Robust autofocusing propagation in turbulence

Turbulence in complex environments such as the atmosphere and biological media has always been a great challenge to the application of beam propagation in optical communication, optical trapping and manipulation. To overcome this challenge, this study comprehensively investigates the robust propagation of traditional Gaussian and autofocusing beams in turbulent environments. In order to select stable beams that exhibit high intensity and high field gradient at the focal position in complex environments, Kolmogorov turbulence theory is used to simulate the propagation of beams in atmospheric turbulence based on the multi-phase screen method. We systematically analyze the intensity fluctuations, the variation of the coherence factor and the change in the scintillation index with propagation distance. The analysis reveals that the intensity fluctuations of autofocusing beams are significantly smaller than those of Gaussian beams, and the coherence of autofocusing beams is better than that of Gaussian beams under turbulence. Moreover, autofocusing beams exhibit less oscillation than Gaussian beams, indicating that autofocusing beams propagate in complex environments with less distortion and intensity fluctuation. Overall, this work clearly demonstrates that autofocusing beams exhibit higher stability in propagation compared with Gaussian beams, showing great promise for applications such as optical trapping and manipulation in complex environments.

PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

AUTOFOCUSING OF SYNTHETIC HRR RADAR USING STEPPED FREQUENCY WAVEFORMS

Most operating radar systems don′t have sufficient frequency bandwidth to produce high range resolution(HRR) profile of a target. But we can use stepped frequency waveform in a narrow band coherent radar to obtain the HRR profile of a target. For moving targets which are of great importance in practical radar usage, autofocusing,i.e. phase correction, is a necessary and critical step of the synthetic HRR processing. The purpose of autofocusing is to remove the radial motion effect of the target from radar echoes, and only reserve the stepped frequency effect which is the basis of synthetic HRR capability. We investigate two autofocusing approaches for synthetic HRR radars using stepped frequency waveform in this paper. The first is motion fitting method. This method depends on a certain parametric model, and is computationally expensive. Then we propose the iterative dominant scatterer method. It is robust, non parametric and simple in computation in comparison with the motion fitting method. Experimental results based on data acquired by using a metallised scale model B 52 in a microwave anechoic chamber reveal the validity and effectiveness of the method.

IMPROVEMENT OF PHASE GRADIENT AUTOFOCUS ALGORITHM

The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne SAR. But PGA has two shortcomings: first, it has a worse estimation property for fast changing phase error; second, there exists a section of linear phase in the phase error estimated by this algorithm. This paper introduces the idea of rank one phase estimate (ROPE) autofocus technique, and improves PGA. The improved PGA(IPGA) can successfully overcome both these shortcomings of PGA.

Research on Wavelet Based Autofocus Evaluation in Micro-vision

This paper presents the construction of two kinds of focusing measure operators defined in wavelet domain. One mechanism is that the Discrete Wavelet Transform （DWT） coefficients in high frequency subbands of in-focused image are higher than those of defocused one. The other mechanism is that the autocorrelation of an in-focused image filtered through Continuous Wavelet Transform （CWT） gives a sharper profile than blurred one does. Wavelet base, scaling factor and form to get the sum of high frequency energy are the key factors in constructing the operator. Two new focus measure operators are defined through the autofocusing experiments on the micro-vision system of the workcell for micro-aligmnent. The performances of two operators can be quantificationally evaluated through the comparison with two spatial domain operators--Brenner Function （BF） and Squared Gradient Function （SGF）. The focus resolution of the optimized DWT-based operators is 14% higher than that of BF and its computational cost is 52% approximately lower than BF＇s. The focus resolution of the optimized CWT-based operators is 41% lower than that of SGF whereas its computational cost is approximately 36% lower than SGF＇s. It shows that the wavelet based autofocus measure functions can be practically used in micro-vision applications.

