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We have proposed the Adaptive Sub-Band Compound (A-SBC) method, which uses subbands of different frequencies to improve the resolution by adaptive compounding. A-SBC effectively suppresses the sidelobe level by mainly utilizing the principle that the phases of subbands of different frequencies are inconsistent off-axis. There are many specific methods that can realize A-SBC. In this study, we propose three additional methods based on a previous application of A-SBC to multi-angle plane-wave beamforming. We evaluate these four methods through simulation and human carotid artery experiments.

Optimizing antenna arrays is essential for achieving efficient beamforming with very low sidelobe level (SLL) where adopting tapered window functions is one of the straightforward efficient techniques for achieving this goal. Recently, two-dimensional (2D) beamforming has been extensively required for many applications; therefore, this paper proposes two extrapolation techniques applied to one-dimensional (1D) tapered functions to efficiently feed 2D antenna arrays using cross-linear and adaptive radial tapering techniques. The first proposed 2D cross-linear tapering technique determines the 2D tapering coefficients by Hadamard multiplication of two right-angled grids of repeated 1D functions, while the second proposed adaptive radial tapering technique locates the antenna element in the 2D array in terms of its radial distance with respect to the array center, then converts this distance to an element index in a virtual 1D tapering window to determine the element weighting value. The adaptive radial tapering technique is optimized for achieving the minimum SLLs. The two proposed techniques are analyzed and discussed, where it is found that the adaptive radial tapering provides deeper SLLs compared to the cross-linear tapering technique. The two extrapolation techniques are examined for four window functions including triangular (Bartlett), Hamming, cosine-square, and Blackman windows, and the simulation results show that for extrapolating the Blackman window using adaptive radial tapering, a −50 dB SLL can be achieved which is independent on the array size, while cross-linear tapering provides −35 dB and −41 dB SLLs for 16×16 and 32×32 antenna arrays, respectively.

Antenna arrays have become an essential part of most wireless communications systems. In this paper, the unwanted sidelobes in the symmetric linear array power pattern are reduced efficiently by utilizing a faster simultaneous sidelobes processing algorithm, which generates nulling sub-beams that are adapted to control and maintain steep convergence toward lower sidelobe levels. The proposed algorithm is performed using adaptive damping and heuristic factors which result in learning curve perturbations during the first few loops of the reduction process and is followed by a very steep convergence profile towards deep sidelobe levels. The numerical results show that, using the proposed adaptive sidelobes simultaneous reduction algorithm, a maximum sidelobe level of −50 dB can be achieved after only 10 iteration loops (especially for very large antenna arrays formed by 256 elements, wherein the processing time is reduced to approximately 25% of that required by the conventional fixed damping factor case). On the other hand, the generated array weights can be applied to practical linear antenna arrays under mutual coupling effects, which have shown very similar results to the radiation pattern of the isotropic antenna elements with very deep sidelobe levels and the same beamwidth.

Advanced waveform design schemes have been widely employed for radar and sonar remote sensing analysis such as target detection and separation, where significant range sidelobe is a main factor that limits the improvement of analysis performance. As an extensional type of Golay complementary waveforms, complementary sets are a waveform design scenario of concern that shows more diversity in the design of transmission order, and results in a different distribution of range sidelobes. This work proposes an oversampled generalized Prouhet–Thue–Morse (OGPTM) method for the transmitted signal design of complementary sets, with comprehensive analysis to the influence on the sidelobe distribution. Based on this idea and our previous work, we further put forward a pointwise multiplication processor (PMuP) to integrate two delay-Doppler maps of oversampled complementary sets, which achieve much better sidelobe suppression performance on high-speed target detection with range migration.

In this paper, an efficient sidelobe levels (SLL) reduction and spatial filtering algorithm is proposed for linear one-dimensional arrays. In this algorithm, the sidelobes are beamspace processed simultaneously based on its orientation symmetry to achieve very deep SLL at much lower processing time compared with recent techniques and is denoted by the sidelobes simultaneous reduction (SSR) algorithm. The beamwidth increase due to SLL reduction is found to be the same as that resulting from the Dolph-Chebyshev window but at considerably lower average SLL at the same interelement spacing distance. The convergence of the proposed SSR algorithm can be controlled to guarantee the achievement of the required SLL with almost steady state behavior. On the other hand, the proposed SSR algorithm has been examined for spatial selective sidelobe filtering and has shown the capability to effectively reduce any angular range of the radiation pattern effectively. In addition, the controlled convergence capability of the proposed SSR algorithm allows it to work at any interelement spacing distance, which ranges from tenths to a few wavelength distances, and still provide very low SLL.

