Method for differential phase delay resolution of phase referencing VLBI technique and its experimental verification

The phase referencing Very Long Baseline Interferometry (VLBI) technique is a newly developed tool to measure the angular position of a deep space exploration probe in the plane-of-the-sky. Through alternating observations between the probe and a nearby reference radio source, their accurate relative angular separation can be obtained from the radio images generated by this technique. To meet the requirements of the current orbit determination software, differential delay should be firstly derived from those radio images. A method to resolve the differential phase delay from the phase referencing VLBI technique is proposed in this paper, and as well the mathematical model for differential phase ambiguity resolution is established. This method is verified with practical measurement data from the Chang’E-3 mission. The differential phase delay between the Chang’E-3 lander and rover was derived from the phase referencing VLBI measurements, and was then imported into the Shanghai astronomical observatory Orbit Determination Program (SODP) to calculate the position of the rover relative to the lander on the lunar surface. The results are consistent with those acquired directly from radio images, indicating that the differential phase ambiguity has been correctly resolved. The proposed method can be used to promote applications of the phase referencing VLBI technique in future lunar or deep space explorations, and more accurate orbit determination becomes promising.

Non-circular signal DOA estimation based on coprime array MIMO radar

Aiming at the problems of low degree of freedom, small array aperture, and phase ambiguity in traditional coprime array direction-of-arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed. Firstly, this method combines the coprime array and the MIMO radar to form transmitter and receiver array. Secondly, the array is expanded using the non-circular signal characteristics to reconstruct the received signal matrix. Then the dimensionality reduction is performed. The two-dimensional spectral peak search is converted into an optimization problem, and the optimization of the two-dimensional MUSIC algorithm is reconstructed using constraints, and a cost function is constructed to solve the problem. In addition, use the power series of the noise eigenvalues to correct the noise subspace to further improve the accuracy of the algorithm. Finally, the problem of no phase ambiguity in the method in this article is derived. Simulation experiments show that the method in this article can effectively avoid phase ambiguity, greatly improve the degree of freedom, and expand the array aperture. Compared with the traditional MUSIC algorithm and the mutual prime array MUSIC algorithm, it has better resolution and DOA estimation accuracy.

Holographic quantum singularity

In this study, we addressed the influence of quantum singularity on the topological state. The quantum singularity creates the defect in the momentum space ubiquitously and leads to the phase transition for the topological material. The kinetic equation reveals that the defect generates an anomaly without the characteristic energy scale. In the holographic model, the three-dimensional dislocations map into the gravitational bulk as domain walls extending along the AdS radial direction from the boundary. The creation/annihilation of the domain wall causes the quantum phase transition by ’t Hooft anomaly generation and is controlled by the gauge field. In other words, the phase transition is realized by the anomaly inflow. This ’t Hooft anomaly is caused by a phase ambiguity of the ground state resulting from the singularity in parameter space. This singularity gives the basis for the boundary’s topological state with the Berry connection. ’t Hooft anomaly’s renormalization group invariance shows that the total Berry flux is conserved in the UV layer to the IR layer. Phase transition entails domain wall constitution, which generates the entropy from the non-universal form or quantum entropy correction.

Coherent Target Direction-of-Arrival Estimation for Coprime Arrays: From Spatial Smoothing Perspective

In this paper, we investigate the issue of direction-of-arrival (DOA) estimation of multiple signals in coprime arrays. An algorithm based on multiple signal classification (MUSIC) and forward and backward spatial smoothing (FBSS) is used for DOA estimation of this signal caused by multipath and interference. The large distance between adjacent elements of each subarray in the coprime arrays will bring phase ambiguity issues. According to the feature of the coprime number, the ambiguity problem can be eliminated. The correct DOA estimation can be obtained by searching for the common peak of the spatial spectrum and finding the overlapping peaks in the MUSIC spectrum of the two subarrays. For the rank deficit problem caused by the coherent signal, the FBSS algorithm is used for signal preprocessing before the MUSIC algorithm. Theoretical analysis and simulation results show that the algorithm can effectively solve the rank deficiency and phase ambiguity problems caused by coherent signals and sparse arrays in the coprime arrays.

Squint Model InISAR Imaging Method Based on Reference Interferometric Phase Construction and Coordinate Transformation

The imaging quality of InISAR under squint geometry can be greatly degraded due to the serious interferometric phase ambiguity (InPhaA) and thus result in image distortion problems. Aiming to solve these problems, a three-dimensional InISAR (3D ISAR) imaging method based on reference InPhas construction and coordinate transformation is presented in this paper. First, the target’s 3D coarse location is obtained by the cross-correlation algorithm, and a relatively stronger scatterer is taken as the reference scatterer to construct the reference interferometric phases (InPhas) so as to remove the InPhaA and restore the real InPhas. The selected scatterer needs not to be exactly in the center of the coarsely located target. Then, the image distortion is corrected by coordinate transformation, and finally the 3D coordinates of the target can be accurately estimated. Both simulation and practical experiment results validate the effectiveness of the method.

Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array

A partial dictionary based direction of arrival (DOA) estimation method which addresses the off-grid problem and exploits combined coprime and nested array (CCNA) is proposed. Compared to general coprime array, CCNA yields two sparse coprime subarrays in the coarray domain by adding a third subarray in the physical-array domain. To ensure the DOA estimation performance, the subarray with larger aperture is chosen, and the cyclic phase ambiguity caused by the sparse subarray allows partial dictionary covering arbitrary cycle to represent the whole atoms, and then, the off-grid sparse reconstruction method is developed to amend the grid mismatch. After the sparse recovery and off-grid compensation, ambiguous DOA estimations can be eliminated by substituting the estimations into the whole virtual array. Multiple simulations verify that the proposed algorithm outperforms the other state-of-the-art methods in terms of DOA estimation accuracy and angular resolution.

Non-circular Signal DOA Estimation based on Coprime Array MIMO Radar

Aiming at the problems of low degree of freedom, small array aperture, phase ambiguity and other problems of traditional coprime array direction of arrival estimation methods, a non-circular signal DOA estimation method based on expanded coprime array MIMO radar is proposed. Firstly, this method combines the coprime array and the MIMO radar to form transmitter and receiver array. Secondly, the array is expanded using the non-circular signal characteristics to reconstruct the received signal matrix. Then the dimensionality reduction is performed. The two-dimensional spectral peak search is converted into an optimization problem, and the optimization of the two-dimensional MUSIC algorithm is reconstructed using constraints, and a cost function is constructed to solve the problem. In addition, using the power series of the noise eigenvalues to correct the noise subspace to further improve the accuracy of the algorithm. Finally, the problem of no phase ambiguity in the method in this article is derived. Simulation experiments show that the method in this article can effectively avoid phase ambiguity, greatly improve the degree of freedom, and expand the array aperture. Compared with the traditional MUSIC algorithm and the mutual prime array MUSIC algorithm, it has better resolution and DOA estimation accuracy.