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Low elevation estimation, which has attracted wide attention due to the presence of specular multipath, is essential for tracking radars. Frequency agility not only has the advantage of strong anti-interference ability, but also can enhance the performance of tracking radars. A frequency-agile refined maximum likelihood (RML) algorithm based on optimal fusion is proposed. The algorithm constructs an optimization problem, which minimizes the mean square error (MSE) of angle estimation. Thereby, the optimal weight at different frequency points is obtained for fusing the angle estimation. Through theoretical analysis and simulation, the frequency-agile RML algorithm based on optimal fusion can improve the accuracy of angle estimation effectively.

Multicenter case series has reported patients with hepatic injury following COVID-19 vaccination, which raised concern for the possibility of vaccine-induced liver dysfunction. We aimed to assess the impact of COVID-19 vaccination on liver function of pregnant women, who may be uniquely susceptible to vaccine-induced liver dysfunction. We conducted a retrospective cohort study at a tertiary hospital in Shanghai, China. Vaccine administration was obtained from the electronic vaccination record. Serum levels of alanine transaminase (ALT), aspartate transaminase (AST), total bile acid (TBA) and total bilirubin (TBIL) in early pregnancy were determined by enzymatic methods. Among the 7745 included pregnant women, 3832 (49.5%) received at least two doses of an inactivated vaccine. COVID-19 vaccination was significantly associated with higher levels of maternal serum TBA. Compared with unvaccinated pregnant women, the mean TBA levels increased by 0.17 μmol/L (β = 0.17, 95% CI, 0.04, 0.31) for women who had been vaccinated within 3 months before the date of conception. Moreover, COVID-19 vaccination was significantly associated with an increased risk of maternal hyperbileacidemia. The risk of hyperbileacidemia increased by 113% (RR = 2.13; 95% CI, 1.17-3.87) for pregnant women who had been vaccinated within 3 months before conception compared with unvaccinated pregnant women. However, when the interval from complete vaccination to conception was prolonged to more than 3 months, COVID-19 vaccination was not associated with serum TBA levels or maternal hyperbileacidemia. Our findings suggest that vaccination with inactivated COVID-19 vaccines more than 3 months before conception have no detrimental effects on maternal liver function in early pregnancy.

In this paper, a space-time adaptive processing (STAP) method is proposed for the airborne radar with the array amplitude-phase error considered, which is based on atomic norm minimization (ANM). In the conventional ANM-based STAP method, the influence of the array amplitude-phase error is not considered and restrained, which inevitably causes performance deterioration. To solve this problem, the array amplitude-phase error is firstly estimated. Then, by pre-estimating the array amplitude-phase error information, a modified ANM model is built, in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix (CCM) to improve the estimation accuracy of the CCM. To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error, the clutter sparsity is analyzed in this paper. Meanwhile, simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method. Moreover, the measured data is used to verify the effectiveness of the proposed method.

The airborne conformai array (CFA) radar's clutter ridges are range-modulated, which result in a bias in the estimation of the clutter covariance matrix (CCM) of the cell under test (CUT), further, reducing the clutter suppression performance of the airborne CFA radar. The clutter ridges can be effectively compensated by the space-time separation interpolation (STS-INT) method, which costs less computation than the space-time interpolation (STINT) method, but the performance of interpolation algorithms is seriously affected by the short-range clutter, especially near the platform height. Location distributions of CFA are free, which yields serious impact that range spaces of steering vector matrices are non-orthogonal complement and even no longer disjoint. Further, a new method is proposed that the short-range clutter is pre-processed by oblique projection with the intersected range spaces (OPIRS), and then clutter data after being pre-processed are compensated to the desired range bin through the STSINT method. The OPIRS also has good compatibility and can be used in combination with many existing methods. At the same time, oblique projectors of OPIRS can be obtained in advance, so the proposed method has almost the same computational load as the traditional compensation method. In addition, the proposed method can perform well when the channel error exists. Computer simulation results verify the effectiveness of the proposed method.