A Simple Model for On-Sensor Phase-Detection Autofocusing Algorithm

A simple model of the phase-detection autofocus device based on the partially masked sensor pixels is described. The cross-correlation function of the half-images registered by the masked pixels is proposed as a focus function. It is shown that—in such setting—focusing is equivalent to searching of the cross-correlation function maximum. Application of stochastic approximation algorithms to unimodal and non-unimodal focus functions is shortly discussed.

Implementation of Autofocus in Alignment System for Layered Imprint Fabrication

Autofocus method based on the analysis of image content information is investigated to reduce the alignment error resulting from mark positioning uncertainty due to defocus in microstructure layered fabrication process based on multilevel imprint lithography. The applicability of several autofocus functions to the alignment mark images is evaluated concerning their uniformity, sharpness near peak, reliability and measure computation efficiency and the most suitable one based on power spectrum in frequency domain (PSFD) is adopted. To solve the problem of too much computation amount needed in PSFD algorithm, the strategy of interested region detection and effective image reconstruction is proposed and the algorithm efficiency is improved. The test results show that the computation time is reduced from 0.316 s to 0.023 s under the same conditions while the other merits of the function are preserved, which indicates that the modified algorithm can meet the mark image autofocusing requirements in response time, accuracy and robustness. The alignment error due to defocus which is about 0.5 μm indicated by experimental results can be reduced or eliminated by the autofocusing implementation.

Modified Approach to PGA Phase Averaging for ISAR Autofocus

A new approach to phase averaging in phase gradient algorithm (PGA) is proposed, which is based on the fundamental fact that the information of translational phase error is widely contained in every defocused scatterer in ISAR image. The new approach aims to choose strong scatterers for error phase averaging with a threshold rather than just simply to pick out the strongest point in each range cell, which is not necessarily real strong scatterers if in some range cells consists more than one strong scatterer and whereas in other range cells no scatterer at all. The results of processing real data are presented to confirm the validity of the proposed approach.

Three-Airy autofocusing beams

We numerically and experimentally demonstrate that a three-Airy autofocusing beam can be generated by superposing three deformed two-dimensional(2D)Airy beams with a triangle symmetry.When the initial angle between two wings of the deformed 2D Airy beams increases,such a three-Airy autofocusing beam exhibits that the focusing length decreases and the intensity contrast at the focal point changes.Moreover,after introducing an optical vortex phase,this three-Airy autofocusing beam displays a transverse rotation in propagation.The rotation angle is determined by the topological charge of the vortex and the initial wing angle.Our results may have some potential applications in optical manipulation.

ADAPTIVE KURTOSIS OPTIMIZATION AUTOFOCUS ALGORITHM

This paper proposes an autofocus algorithm used for Synthetic Aperture Radar (SAR) images, called Adaptive Kurtosis Optimization Autofocus Algorithm (AKOAA). The AKOAA can reduce the differ-ence between initial value and real value in focusing by adaptively adjusting the initial value, therefore effec-tively improve the local extremum problem in the Contrast Optimization Autofocus Algorithm (COAA) and speed up the convergence velocity. The principle and realization method of AKOAA are thoroughly investi-gated, and experimental results using real L-band SAR data show that the focus speed of AKOAA is nearly doubled compared with that of the COAA, and the image contrast of AKOAA is improved as well.

A High Speed Autofocusing System for Micro System Applications

In this paper,we present a high speed autofocus system for micro system applications and design a look-up-table based autofocusing algorithm for applications when a target object is always visible,e.g.,manufacturing parts with alignment fiducials.We perform an evaluation of 24 focus measures to verify that which focus measure is the best for the look-up-table based method.From the evaluation,we find that the Chebyshev moments-based focus measure（CHEB） is the most suitable.Furthermore,we also develop a look-up-table based autofocus system that uses CHEB as the focus measure.In training phase,we offline construct a table from training images of an object that are captured at several lens distances.Each entry of table consists of focus measure computed from image and lens distance.In working phase,given an input image,the algorithm first computes the focus measure and then finds the best match focus measure from the table and looks up the corresponding lens position for moving it into the in-focus position.Our algorithm can perform autofocusing within only 2 steps of lens moving.The experiment shows that the system can perform high speed autofocusing of micro objects.

