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In the realm of bearings-only target tracking, the pseudo-linear Kalman filter (PLKF) has garnered significant interest, due to its low computational demands and robust stability. However, the interrelation between the measurement matrix and noise introduces bias into the PLKF's target state estimation. To address this issue, we introduce a fusion unbiased PLKF (FUBKF) algorithm. This algorithm initiates with a global pseudo-linear treatment of the measurement equation, subsequently isolating the noise within the measurement matrix. By employing the unscented Kalman filter (UKF), the algorithm achieves precise estimation of the measurement matrix, thereby mitigating the estimation error stemming from the correlation between the measurement matrix and noise. Simulation outcomes demonstrate that the proposed algorithm substantially enhances tracking accuracy and sustains high stability in both 2D and 3D bearings-only target tracking scenarios, encompassing both non-maneuvering and maneuvering conditions. [ABSTRACT FROM AUTHOR]

An integral domain R is said to be locally G-Dedekind if the Gorenstein global dimension of R is at most one for each maximal ideal . In this paper, we show that an integral domain R is not necessarily a G-Prüfer even if R is a locally G-Dedekind domain, which gives a negative answer to the question raised by the first author. It follows that the localization of the G-Prüfer domain differs from the classical case of the Prüfer domain. We also study coherent locally G-Dedekind domains, called almost G-Dedekind domains. The almost G-Dedekind domains need not be integrally closed and fill the gap between the G-Dedekind domains and the G-Prüfer domains. Various examples are provided to illustrate the new concept. [ABSTRACT FROM AUTHOR]

The concept of Gorenstein Krull domains can be viewed as a Gorenstein analogue of Krull domains, which are not necessarily integrally closed. This allows us to study those domains from the point view of Gorenstein homological algebra. By the so-called w-operation, we prove that an integral domain is Gorenstein Krull if and only if for any nonzero nonunit, the Gorenstein global dimension of its w-factor ring is zero. [ABSTRACT FROM AUTHOR]

Synthetic-aperture radar (SAR) can work in all weather conditions and at all times, and satellite-borne radar has the characteristics of short revisiting period and large imaging width. Therefore, satellite-borne synthetic-aperture radar has been widely deployed, and the SAR images have been widely used in geographic mapping, radar interpretation, ship detection, and other fields. Satellite-borne synthetic-aperture radar is also susceptible to various types of intentional or unintentional interference during the imaging process, and because the interference is a direct wave, its power is much stronger than the wave reflected by targets. As a common interference pattern, radio-frequency interference widely exists in various satellite-borne synthetic-aperture radars, which seriously deteriorates SAR image quality. In order to solve the above problems, this paper proposes a feature decomposition network to suppress interference based on regularization optimization. The contributions of this work are as follows: 1. By analyzing the performance limitations of the existing methods, this work proposes a novel regularization method for radio-frequency interference suppression tasks. From the perspective of data distribution histograms and residual components, the proposed method eliminates the variable components introduced by common regularization, greatly reduces the difficulty of data mapping, and significantly improves its robustness and performance. 2. This work proposes a feature decomposition network, where the feature decomposition module contains two parts; one part only represents the interference signal, and the other part only represents the radar signal. The neurons representing the interference signal are discarded, and the neurons representing the radar signal are used as input for the subsequent network. A cosine similarity constraint is used to separate the interference from the network as much as possible. Finally, this method is validated on the MiniSAR dataset and Sentinel-1A dataset. [ABSTRACT FROM AUTHOR]

With respect to the detection and recognition of an Artificial Modulation Target (AMT) with different modulated types, the state-of-the-art methods generally suffer the deficiencies of overfitting and insufficient generalization of existing neural network solutions. To address these problems, this paper proposes a multi-scale amplitude-phase feature discrimination method for AMTs in SAR images. First, a multi-type modulated AMT Dataset is generated (AMT Detection and Modulation Type Recognition Dataset, ADMTR Dataset), wherein the factors of jamming position, jamming-to-signal ratio (JSR), and the modulated parameter are considered to enhance the generalization. Second, a Multi-Input Multi-Output Fusion Wavelet Neural Network (MIMOFWTNN) is established, which not only uses the amplitude information of the scene but also adequately makes use of the phase and high-frequency information. This empowers us to detect the AMT in a higher dimensional feature space such that the type recognition can be implemented with more certainty. Analysis and discussions conducted on comparison experiments and ablation experiments demonstrate that the proposed network can achieve an average accuracy of 96.96% on the cross-validation set and a correct rate of 99.0% on the completely independent test set, which outperforms the compared methods. [ABSTRACT FROM AUTHOR]

