Nonlinear Frequency Offset Beam Design for FDA-MIMO Radar.

The beam pattern of frequency diversity array (FDA) radar has a range-angle two-dimensional degree of freedom, which makes it possible to distinguish different targets from the same angle and brings a new approach to anti-jamming of radars. However, the beam pattern of conventional linearly frequency-biased FDA radar is range-angle-coupled and time-varying. The method of adding nonlinear frequency bias among the array elements of the FDA array has been shown to eliminate this coupling property while still allowing for better beam performance of the emitted beam. In this paper, we obtain a decoupled and time-invariant beam direction map using the FDA-multi-input-multi-output (FDA-MIMO) radar scheme and then obtain a sharp pencil-shaped main sphere beam pattern with range-angle dependence using a linear frequency offset scheme weighted by a Chebyshev window. Finally, the anti-interference performance of the proposed method is verified in an anti-interference experiment.

Multi-Target Tracking AA Fusion Method for Asynchronous Multi-Sensor Networks.

Aiming at the problem of asynchronous multi-target tracking, this paper studies the AA fusion optimization problem of multi-sensor networks. Firstly, each sensor node runs a PHD filter, and the measurement information obtained from different sensor nodes in the fusion interval is flood communicated into composite measurement information. The Gaussian component representing the same target is associated with a subset by distance correlation. Then, the Bayesian Cramér-Rao Lower Bound of the asynchronous multi-target-tracking error, including radar node selection, is derived by combining the composite measurement information representing the same target. On this basis, a multi-sensor-network-optimization model for asynchronous multi-target tracking is established. That is, to minimize the asynchronous multi-target-tracking error as the optimization objective, the adaptive optimization design of the selection method of the sensor nodes in the sensor network is carried out, and the sequential quadratic programming (SQP) algorithm is used to select the most suitable sensor nodes for the AA fusion of the Gaussian components representing the same target. The simulation results show that compared with the existing algorithms, the proposed algorithm can effectively improve the asynchronous multi-target-tracking accuracy of multi-sensor networks.

Joint Estimation Method of DOD and DOA of Bistatic Coprime Array MIMO Radar for Coherent Targets Based on Low-Rank Matrix Reconstruction.

Based on low-rank matrix reconstruction theory, this paper proposes a joint DOD and DOA estimation method for coherent targets with bistatic coprime array MIMO radar. Unlike the conventional vectorization, the proposed method processed the coprime array with virtual sensor interpolation, which obtained a uniform linear array to generate the covariance matrix. Then, we reconstructed the Toeplitz matrix and established a matrix optimization recovery model according to the kernel norm minimization theory. Finally, the reduced dimension multiple signal classification algorithm was applied to estimate the angle of the coherent targets, with which the automatic pairing of DOD and DOA could be realized. With the same number of physical sensors, the proposed method expanded the array aperture effectively, so that the degree of freedom and angular resolution could be improved significantly for coherent signals. However, the effectiveness of the method was largely limited by the signal-to-noise ratio. The superiority and effectiveness of the method were proved using simulation experiments.

Meter Wave Polarization-Sensitive Array Radar for Height Measurement Based on MUSIC Algorithm.

Obtaining good measurement performance with meter wave radar has always been a difficult problem. Especially in low-elevation areas, the multipath effect seriously affects the measurement accuracy of meter wave radar. The generalized multiple signal classification (MUSIC) algorithm is a well-known measurement method that dose not require decorrelation processing. The polarization-sensitive array (PSA) has the advantage of polarization diversity, and the polarization smoothing generalized MUSIC algorithm demonstrates good angle estimation performance in low-elevation areas when based on a PSA. Nevertheless, its computational complexity is still high, and the estimation accuracy and discrimination success probability need to be further improved. In addition, it cannot estimate the polarization parameters. To solve these problems, a polarization synthesis steering vector MUSIC algorithm is proposed in this paper. First, the MUSIC algorithm is used to obtain the spatial spectrum of the meter wave PSA. Second, the received data are properly deformed and classified. The Rayleigh-Ritz method is used to decompose the angle to realize the decoupling of polarization and the direction of the arrival angle. Third, the geometric relationship and prior information of the direct wave and the reflected wave are used to continue dimension reduction processing to reduce the computational complexity of the algorithm. Finally, the geometric relationship is used to obtain the target height measurement results. Extensive simulation results illustrate the accuracy and superiority of the proposed algorithm.

Coherent Signal DOA Estimation for MIMO Radar under Composite Background of Strong Interference and Non-Uniform Noise.

To address the problems of low accuracy and low robustness of the conventional algorithm in estimating the direction of arrival (DOA) of coherent signals against a composite background of strong interference and non-uniform noise, in this paper, a coherent signal DOA estimation algorithm based on fixed projection blocking is proposed in conjunction with a multi-input multi-output (MIMO) radar. The covariance matrix of the received signal is first decomposed by eigenvalues, and a fixed projection matrix orthogonal to the interference guidance vector is constructed as the interference blocking matrix. Then, the received array signal is pre-processed to re-form the covariance matrix, and this matrix is rendered decoherent through a Toeplitz reconstruction. Finally, the reconstructed covariance matrix is estimated by DOA using the propagation operator algorithm to reduce the complexity. The simulation verifies that the proposed algorithm has a better robustness and higher accuracy than conventional algorithms for the DOA estimation of coherent signals in composite backgrounds.

The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise.

