A fresh phase unwrapping algorithm based on iterated unscented Kalman filter is proposed to estimate unambiguous unwrapped phase of interferometric fringes. This method is the result of combining an iterated unscented Kalman filter with a robust phase gradient estimator based on amended matrix pencil model, and an efficient quality-guided strategy based on heap sort. The iterated unscented Kalman filter that is one of the most robust methods under the Bayesian theorem frame in non-linear signal processing so far, is applied to perform simultaneously noise suppression and phase unwrapping of interferometric fringes for the first time, which can simplify the complexity and the difficulty of pre-filtering procedure followed by phase unwrapping procedure, and even can remove the pre-filtering procedure. The robust phase gradient estimator is used to efficiently and accurately obtain phase gradient information from interferometric fringes, which is needed for the iterated unscented Kalman filtering phase unwrapping model. The efficient quality-guided strategy is able to ensure that the proposed method fast unwraps wrapped pixels along the path from the high-quality area to the low-quality area of wrapped phase images, which can greatly improve the efficiency of phase unwrapping. Results obtained from synthetic data and real data show that the proposed method can obtain better solutions with an acceptable time consumption, with respect to some of the most used algorithms.

A broadband circularly polarized metasurface antenna with low radar cross-section (RCS) is proposed. Four metasurface elements are arranged orthogonally in a 2×2 array and fed with a 90° phase difference to achieve circular polarization radiation. Each metasurface element is a non-uniform sub-array of 4×4 metallic patches. Attributed to the non-uniform property of the metasurface element, two characteristic modes with different resonant frequencies but with similar surface current distributions are formed. By optimizing the geometric parameters of the non-uniform element, the two modes are merged with each other, resulting in bandwidth (BW) broadening of the proposed antenna. Simulated and measured results show that the designed antenna has a −10-dB impedance BW of 49.60%, 3-dB axial ratio BW of 33.13%, and peak gain of 13.17 dBic. Moreover, the RCS reduction is higher than 6 dB in the entire operation frequency band. Additionally, the antenna has a low profile of 0.08λ (λ is the free-space wavelength at an operation frequency of 8.25 GHz).

This paper introduces a chessboard metasurface comprising four orthogonally arranged elements designed to create a broadband circularly polarized (CP) antenna with ultra-wideband radar cross-section reduction (RCSR). Each element is a bilayer structure consisting of a polarization rotation surface (PRS) and a phase-controlled surface (PCS). The PCS effectively modulates the phases of co-polarized and cross-polarized reflective waves, resulting in a considerable bandwidth expansion for polarization conversion. To achieve CP radiation, the chessboard metasurface is fed sequentially with rotational input, with each output port featuring a double-V-shaped slot coupled by a fork-shaped microstrip. This feeding approach significantly suppresses scattering modes within the working band, thereby enhancing in-band RCSR. Additionally, eight micro-slots are further etched onto the ground plane to achieve a full in-band RCSR exceeding 10 dB. Simulation results demonstrate an impedance bandwidth of 54.5% (6-10.5 GHz) and a 3 dB axial ratio bandwidth of 32.9% (6.6-9.2 GHz), with a peak gain of 11.9 dBic. Besides, the antenna exhibits 10 dB out-of-band and full in-band RCSR in the ultra-wideband range from 6.6 to 22.4 GHz. Experimental results corroborate the findings of the simulations.

This paper presents an enhanced phase unwrapping algorithm by combining an unscented Kalman filter, an enhanced local phase gradient estimator based on an amended matrix pencil model, and a path-following strategy. This technology is able to accurately unwrap seriously noisy wrapped phase images by applying the unscented Kalman filter to simultaneously perform noise suppression and phase unwrapping along the path from the high-quality region to the low-quality region of the wrapped phase images. Results obtained with synthetic data and real data validate the effectiveness of the proposed method and show improved performance of this new algorithm with respect to some of the most used algorithms.

This paper presents an efficient and robust phase unwrapping algorithm which combines an unscented Kalman filter (UKF) with a strategy of quantizing a paths-guided map and a pixel classification strategy based on phase quality information. The advantages of the proposed method depend on the following contributions: (1) the strategy of quantizing the paths-guided map can accelerate the process of searching unwrapping paths and greatly reducing time consumption on the unwrapping procedure; (2) the pixel classification strategy proposed by this paper can reduce the error propagation effect by decreasing the amounts of pixels with equal quantized paths-guided value in the process of unwrapping; and (3) the unscented Kalman filter enables simultaneous filtering and unwrapping without the information loss caused by linearization of a nonlinear model. In addition, a new paths-guided map derived from a phase quality map is inserted into the strategy of quantizing the paths-guided map to provide a more robust path of unwrapping, and then ensures better unwrapping results. Results obtained from synthetic data and real data show that the proposed method can efficiently obtain better solutions with respect to some of the most used algorithms.

This paper proposes a new phase unwrapping (PU) algorithm based on an unscented information filter for interferometric fringes. The proposed algorithm is the result of combining an unscented information filter with a Levenberg–Marquardt method, a robust phase gradient estimator called the amended matrix pencil model, and an efficient quality-guided strategy based on heapsort. The unscented information filter, a new type of filter that has recently been well applied to traditional nonlinear object tracking fields, is introduced to estimate the unambiguous unwrapped phase of wrapped phase images for the first time, to the best of our knowledge. First, a recursive PU procedure based on an unscented information filter is established to perform PU and noise filtering at the same time by combining the unscented information filter and the amended matrix pencil model, where the amended matrix pencil model is applied to acquire phase gradient information needed for the recursive PU procedure. Second, the above recursive PU procedure is further optimized to improve the accuracy of the phase estimate by inserting the Levenberg–Marquardt method. This is also the first time that the Levenberg–Marquardt method is combined with the unscented information filter for the unwrapping of interferometric fringes, to the best of our knowledge. Finally, the efficient quality-guided strategy based on heapsort is used to efficiently route the path of the unwrapping procedure and to guide the proposed method to efficiently unwrap wrapped pixels along the path from the high-reliance region to the low-reliance region of the wrapped fringes. Results obtained with synthetic data and real data show more acceptable solutions with the proposed method, compared to some of the most used algorithms.