The versatile video coding (VVC) is the latest video coding standard, which uses a Multi-Type Tree (MTT) coding structure. Compared with existing video coding standards, this structure can flexibly split coding blocks according to the complex texture features of the image. As MTT structure introduces binary tree (BT) and ternary tree (TT) splitting, it will lead to a sharp increase in computational complexity. In the paper, a fast Coding Unit (CU) size decision method for intra prediction of VVC is proposed, which can significantly reduce the calculation in the intra encoding of VVC. The proposed method consists of two steps: 1) determine whether CU is divided and 2) select the best CU splitting mode. In the intra prediction process, the CU texture complexity is firstly calculated, which judges whether the CU is divided into sub-CUs. Then, the unnecessary splitting mode candidates are discarded according to the relationship between the texture direction and the CU splitting mode. The experimental results show that our proposed fast CU partition method reduces about 48.58% the computational complexity, while the BDBR only increases by 0.91%.

For collocated Multiple-Input Multiple-Output (MIMO) radar, we investigate the target detection problem in Gaussian clutter with an unknown but random covariance matrix. An inverse complex Wishart distribution is chosen as prior knowledge for the random covariance matrix. We propose two detectors in the Bayesian framework based on the criteria of the Generalized Likelihood Ratio Test. The two main advantages of the proposed Bayesian detectors are as follows: (1) no training data are required; and (2) a prior knowledge about the clutter is incorporated in the decision rules to achieve detection performance gains. Numerical simulations show that the proposed Bayesian detectors outperform the current commonly used non-Bayesian counterparts, particularly when the sample number of the transmitted waveform is small. In addition, the performance of the proposed detector will decline in parameter mismatched situation.

For the first time, the preparation and characterization of a novel anode material Li2NiFe2O4 are reported in this work. The preparation of Li2NiFe2O4 is conducted under the air conditions by using a subsection calcination method. The influence of annealing periods on the properties of the resultant materials is thoroughly explored. The characteristics of the materials are mainly examined by X-ray diffraction (XRD), scanning electron microscopy (SEM), cyclic voltammetry (CV), galvanostatic charge-discharge tests and electrochemical impedance spectroscopy (EIS). The results of the XRD patterns effectively demonstrate the formation of crystalline Li2NiFe2O4, and the SEM images indicate that particles with octahedron crystal morphology are prepared and the 9 h-annealed sample has the smallest particle size among all the prepared samples. The results of electrochemical measurements reveal that 9 h-calcined sample delivers a high specific capacity of 203 mAh g−1 after 20 cycles at a current density of 100 mA g−1. The successful preparation of Li2NiFe2O4 is believed to be able to trigger the research work concerning the novel group of Li2MFe2O4 materials.

A novel finding, that the “burned” graphene has a significant role in determining the morphology of the resultant LiNiO2 nanoparticles prepared under the air conditions, was reported in this work. Briefly, prior to the calcination-preparation of LiNiO2, a series of graphene with various weight contents (0.5 wt %, 1 wt %, 1.5 wt % and 2 wt %) were added in the starting materials of LiNiO2, and then followed by a subsection calcination method under the air conditions. The obtained samples were thoroughly characterized by using X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM) and Fourier transform infrared spectroscopy (FTIR). It was found that when the “burned” content of graphene is below 2 wt %, LiNiO2 particles with an average size ranging from about 100 to 500 nm were demonstrated to have regular crystal structures. Results obtained from the electrochemical measurements effectively indicated that the largest value of initial discharge capacity and the highest cycling stability were exhibited by the 1.5 wt % graphene-burned LiNiO2 cathode material as compared to other graphene-burned samples. Interestingly, when employing graphite other than graphene as the carbon source, LiNiO2 particles with well defined octahedron structure were prepared by the same process, which is beneficial to the development of micro-devices. A novel concept, that burned graphene has a significant role in determining the morphology as well as the electrochemical properties of resulting samples, is presented in this work.

For the first time, it was found that dry-grinding the mixture containing technical grade PdO and multi-walled carbon nanotubes (MWCNTs) can generate a catalyst with ultrahigh electrocatalytic activity for ethanol oxidation reaction (EOR). The as-prepared catalysts were denoted as PdO/MWCNTs. For a comparison, the graphene and graphite supported PdO samples were also prepared using the same process, leading to the formation of PdO/graphene and PdO/graphite catalysts respectively. The structural details, the morphologies as well as the particle sizes of the prepared catalysts are mainly characterized by X-ray diffraction (XRD) and transmission electron microscopy (TEM). Although no novel diffraction peaks were observed in the XRD patterns of the resulting samples, the morphologies of the samples after the dry-grinding process have changed greatly as compared to the starting materials of PdO. The results also indicate that the PdO/MWCNTs catalysts show the smallest particle sizes among all the prepared catalysts. The catalytic activities of the prepared PdO/MWCNTs catalysts towards EOR are examined by electrochemical measurements, and the results obtained from cyclic voltammery (CV) test demonstrated that the PdO/MWCNTs catalyst delivers a forward peak current density for EOR of 5029 mA mg −1 at a scan rate of 50 mV s −1 , which is about 2.1 times higher than the reported value (2361 mA mg −1 ) obtained on the (Pd/C) catalyst. After detailed analysis, it is thought that the easier hydrogen evolution process on the PdO/MWCNTs catalyst is regarded as the main reason for its excellent electrochemical performance as compared to other catalysts, i.e., PdO/graphene and PdO/graphite. Most interestingly, the as-prepared catalyst has electrocatalytic activity for both methanol oxidation reaction and formic acid oxidation, which were also explored approximately in this preliminary work.

