobe width (MLW) with the constraints of aperture size and element spacing. The aforementioned designs result in non-convex and nonlinear optimization problems, and solutions are derived via the alternating direction multiplier method (ADMM). Furthermore, considering a parametric trade-off between SLL and MLW, a hybrid algorithm is proposed to search for the SLL-MLW Pareto front boundary. Finally, simulations are provided to demonstrate the high angular resolution and ambiguity-free properties of the optimized sparse arrays.

We report on a ${\mathrm{Si}}_{\text{1−x}}{\mathrm{Ge}}_x/\mathrm{Si}$ multiple quantum-well resonant-cavity-enhanced (RCE) photodetector with a silicon-on-oxide reflector as the bottom mirror operating near 1.3 μm. The breakdown voltage of the photodetector is above 18 V and the dark current density at 5 V reverse bias is 12 pA/μm². The RCE photodetector shows enhanced responsivity with a clear peak at 1.285 μm and the peak responsivity is measured around 10.2 mA/W at a reverse bias of 5 V. The external quantum efficiency at 1.3 μm is measured to be 3.5% under reverse bias of 16 V, which is enhanced three- to fourfold compared with that of a conventional p-i-n photodetector with a Ge content of 0.5 reported in 1995 by Huang et al. [Appl. Phys. Lett. 67, 566 (1995)].

Vehicular Ad-Hoc Networks (VANETs) have received a great attention recently due to their potential and various applications. However, the initial phase of the VANET has many research challenges that need to be addressed, such as the issues of security and privacy protection caused by the openness of wireless communication networks among the city-wide applied regions. Specially, anomaly detection for a VANET has become a challenging problem, due to the changes in the scenario of VANETs comparing with traditional wireless networks. Motivated by this issue, we focus on the problem of anomaly detection in VANETs, and propose an effective anomaly detection approach based on the convolutional neural network in this paper. The proposed approach takes into account the spatio-temporal and sparse features of VANET traffic, and it uses a convolutional neural network architecture and a loss function based on Mahalanobis distance to extract and estimate the traffic matrix. Then, reinforcement learning is used to implement anomaly detection. Furthermore, a comprehensive assessment is provided to validate the proposed approach, which illustrates the effectiveness of this approach.

Air moving target indication (AMTI) is an important task of spaceborne radar. Medium-earth-orbit (MEO) synthetic aperture radar (SAR) has the characteristics of large coverage, short revisit time, and high orbital altitude, and thus is an attractive tool for AMTI missions. However, due to air moving target’s high-speed maneuvering and MEO SAR’s long synthetic aperture time and significant curvature of trajectory, the signal of air moving target after imaging processing is very complex, which makes the design of AMTI method be challenging. In this paper, a study on image-domain signal modeling and refocusing of air moving target for MEO multichannel SAR is presented. The range equation of an air moving target with three-dimensional velocities and accelerations is established. In addition, the target’s signal models after range migration correction and azimuth compression with the stationary scene parameters are derived. Then, via dividing targets into three types based on their residual range migration and Doppler ambiguity, the image-domain signal models of air moving targets are developed. Furthermore, a refocusing method that can cope with large range migration and Doppler ambiguity is proposed. Finally, numerical experiments are conducted to validate the developed signal models and proposed refocusing method.

For multichannel synthetic aperture radar (SAR) ground moving target indication (GMTI) systems, the clutter suppression method based on post-Doppler space time adaptive processing technology is popular due to its excellent performance. However, to coherently integrate a target's energy of each channel, this kind of method requires a search of target's velocity, which would introduce a large computation load when the search step size is too small. While the existing studies mainly focus on improving its performance in the cases of complex scenes and geometries, the studies on optimizing the search step size are rare. To address this issue, this paper proposes a method for calculating the optimal velocity search step size of adaptive clutter suppression for the commonly used airborne three-channel SAR-GMTI systems. First, the signal models in the range Doppler domain are developed. Then, considering that both the signal-to-clutter-noise ratio loss of clutter suppression and the coherent integration gain loss are introduced by the mismatch of target's steer vector, the relationship between the coherent accumulation gain loss and the velocity search error is utilized to develop the analytical expression for the optimal velocity search step size. Experimental results validate the proposed method.

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.