Optimization design of autofocusing metasurface for ultrasound wave application

In this paper,two optimized autofocusing metasurfaces(AFMs)with different desired focal distances are designed by using particle swarm optimization(PSO)algorithm.Based on the ffnite element simulation software COMSOL Multiphysics,the performance of ultrasound transducer(UT)with AFM at different design parameters in Airy distributions(r0,ω)and the bottom thickness(d)of AFM are simulated and analyzed.Based on the simulation data,the artiffcial neural network model is trained to describe the complex relationship between the design parameters of AFM and the performance parameters of UT.Then,the multiobjective optimization function for AFM is determined according to the desired performance parameters of UT,including focal position,lateral resolution,longitudinal resolution and absolute sound pressure.In order to obtain AFMs with the desired performance,PSO algorithm is adopted to optimize the design parameters of AFM according to the multiobjective optimization function,and two AFMs are optimized and fabricated.The experimental results well agree with the simulation and optimization results,and the optimized AFMs can achieve the desired performance.The fabricated AFM can be easily integrated with UT,which has great potential applications in wave ffeld modulation underwater,acoustic tweezers,biomedical imaging,industrial nondestructive testing and neural regulation.

A new autofocus method for inverse synthetic aperture radar——Local dominant scatterer synthesis

Motion compensation is a key and difficult step in inverse synthetic aperture radar (ISAR) . The calibration of initial phase errors, which is well known as autofocus, requires very high precision, so it determines the quality of the reconstructed image to a great extent. A new autofocus method called the local dominant scatterer synthesis (LDSS) is presented. It has the capability to sufficiently reduce the errors induced by clutter and noise, and the advantage of having wide applications. Experiments of real measured data have shown its effectiveness.

Efcient autofocus method for sequential automatic capturing of high-magnification microscopic images

This letter presents an autofocus （AF） method to position a high-magnification microscope lens that automatically captures hundreds of images from a single moving slide. These images are taken by a mobile clinic unit in a rural location, and are later automatically processed and revised by a remote specialist. This process requires high focus precision to enable image processing techniques to achieve proper results. Low focusing times are also required for the system to be operative. We propose a novel method that combines two focus measures with an adapted searching scheme to cope with both constraints.

A novel autofocus algorithm based on maximum total variation criteria for SAR images

A novel autofocus algorithm for synthetic aperture radar(SAR)based on total variation is presented in this paper.The method,which starts with a complex phase-degraded SAR image,after the phase errors model is intro-duced into the range-compressed phase-history domain,carries out phase errors correction by changing the focus till the total variation of the azimuth profile is maximized.Compared with the minimum entropy autofocus algorithm,the autofocus algorithm has less computational complexity and is easier to implement.The simulation and the processing results of the measured data show the validity of the proposed method.

Generation and regulation of two-dimensional autofocusing Airy beams based on holographic metasurfaces

This paper proposes a new method to generate a two-dimensional(2D)Airy beam and Airy autofocusing beam by using the scalar holographic metasurface with amplitude-phase modulation in the microwave band.The proposed holographic metasurface comprises subwavelength patch unit cells with a period of fewer than 1/8 wavelengths,which means that it has the finer sampling for electromagnetic waves and can simultaneously achieve precise modulations for the amplitude and phase of electromagnetic waves.Firstly,the 2D-Airy beam with quasi-non-diffraction and selfbending characteristics is generated,from which the holographic metasurface is designed to realize four different 2D-Airy beams with the same focus,achieving the 2D-Airy autofocusing beam in the microwave frequency.The holographic metasurface for Airy beam generation has high efficiency and an ultra-lower profile.Meanwhile,for applying the Airy beam in wireless power transfer(WPT),the efficiency of the generated Airy beam and Airy autofocusing beam is calculated for the first time in the microwave field.The simulation results show that the efficiency of the 2D-Airy beam can reach 66%at 150 mm away from the metasurface,while the efficiency of the 2D-Airy autofocusing beam at the focus,which is 280 mm from the metasurface,can reach 35%.The theoretical,simulated,and measured results show that the proposed method and holographic metasurfaces can flexibly achieve the special characteristics of self-autofocusing and self-bending Airy beams in the microwave domain,providing an effective path for wireless power transfer(WPT)scenario with radial obstructions.

