Joint-2D-SL0 Algorithm for Joint Sparse Matrix Reconstruction

Sparse matrix reconstruction has a wide application such as DOA estimation and STAP. However, its performance is usually restricted by the grid mismatch problem. In this paper, we revise the sparse matrix reconstruction model and propose the joint sparse matrix reconstruction model based on one-order Taylor expansion. And it can overcome the grid mismatch problem. Then, we put forward the Joint-2D-SL0 algorithm which can solve the joint sparse matrix reconstruction problem efficiently. Compared with the Kronecker compressive sensing method, our proposed method has a higher computational efficiency and acceptable reconstruction accuracy. Finally, simulation results validate the superiority of the proposed method

Syntaxin of plants71 plays essential roles in plant development and stress response via regulating pH homeostasis

SYP71, a plant-specific Qc-SNARE with multiple subcellular localization, is essential for symbiotic nitrogen fixation in nodules in Lotus, and is implicated in plant resistance to pathogenesis in rice, wheat and soybean. Arabidopsis SYP71 is proposed to participate in multiple membrane fusion steps during secretion. To date, the molecular mechanism underlying SYP71 regulation on plant development remains elusive. In this study, we clarified that AtSYP71 is essential for plant development and stress response, using techniques of cell biology, molecular biology, biochemistry, genetics, and transcriptomics. AtSYP71-knockout mutant atsyp71-1 was lethal at early development stage due to the failure of root elongation and albinism of the leaves. AtSYP71-knockdown mutants, atsyp71-2 and atsyp71-3, had short roots, delayed early development, and altered stress response. The cell wall structure and components changed significantly in atsyp71-2 due to disrupted cell wall biosynthesis and dynamics. Reactive oxygen species homeostasis and pH homeostasis were also collapsed in atsyp71-2. All these defects were likely resulted from blocked secretion pathway in the mutants. Strikingly, change of pH value significantly affected ROS homeostasis in atsyp71-2, suggesting interconnection between ROS and pH homeostasis. Furthermore, we identified AtSYP71 partners and propose that AtSYP71 forms distinct SNARE complexes to mediate multiple membrane fusion steps in secretory pathway. Our findings suggest that AtSYP71 plays an essential role in plant development and stress response via regulating pH homeostasis through secretory pathway

Enhanced 2D-DOA Estimation for Large Spacing Three-Parallel Uniform Linear Arrays

An enhanced two-dimensional direction of arrival (2D-DOA) estimation algorithm for large spacing three-parallel uniform linear arrays (ULAs) is proposed in this paper. Firstly, we use the propagator method (PM) to get the highly accurate but ambiguous estimation of directional cosine. Then, we use the relationship between the directional cosine to eliminate the ambiguity. This algorithm not only can make use of the elements of the three-parallel ULAs but also can utilize the connection between directional cosine to improve the estimation accuracy. Besides, it has satisfied estimation performance when the elevation angle is between 70° and 90° and it can automatically pair the estimated azimuth and elevation angles. Furthermore, it has low complexity without using any eigen value decomposition (EVD) or singular value decompostion (SVD) to the covariance matrix. Simulation results demonstrate the effectiveness of our proposed algorithm

Analysis of the impact of traction power supply system containing new energy on the power quality of the power system

The access of new energy in the traction power supply system (TPSS) can not only realize low-carbon operation of electrified railroads in the western region, but also promote elimination on the spot of new energy. However, it also brings a series of power quality problems to the power system. The objective of this study was to analyze the impact of TPSS containing new energy on the power quality of the power system. Firstly, a probabilistic model of TPSS containing new energy is established by means of the randomness of locomotive and new energy output power; Secondly, it is analyzed theoretically that the impact of new energy access to the TPSS on the voltage imbalance, power factor and voltage deviation of power system; Finally, Monte Carlo simulation is applied to calculate the probabilistic load flow to obtain the evaluation index, which is used to quantify the impact of new energy access on the power system quality. The results show that the matching degree of new energy output power and load power has a significant impact on the voltage imbalance, power factor and voltage deviation of the power system, while the access location has a smaller impact on the above indicators

Space Precession Target Classification Based on Radar High-Resolution Range Profiles

Precession is a common micromotion form of space targets, introducing additional micro-Doppler (m-D) modulation into the radar echo. Effective classification of space targets is of great significance for further micromotion parameter extraction and identification. Feature extraction is a key step during the classification process, largely influencing the final classification performance. This paper presents two methods for classifying different types of space precession targets from the HRRPs. We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target. Experimental results demonstrate that the support vector machine (SVM) using histograms of oriented gradient (HOG) features achieves a good result, whereas the deep convolutional neural network (DCNN) obtains a higher classification accuracy. DCNN combines the feature extractor and the classifier itself to automatically mine the high-level signatures of HRRPs through a training process. Besides, the efficiency of the two classification processes are compared using the same dataset

ESPRIT-Like Two-Dimensional DOA Estimation for Monostatic MIMO Radar with Electromagnetic Vector Received Sensors under the Condition of Gain and Phase Uncertainties and Mutual Coupling

In this paper, we focus on the problem of two-dimensional direction of arrival (2D-DOA) estimation for monostatic MIMO Radar with electromagnetic vector received sensors (MIMO-EMVSs) under the condition of gain and phase uncertainties (GPU) and mutual coupling (MC). GPU would spoil the invariance property of the EMVSs in MIMO-EMVSs, thus the effective ESPRIT algorithm unable to be used directly. Then we put forward a C-SPD ESPRIT-like algorithm. It estimates the 2D-DOA and polarization station angle (PSA) based on the instrumental sensors method (ISM). The C-SPD ESPRIT-like algorithm can obtain good angle estimation accuracy without knowing the GPU. Furthermore, it can be applied to arbitrary array configuration and has low complexity for avoiding the angle searching procedure. When MC and GPU exist together between the elements of EMVSs, in order to make our algorithm feasible, we derive a class of separated electromagnetic vector receiver and give the S-SPD ESPRIT-like algorithm. It can solve the problem of GPU and MC efficiently. And the array configuration can be arbitrary. The effectiveness of our proposed algorithms is verified by the simulation result