Due to the discontinuity of ocean waves and mountains, there are often multipath propagation effects and obvious pulse characteristics in low-altitude detection. If the conventional direction of arrival (DOA) estimation method is directly used for direction finding, it will lead to a large error. In view of serious misalignment in the DOA estimation of multipath signals under the background of impulse noise, a DOA estimation method based on spatial difference and a modified projection subspace algorithm is proposed in this paper. Firstly, the covariance matrix of the received data vector is used for spatial difference to eliminate the multipath effects of low-altitude targets. Secondly, the modified projection matrix is constructed using the signal source estimated with the least squares criterion and then used for modifying the covariance matrix, thus eliminating the cross-covariance matrices that affect the estimation accuracy. Finally, the modified covariance matrix is used for the DOA estimation of targets. Simulations show that the proposed algorithm achieves a higher accuracy in the DOA estimation of low-altitude targets than conventional algorithms under two common impulse noise models, without requiring prior knowledge of impulse noise.

Raman and Density Functional Theory Studies of Li2Mo4O13 Structures in Crystalline and Molten States.

The Li2Mo4O13 melt structure and its Raman spectral characteristics are the key for establishing the composition-structure relationship of lithium molybdate melts. In this work, Raman spectroscopy, factor group analysis, and density functional theory (DFT) were applied to investigate the structural and spectral details of the H-Li2Mo4O13 crystal and a Li2Mo4O13 melt. Factor group analysis shows that the crystal has 171 vibrational modes (84Ag + 87Au), including three acoustic modes (3Au), six librational modes (2Ag + 4Au), 21 translational modes (7Ag + 14Au), and 141 internal modes (75Ag + 66Au). All of the Ag modes are Raman-active and were assigned by the DFT method. The Li2Mo4O13 melt structure was deduced from the H-Li2Mo4O13 crystal structure and demonstrated by the DFT method. The results show that the Li2Mo4O13 melt is made up of Li+ ions and Mo4O132- groups, each of which is formed by four corner-sharing MoO3Ø/MoO2Ø2 tetrahedra (Ø = bridging oxygen). The melt has three acoustic modes (3A) and 54 optical modes (54A). All of the optical modes are Raman-active and were accurately assigned by the DFT method.

Investigation on the Structure of a LiB3O5-Li2Mo3O10 High-Temperature Solution for Understanding the Li2Mo3O10 Flux Behavior.

LiB3O5 is the most widely used nonlinear optical crystal. Li2Mo3O10 (a nominal composition) is a typical flux used to produce large-sized and high-quality LiB3O5 crystals. The structure of the LiB3O5-Li2Mo3O10 high-temperature solution is essential to understanding the flux behavior of Li2Mo3O10 but still remains unclear. In this work, high-temperature Raman spectroscopy combined with density functional theory (DFT) was applied to study the LiB3O5-Li2Mo3O10 solution structure. Raman spectra of a LiB3O5-Li4Mo5O17-Li2Mo4O13 polycrystalline mixture were recorded at different temperatures until the mixture melted completely. The solution structure was deduced from the spectral changes and verified by DFT calculations. When the mixture began to melt, its molybdate component first changed into the Li2Mo3O10 melt; meanwhile, the complicated molybdate groups existing in the crystalline state transformed into Mo3O102- groups, which are formed by three corner-sharing MoO3Ø-/MoO2Ø2 (Ø = bridging oxygen atom) tetrahedra. When LiB3O5 dissolved in the Li2Mo3O10 melt, the crystal structure collapsed into polymeric chains of [B3O4Ø2-]n. Its basic structural unit, the B3O4Ø2- ring, coordinated with the Mo3O102- group to form a MoO3·B3O4Ø2- complex and a Mo2O72- group. On the basis of the LiB3O5-Li2Mo3O10 solution structure, we discuss the LiB3O5 crystal growth mechanism and the compositional dependence of the solution viscosity.

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.

Raman Spectral and Density Functional Theory Analyses of the CsB3O5 Melt Structure.

Melt structures are essential to understand a variety of crystal growth phenomena of alkali-metal triborates, but have not been fully explored. In this work, Raman spectroscopy, coupled with the density functional theory (DFT) method, has been used to solve the CsB3O5 (CBO) melt structure. When the CBO crystal melts, the extra-ring B4-Ø bonds (the B-Ø bonds of BØ4 groups, Ø = bridging oxygen atom) that connect two B3O3Ø4 rings (the basic boron-oxygen unit in the CBO crystal structure) break. As a result, the three-dimensional boron-oxygen network collapses to unique polymer-like [B3O4Ø2]n chains. On the basis of the optimized [B3O4Ø2]n chain model, the CBO melt Raman spectrum was calculated by the DFT method for the first time and the calculated results confirm that the [B3O4Ø2]n chain is the primary species in the CBO melt. These results also demonstrate the capability of the combined Raman spectral and DFT method for analyzing borate melt structures.

Raman spectral study of metal-cytosine complexes: a density functional theoretical (DFT) approach.

The fluctuation of surface-enhanced Raman scattering (SERS) spectra has been an obstacle to the analysis of the adsorbate on the metal surface. In this paper, we aim at using the density functional theory (DFT) to study the fluctuant Raman spectra of the cytosine molecule which interacts with a coinage metal atom or cation via N1 and N3 sites. The results show that the adsorption site strongly influences the Raman spectral property of cytosine molecule, especially the relative intensity of some bands. In addition, the SERS spectra of cytosine which is adsorbed on the gold, silver, and copper electrodes are measured, and the possible orientation and adsorption site of the cytosine molecule adsorbed on metal electrodes surface are proposed with the help of DFT simulations.