For low-angle targets, the performance of altitude measurement is affected by multipath phenomenon. Generally, the response at the receiver is contributed by the echoes of target and its image. Such sparsity of signals in the elevation direction provides a foundation for parameter estimation based on compressive sensing with parameterized dictionary. As the dictionary atoms are multi-parameter, it may increase the dimension of the parameterized dictionary. This may increase the cost of computation and storage violently. Aiming at this problem, a novel compressive sensing based algorithm, combined with alternative optimization and dictionary refinement, is proposed in this paper. The algorithm is based on the criterion of maximizing the correlation coefficient of target signal component and the atoms of a parameterized dictionary, where the dictionary grids can be iteratively refined to estimate the parameters more precisely. Numerical results based on simulated data and real data show the efficiency of the proposed algorithm.

In this paper, a new three-stage beamformer is proposed for reception of coherent signals with the assumption that the directions-of-arrivals (DOA's) of the uncorrelated interferers have been estimated a priori. First, the estimated DOA's of the uncorrelated interferers are used to construct a transformation matrix. Secondly, the composite vector of the coherent sources is estimated based on the transformation matrix. Finally, using the estimated composite vector and the array correlation matrix, adaptive beamforming is performed. Experimental results show that the proposed beamformer almost achieves the optimum performance and rapidly converges. Finally, we also discuss how to counteract DOA error by high-order constraints.

The eigenspace-based linearly constrained minimum variance beamformer (ELCMVB) is presented; it combines the linearly constrained minimum variance beamformer (LCMVB) with the eigenspace-based beamformer. The ELCMVB projects the presumed steering vector of the LCMVB onto the signal subspace, the projected steering vector is then used to calculate the weight vector for beamforming with the linearly constrained minimum variance technique. Compared to the generalized eigenspace-based beamformer (GEIB), the ELCMVB removes the computation of the modified signal subspace. It can thus avoid numerical instability. The theoretical analysis also indicates that the ELCMVB performance is not affected by the positions of the null constraints. Computer simulation results are presented and demonstrate the merits of the ELCMVB.

For the purpose of improving DOA estimation performance, we propose a new simplified temporal-spatial maximum likelihood algorithm. Instead of using discrete Fourier transform (DFT) filters, the proposed algorithm uses special Doppler filters to process the received data according to the signal's Doppler frequency. The processed data are then used by the maximum likelihood algorithm to estimate DOA. Because the special Doppler filters can greatly reduce the influences between signals, the proposed algorithm works significantly better than the simplified temporal-spatial maximum likelihood algorithm. Computer simulation results are presented and demonstrate the merits of the proposed algorithm.

This paper deals with adaptive interference cancellation in the presence of array imperfections and beam pointing error. A new interference canceler with robust capabilities is proposed. This interference canceler first obtains the modified interference subspace (MIS) by employing the covariance differencing technique, then it obtains the projection vector of the steering vector of the desired signal onto the orthogonal complementary space of the MIS as the weight vector. Compared to the eigenanalysis interference canceler (EIC), the proposed interference canceler is not only robust to the array complex gain errors, but also to beam pointing error. The performance of this interference canceler is examined via simulations.

This paper deals with adaptive array beamforming in the presence of the pointing error. A modified algorithm with robust capabilities for the eigenspace based adaptive beamforming is presented. By utilizing the signal-plus-interference subspace obtained with the eigenstructure of the correlation matrix, we calibrate the presumed steering vector in the ESB algorithm. The calibrated steering vector is then used for the ESB adaptive beamforming. Several computer simulation examples are presented that demonstrate the advantages of the proposed algorithm over the conventional ESB algorithm.