Time-division broadcast positioning systems offer advantages such as low implementation complexity and support for an unlimited number of passive receivers. However, most existing joint localization and synchronization (JLAS) methods for moving terminals rely on the assumption of pre-synchronized base stations (BSs), which restricts their flexibility and scalability in ad-hoc or large-scale deployments. This paper proposes a Fully Asynchronous JLAS (FA-JLAS) framework that operates without any prior inter-BS synchronization. We derive a new set of composite observables, the Symmetric Asynchronous TDOA (SA-TDOA) and the Inter-Frame Differencing Observable (IFDO), from timestamp measurements shared among BSs. These observables are designed to analytically eliminate nuisance parameters, including clock offsets and static non-line-of-sight (NLOS) delays. Based on these observables, a MAP-based estimation framework is developed that incorporates motion priors and jointly estimates the user equipment’s (UE) kinematic state and network synchronization parameters, thereby improving robustness in challenging 3D environments. Theoretical performance bounds are derived using the Cramér-Rao Lower Bound (CRLB), and simulation results demonstrate that the FA-JLAS framework achieves near-CRLB accuracy across various scenarios.

The electromagnetic (EM) inverse scattering problems (ISPs) are characterized by nonlinearity, presenting a challenge in achieving a satisfactory reconstruction of the relative permittivity of strong scatterers. Joint inversion has been demonstrated as an effective approach for improving the quality of EM inversion through the integration of acoustic inversion. However, when solving the ISPs associated with complex structured scatterers and multiple scatterers, the accuracy of the EM parameters reconstructed by previous joint inversion methods is inadequate. Aim to solving this problem, this paper proposes a new inversion method, which is based on framework of the subspace-based optimization method (SOM). The proposed method adopts the joint inversion architecture and incorporates the image segmentation technique. The acoustic data is processed before being employed to construct structural similarity constraints for EM inversion, rather than being directly utilized as in previous methods. And in this new approach, Pyramid Scene Parsing Network (PSPNet) is employed to extracting the boundary information of the targets from high-resolution acoustic images. Subsequently, this information is leveraged to formulate a more effective objective function or a better initial contrast for EM inversion. Compared with previous joint inversion method, this new imaging segmentation-based inversion method (ISIM) of EM and acoustic data offers advantages in inversion accuracy and computational speed by making more efficient use of acoustic information. Additionally, in scenarios involving complex structural scatterers or multiple scatterers, ISIM is capable of achieving more precise results. The effectiveness and advantages of ISIM are validated through several numerical examples.

Tsunami bring great disasters to human beings. The focus of the research is to predict the feasibility of tsunami early warning by microwave radar scheme. In this article, the electromagnetic (EM) scattering characteristics of the sea surface from the calm sea to the submarine earthquake are studied. Based on the high-order Boussinesq wave model combined with the up and down movement of the two submarine plates, the 3-D geometric propagation model of the tsunami sea surface is established. The geometric structure and propagation characteristics of the sea surface under different earthquake magnitudes are analyzed. The higher the earthquake magnitude, the more obvious the effect on the sea wave height and sea surface slope. Second, the influence of wind velocity disturbance on sea surface roughness caused by tsunami is deduced. The EM scattering distribution of tsunami-affected sea surface is solved by combining the wind disturbance theory with the EM scattering method based on the surface element model. In addition, the distribution of EM scattering coefficients of tsunami sea surface under different radar parameters, background wind speed, and earthquake magnitude are also discussed, providing an important theoretical basis for the rapid warning of tsunami by microwave radar.

The electromagnetic (EM) inverse scattering problems (ISPs) exhibit strong nonlinearity, making it a challenge to reconstruct relative permittivity of strong scatterers with high quality. Joint inversion can leverage the satisfactory solution obtained from acoustic inversion to mitigates the impact of strong nonlinearity on EM inversion. However, how to improve the precision of reconstructing the internal electrical parameter distribution through this kind of joint inversion approach is still a challenge. Aim to improve the quality of reconstruction, a new joint inversion method based on the framework of the subspace-based optimization method (SOM) is proposed in this paper. This new method utilizes the Pearson correlation coefficient (PCC) to construct structural similarity constraints, thereby enhancing the linear correlation between EM and acoustic parameters. In inversion process, all data obtained from acoustic inversion can offer effective constraints. In order to improve convergence speed and stability of the proposed method, a constraint which is consisted of CGF is induced in the object function. And by utilizing the results of the results of acoustic inversion, the inversion domain can be further refined, giving rise to better computational efficiency. With these treatments, the proposed method has better performance in both accuracy and efficiency. The effectiveness and advantages of the proposed method is validated through several numerical examples.