Reconfigurable metasurfaces have shown unprecedented capabilities in controlling electromagnetic (EM) waves in recent years and play an essential role in information manipulation. However, most research on reconfigurable metasurfaces is limited to planar rigid structures, with only one control function and suitable for specific single polarization. Achieving simultaneous control of phase, polarization, and frequency in the conformal structure has significant practical implications in many applications, but remains obviously challenging. In this paper, a flexible multifunctional time‐varying phase‐modulated metasurface (MTPM) with orthogonal polarization control is proposed for conformal applications to manipulate the spectrum distribution. It enables time encoding capability in controlling the phase characteristics of x‐ and y‐polarized EM waves individually by switching the bias voltage of the PIN diode in two directions. Discrete harmonic spectrum and continuous Doppler frequency shifts are implemented separately on two orthogonal polarizations by applying different time coding sequences. As a practical application, a conformal MTPM for radar feature transformation is explored. Multiple discrete false targets and defocusing phenomena can be realized respectively for x‐ and y‐polarized waves. Both simulated and measured results verify the validity of the proposed method and prototype. [ABSTRACT FROM AUTHOR]

In radar electronic countermeasures, as the difference between jamming and targets continues to decrease, traditional methods that are implemented based on classical features are currently unable to meet the requirements of jamming detection. Compared with classical features such as texture, scale, and shape, shadow has better discernability and separability. In this paper, target shadow is investigated and applied to detect jamming in Synthetic Aperture Radar (SAR) images, and a SAR false target identification method based on shadow features is proposed. First, a difference image is generated by change detection, which can extract the shadow region in single-time SAR images. Then, a three-step differentiation condition is proposed, which can distinguish false targets from real targets. Simulated experimental results show that the proposed method can effectively extract the shadow region in SAR images and accurately distinguishreal and false targets. Furthermore, the potential of shadow in SAR image interpretation and electronic countermeasures is also demonstrated. [ABSTRACT FROM AUTHOR]

Aiming at the inherent defect of single jammer against synthetic aperture radar (SAR) system with ground moving target indication (GMTI), this defect is usually solved by using the idea of dual-jammer cooperative jamming. However, the jamming methods of dual-jammer cooperative jamming in the current public literature need to reconnoitre some key parameters of SAR-GMTI system in advance, such as the carrier platform speed, the nearest slant distance between the jammer and the carrier platform, and the self-position of the two jammers. The acquisition of these parameters usually requires complex reconnaissance equipment. To solve this problem, an implementation method of dual-jammer system against SAR-GMTI based on integration of reconnaissance and jamming is proposed. This method uses the layout of jammers and receivers as well as the time difference of arrival (TDOA) information between receivers to effectively solve the problem of reconnaissance key parameters of complex equipment, and simplifies the configuration of jamming system. The results show that, considering the measurement error of TDOA and the spacing error of two antennas in SAR-GMTI system, the proposed method can also generate false moving targets with controllable velocity and azimuth position. Theoretical analysis and simulation results verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

A representative general polarimetric model-based decomposition framework was proposed by Chen et al., which implements a simultaneous full-parameter inversion by using complete polarimetric information and solves several limitations in previous decomposition methods. However, there are still shortcomings in Chen's work. Firstly, only the real part of the parameter β in the generalized surface scattering model is considered. Secondly, inappropriate initial input values may lead to local optima in the nonlinear least squares optimization algorithm. Thirdly, the volume scattering component is underestimated in the volume scattering-dominated scene, but overestimated in buildings with large orientation (LOB) areas. Finally, nonlinear optimization is time-consuming computationally. To overcome those issues, an improved generalized polarimetric model-based decomposition method is proposed in this paper. The imaginary part of the parameter β is incorporated into the decomposition framework of the proposed method. Ingeniously utilizing the internal relationship in the generic equations composed of coherent matrix elements, the model parameters can be inversed by simplifying the nonlinear equations to linear equations. Therefore, compared with Chen's method, the proposed method does not rely on the initial input values, and improves the computational efficiency. In addition, a hierarchical decomposition scheme is presented to solve the problem of underestimation or overestimation of volume scattering component mentioned above. The performance and advantages of this method are evaluated with L-band and C-band polarimetric synthetic aperture radar (PolSAR) data sets. Comparison studies are carried out with other model-based decomposition methods, demonstrating that the proposed method can further improve decomposition performance, especially in LOB areas. [ABSTRACT FROM AUTHOR]