Discrete Fourier transform (DFT) is a common analysis tool in digital signal processing. This transform is well studied and its shortcomings are known as well. Various window functions (e.g., Hanning, Blackman, Kaiser) are often used to reduce sidelobes and to spread the spectrum. In this paper, we introduce a transformation that allows removing the sidelobes of the Fourier transform and increasing the resolution of the DFT without changing the time sample. The proposed method is based on signal phase analysis. We give the comparison of the proposed approach with known methods based on window functions. The advantages and disadvantages of the proposed technique are explicitly shown. We also give a set of examples illustrating the application of our technique in some practical applications, including engine vibration analysis and a short-range radar system.

A metasurface-loaded low-scattering strut has been proposed to reduce the radiation side lobe levels (SLLs) of front-fed reflector antennas. The H-shaped metasurface unit cells help to reduce the radar cross section (RCS) of metallic feed-support struts and finally reduce the SLLs. Compared to the metallic strut, the designed low-scattering strut reduced the forward RCS by 8.8 dB and the total RCS by 4.2 dB at 2.78 GHz. The technique is implemented in a 2 m S-band reflector antenna, and the SLL of the reflector antenna with the low-scattering struts is reduced by 4.0 dB compared to the reflector antenna with metallic struts. The reason for the significant SLL reduction in the reflector antenna utilizing low-scattering struts is explained. The simulation shows that, at 2.78 GHz, the SLL is lower than -21.8 dB. The result proves that the low-scattering strut design can be used to reduce the SLL on the front-fed reflector antenna.

Long-term visualization of the dynamic interactions between intracellular structures throughout the three-dimensional space of whole live cells is essential to better understand their functions, but this task remains challenging due to the limitations of existing three-dimensional fluorescence microscopy techniques, such as an insufficient axial resolution, low volumetric imaging rate and photobleaching. Here, we present the combination of a progressive deep-learning super-resolution strategy with a double-ring-modulated selective plane illumination microscopy design capable of visualizing the dynamics of intracellular structures in live cells for hours at an isotropic spatial resolution of roughly 100 nm in three dimensions at speeds up to roughly 17 Hz. Using this approach, we reveal the complex spatial relationships and interactions between endoplasmic reticulum (ER) and mitochondria throughout live cells, providing new insights into ER-mediated mitochondrial division. We also examined the motion of Drp1 oligomers involved in mitochondrial fission and revealed the dynamic interactions between Drp1 and mitochondria in three dimensions. Combining a double-ring modulated SPIM with reduced side lobes and a sectionalized deep-learning based super-resolution algorithm enables fast, high-resolution, volumetric imaging of organelle interactions and dynamics in live cells.

This study proposes a physical mechanism-guided joint optimization framework to address the problems of low modeling efficiency, insufficient motion compensation accuracy, and feature inversion reliance on experience in inverse synthetic aperture radar (ISAR) imaging under complex electromagnetic environments. Through the geometric decomposition and equivalent edge current coupling method driven by the scattering mechanism, combined with the Krylov order reduction model and hybrid acceleration architecture, high-precision modeling in the Ka band (boundary field error ≤ 1.05%) and a 12.6-fold increase in computational efficiency are achieved. At the imaging algorithm level, a time-frequency sparse joint imaging (Time-Frequency Compressed Sensing ISAR, TF-CSISAR) method is proposed to achieve 2.2 cm ultra-high resolution imaging and improve the sidelobe suppression capability to -28.3 dB, which is significantly better than the traditional RD algorithm (sidelobe level -18 dB).

Programmable metasurfaces have great potential for the implementation of low-complexity and low-cost phased arrays. Due to the difficulty of multiple-bit phase control, conventional programmable metasurfaces suffer a relatively high sidelobe level (SLL). In this manuscript, a time modulation strategy is introduced in the 1-bit transmissive programmable metasurface for reducing the SLLs of the generated patterns. After the periodic time modulation, harmonics are generated in each reconfigurable unit and the phase of the first-order harmonic can be dynamically controlled by applying different modulation sequences onto the corresponding unit. Through the high-speed modulation of the real-time periodic coding sequences on the metasurface by the programmable bias circuit, the equivalent phase shift accuracy to each metasurface unit can be improved to 6-bit and thus the SLLs of the metasurface could be reduced remarkably. The proposed time-modulated strategy is verified both numerically and experimentally with a transmissive programmable metasurface, which obtains an aperture efficiency over 34% and reduced SLLs of about -20 dB. The proposed design could offer a novel approach of a programmable metasurface framework for radar detection and secure communication applications.