The GNSS/INS integrated navigation system is widely used in intelligent vehicles. Due to the vulnerability of GNSS and the low accuracy of low-cost inertial devices, the performance of dead reckoning during GNSS outages is of great concern. The non-holonomic constraint (NHC) is a widely used method to improve dead reckoning performance, but it ignores the sideslip effect caused by tire deformation, which leads to performance degradation. The conventional vehicle dynamics model can achieve higher accuracy by modeling tire sideslip effects; however, its parameters are often complex and challenging to obtain. This work proposes a novel wheel velocity predictor (WVP) based on the vehicle dynamics model, which models tire sideslip effects while having concise and easy-to-estimate parameters. Based on this model, an integrated navigation system is proposed, which can adaptively estimate WVP parameters when GNSS is available and use the additional information from trained WVP to improve navigation performance during GNSS outages. Notably, the proposed system utilizes a more accurate model than conventional NHC while avoiding requiring additional sensors or complex prior vehicle dynamics model parameters. Field experiments have shown that the proposed scheme can accurately estimate the tire sideslip angle in real-time and significantly improve dead reckoning performance compared with the NHC-based method. Furthermore, as part of the WVP parameters, the inertial measurement unit mounting angles can be estimated even with a non-straight driving trajectory. Compared with the NHC-based method, which requires a straight driving trajectory to converge, the application limitation is significantly relaxed.

Under high dynamic and high temperature environments, the error model of the inertial measurement unit (IMU), which is the key sensor of the autonomous driving system, will be affected by temperature and input angular velocity. But the traditional error model of the IMU has the limitation that it cannot compensate with high precision under complex conditions. In this paper, the error model of the ADI16505 IMU is systematically observed at different temperatures and input angular velocity by using a three-axis turntable with a temperature chamber. The measured data objectively reflects the change of the IMU error model with temperature under dynamic angular velocity input. In this paper, an error model considering both temperature and input angular velocity is proposed. An error model was established with the correlation between temperature and angular velocity by the least square method and polynomial fitting. Finally, collecting data under the typical conditions of high temperature and low input angular velocity and compensating with this model. The average error observed on the six axes was reduced by more than 90%, and the feasibility of the optimized error model was verified.

In this letter, a new scheme based on contraction integral equation (CIE) method is proposed to solve the highly nonlinear inverse scattering problems with noise disturbance. By controlling the weight factor in the new scheme through multirounds optimization, the imaging quality of the inversion algorithm is improved while ensuring that the inversion has a better convergence without any significant increase in computational costs. This means that a new degree of freedom in determining the performance of the inversion is proposed and can be controlled by the researcher. This letter discusses the significance of the weight factor and its impact on the performance of the algorithm. Besides, the guidelines for choosing an appropriate weight factor is introduced. Finally, the effectiveness and versatility of the new scheme is verified by numerical analysis.

This article presents a mechanism model of synthetic aperture radar (SAR) remote sensing imaging of submarine topography in shallow areas. According to the shallow water effect and complex geographical factors, a 3-D geometric model of multiscale wave is generated by combining sea spectrum separation and phase superposition methods. It has the advantage of reflecting the random fluctuation characteristics of waves and the refraction phenomenon influenced by submarine topography. In addition, the modulation relationship among submarine topography, tidal current, and sea surface microroughness is established. This constitutes hydrodynamic modulation. The facet-based hybrid method that combines the geometry optics (GO) and the integral equation method (IEM) is adopted to solve the electromagnetic (EM) scattering of super electrically large sea surface. This contains tilt modulation. The effectiveness of the proposed model is demonstrated through the comparisons with the measured results. The influence of the parameters of radar, sea state, water depth, and tidal current direction on the scattering intensity of sea surface is studied as well. It is revealed that the shallower the water depth, the more significant the hydrodynamic and tilt effect. In addition, the velocity bunching (VB) modulation is a special modulation method in SAR imaging. According to the simulated results, the contributions of tilt, hydrodynamic, and VB modulation in SAR imaging mechanism are compared. The VB is the main factor, hydrodynamic is second, and tilt is the least.

Due to the strong nonlinearity, it is always a challenge to reconstruct strong scatterers with high contrasts and/or large dimensions. This article proposes an iterative domain decomposition technique (IDDT) based on the framework of the subspace-based optimization method (SOM) to solve highly nonlinear inverse scattering problems (ISPs). This method takes advantage of the fact that the reduction of unknowns can reduce the nonlinearity of ISPs and different parts of scatterers have different effects on scattered fields. In the inversion procedure, the domain of scatterers (DoS) is obtained by refining the domain of interests (DoI) first. Then, the DoS is divided into two subdomains according to their contributions to scattered fields: the dominant subdomain and the subordinate subdomain. The induced current of the subordinate subdomain is approximated by its deterministic part. Therefore, only the induced current of the dominant subdomain needs to be reconstructed, greatly reducing the dimensions of the solution domain. Then the properties of the entire DoS are retrieved with the properties of the dominant subdomain as initial guesses. This technique can be used repeatedly to improve the reconstruction quality. Compared with the original SOM, this method can reduce the nonlinearity of ISPs and reconstruct stronger scatterers with better reconstruction qualities and less computation loads. The feasibility and efficiency of IDDT-SOM are discussed from the perspective of the relative distribution of induced current by numerical and experimental examples.

Based on composite rough surface and stochastic multiscale models, an improved two-scale model (TSM) is proposed. Different from the classical TSM, the proposed method adopts the integral equation method (IEM) to replace the small perturbation method (SPM) for calculating the contribution from small-scale roughness. Kirchhoff approximation (KA) is still kept in the model to calculate the contribution from large-scale roughness. Because the IEM has wider application range than the SPM, the proposed model exhibits a higher accuracy and has a wider application range in terms of sea surface roughness compared with the classical TSM. Usually, the classical TSM is sensitive to the cutoff wavenumber. The proposed model adopts an adaptive cutoff wavenumber instead of choosing a cutoff wavenumber in the classical TSM. The effectiveness of the proposed model is demonstrated through comparisons with the simulation results of multilevel fast multipole algorithm (MLFMA) and the measured results. Different roughness at different frequencies is analyzed as well.

For target detection in Gaussian noise with unknown covariance matrix, usually sufficient training data are needed to form a nonsingular estimate of the noise covariance matrix. However sufficient training data could not be satisfied in practice. Aiming to design a detector with small training data size, this letter proposes a reduced-dimension detector by incorporating the persymmetric structure of received data. Based on the persymmetric structure, a reduced-dimension approach of subspace transformation-based detector is adopted. Then, the criterion of the generalized likelihood ratio test is used to design the detector. The proposed detector is shown to possess the constant false alarm rate property with respect to noise covariance matrix. Compared with existing detectors, such as conventional polarization-space-time generalized likelihood ratio detector, persymmetric polarization-space-time generalized likelihood ratio detector and subspace transformation-based detector, simulation results demonstrate that the proposed one has better detection performance, especially in the circumstance of limited training data.

Because of strong nonlinearity, it is always a challenge to acquire fine resolution reconstruction results for electric strong scatterers with high contrasts using electromagnetic (EM) data. Many electric strong scatterers have weak nonlinearity in acoustic inversion. To make full use of the advantages of acoustic inversion, two joint inversion methods based on the structural constraints to reconstruct electric strong scatterers using EM and acoustic data are proposed in this article. These two methods utilize the framework of the subspace-based optimization method (SOM). In the inversion process, one of the methods utilizes a cross-gradient function to link the EM and the acoustic inversions, enforcing the structural similarity between the permittivity and the sound velocity. The second method is to utilize the reconstruction result of acoustic data as initial structural information for the EM inversion process. Compared with conventional separate SOM, these two methods achieve finer EM reconstruction for electric strong scatterers. Both structure and contrast values are well reconstructed. The efficiency and the robustness of the methods are validated through numerical experiments.

In this letter, a diagonal approximation has been introduced in the framework of subspace-based optimization method (SOM), for reducing computational complexity. Due to this approximation, the operator which relates the electric field and equivalent current becomes a diagonal one, instead of the nonlinear one in full-wave inversion. Consequently, the proposed method is named as diagonal SOM (DSOM). Compared with the original SOM, DSOM has a more simplified objective function with much less computational cost. DSOM can be applied for solving inverse scattering problems involving not only isotropic objects, but also uniaxial anisotropic objects, which is demonstrated by numerical examples. Furthermore, DSOM provides reconstruction results that are comparable in quality to the ones obtained using SOM, but with much less computation load.

Due to the nonlinear property of large uniaxial anisotropic scatterers, many iterative optimization methods have a high risk of being trapped in local minima. In this paper, a frequency-hopping subspace-based optimization method (SOM) is proposed to reconstruct the relative permittivity distribution of 2-D large uniaxial anisotropic scatterers with transverse electrical (TE) illumination. This hybrid method utilizes the results obtained at lower frequency to provide good initial guesses for higher frequency reconstruction, which reduces the occurrence of local minima for the inversion at the higher frequency. For lower frequency, it can only obtain coarse resolution image although it is unable to show the details of the scatterers. However, this coarse image provides a priori information for the reconstruction at higher frequencies to get finer resolution. Numerical examples demonstrate that the proposed hybrid method can effectively rebuild large uniaxial anisotropic scatterers (six wavelengths) with higher stability compared with conventional SOM that uses only single-frequency data.

Positioning 3-D targets buried in layered medium with electromagnetic waves has widespread applications, such as the detection of land mines. Most of the current electromagnetic inverse methods need to know the preknowledge of the dielectric properties for layered background medium, in order to accurately reconstruct concealed targets. However, this condition is hardly satisfied in real problems. In this letter, an electromagnetic inverse scattering series method (EISSM) is developed and derived for positioning 3-D targets buried in two-layered medium. The prominent advantage of the proposed method is that it does not need any prior information about the dielectric properties of the layered medium. The position error predicted by the EISSM is analyzed and discussed. Compared with the commonly used time-reversal-mirror technique, numerical simulations show that the EISSM is capable of positioning the target buried in two-layer medium with less error.

At low grazing angles (LGA), sophisticated electromagnetic scattering of sea surfaces may give rise to complicated surface-current distribution. Therefore, for the multilevel fast multipole algorithm (MLFMA) with the Rao-Wilton-Glisson basis function, the sea scatterer must be meshed fine enough to ensure the precision of the scattering at LGA, which brings huge computational costs. The higher order hierarchical Legendre vector basis functions can bring a great reduction of the unknowns and sparsification of the impedance matrix. The MLFMA with higher order hierarchical Legendre basis functions is applied in the electromagnetic-scattering approach of 3-D breaking water wave crests at LGA for the first time. In addition, an adaptive-order technique is also introduced for the first time in describing the currents which can achieve accurate results and maximally reduce the computational costs from some case analysis. It has been investigated in analyzing the vertically (VV) and horizontally (HH) polarized scattering of profiles of the LONGTANK breaking waves. "Sea-spike" phenomenon has been demonstrated at LGA.

The microwave backscattering from a three-dimensional (3-D) target approximating the rough crest of a gently spilling water wave at low grazing angle illumination has been numerically examined. The target surfaces were synthesized from the direct two-dimensional (2-D) measurement of the time evolution of the upwave-downwave cross-section of a wave-tank breaker. The reference scattering was found using the multilevel fast multipole algorithm implemented with impedance boundary conditions and resistive surface loading to suppress nonphysical edge diffraction. The scattering was compared with the predictions of the two-scale model and a synthesis of the 3-D backscattering from individual 2-D calculations. Specular reflection from a bulge feature that appeared on the crest prior to breaking dominated the backscattering at both polarizations, overwhelming even the strong vertical polarization Bragg scattering that appeared in the corresponding scattering from the individual 2-D profiles used to synthesize the 3-D target. The scattering from the surface including the bulge could be accurately modeled using a coherent addition of the scattering from the 2-D profiles. The two-scale model performed poorly whenever there are steep sections on the surface that provide significant quasi-specular back-reflection. Accuracy improved when the specular points were eliminated and the dominant scattering roughness was fully illuminated, but was still sensitive to the surface-roughness scale-separation threshold used in its application.

In previous work, an extension to geometrical optics (EGO) that allows the application to reflecting surfaces that have radii of curvature less than the electromagnetic was used to model the microwave backscattering from numerically simulated breaking water wave crests. The same approach has now been applied to plunging wave crest profiles that were directly measured in a wave tank, and the modeled backscattering compared to reference scattering found using moment-method based numerical techniques. When considering the directly measured two-dimensional cross-sections of the breaker, EGO successfully predicts the reduction in the vertically polarized backscatter (VV) observed in the reference scattering through the interference of reflections from the breaker jet itself and the cavity under the jet. A similar reduction is not seen at horizontal polarization (HH), giving a large HH-to-VV ratio at certain times in the breaking process. A three-dimensional scattering profile was synthesized from the 2-D measurements. The EGO-modeled interference of reflections from several different points on the 3-D wave yields a deep null in the VV backscattering that matches the null observed in the reference scattering. Again no interference null is observed in the HH scattering.

The low-grazing-angle (LGA) backscattering from one-dimensionally rough surface profiles approximating breaking water waves with roughened front faces has been numerically examined. The added front-face roughness approximates that expected from wind generation. The reference "exact" backscattering was found using a numerical technique based on the moment method. A model-based approach to predict the backscattering was also implemented. In this, the crest scattering was found directly using the moment method, the multipath scattering was modeled using physical optics, and the distributed-surface scattering from the small-scale roughness was found from the two-scale model. The calculations show that the roughness adds incoherent components to both the vertically (VV) and horizontally (HH) polarized scattering cross sections. At VV, this is due to the random scattering from the small-scale roughness, while at HH it results from random changes in the multipath interference due to the large-scale roughness. As the mechanisms for the incoherent scattering are independent, it is difficult to predict the magnitude of the HH-to-VV backscattering ratio that will occur with specific realizations of the roughness from the underlying breaking-wave shape alone, particularly with large rms roughness added. Overall, the model-based calculations give a good prediction of both the coherent and incoherent scattering coefficients.