Optical storage of circular airy beam in atomic vapor

The realization of quantum storage of spatial light field is of great significance to the construction of high-dimensional quantum repeater.In this paper,we experimentally realize the storage and retrieval of circular Airy beams(CABs)by using theΛ-type three-level energy system based on the electromagnetically induced transparency in a hot rubidium atomic vapor cell.The weak probe beam field is modulated with phase distribution of CABs by a spatial light modulator.We store the probe circular Airy beam(CAB)into the rubidium atomic vapor cell and retrieve it after the demanded delay.We quantitatively analyze the storage results and give corresponding theoretical explanations.Moreover,we investigate the autofocusing and self-healing effect of the retrieved CAB,which indicates that the properties and beam shape of CAB maintain well after storage.Our work will have potential applications in the storage of high-dimensional quantum information,and is also useful for improving the channel capacities of quantum internet.

Optical trapping capability of tornado circular Pearcey beams

We systemically investigate optical trapping capability of a kind of tornado waves on Rayleigh particles.Such tornado waves are named as tornado circular Pearcey beams(TCPBs)and produced by combining two circular Pearcey beams with different radii.Our theoretical exploration delves into various aspects,including the propagation dynamics,energy flux,orbital angular momentum,trapping force,and torque characteristics of TCPBs.The results reveal that the orbital angular momentum,trapping force,and torque of these beams can be finely tuned through the judicious manipulation of their topological charges(l_(1)and l_(2)).Notably,we observe a precise control mechanism wherein the force diminishes with|l_(1)+l_(2)|and|l_(1)-l_(2)|,while the torque exhibits enhancement by decreasing solely with|l_(1)+l_(2)|or increasing with|l_(1)-l_(2)|.These results not only provide quantitative insights into the optical trapping performance of TCPBs but also serve as a valuable reference for the ongoing development of innovative photonic tools.

地震资料层间多次波压制方法研究进展

层间多次波压制是目前困扰油气地震勘探的难题之一。为推动层间多次波压制方法的发展,对层间多次波预测及自适应相减方法的研究进展进行了调研,总结了共聚焦点技术、地表数据分离法、逆散射级数法、虚同相轴法、Marchenko自聚焦方法等备受关注的层间多次波预测方法以及自适应相减法的发展进程,分析了上述方法的优缺点。共聚焦点技术中层相关算法相比边界算法具有更强的适应性,但以牺牲计算成本为代价;逆散射级数法虽然具有较高的多次波预测精度,但是巨大的计算量限制了其推广应用;地表数据分离法和虚同相轴法虽然具有较高的计算效率,但是数据分离过于依赖人工操作;Marchenko自聚焦方法目前在实际应用中尚不成熟。自适应相减方法在一次波和多次波非正交情况下的局限性导致了层间多次波压制方法的诞生。在保证层间多次波压制效果的前提下提高计算效率以及实用性,是当前层间多次波压制方法的重要发展方向。结合目前研究热点,层间多次波压制方法与波形反演、深度学习等方法技术的结合可能是未来的发展趋势。

基于压缩全息的散射介质中三维粒子定位

在三维空间中,粒子作为物质分布的基本单元,其精确定位对于医疗、环境监测、燃烧过程分析以及航空航天研究等领域至关重要。然而,散射介质中的粒子检测常面临分辨率不足和定位难的问题。因此开发了一种新的检测技术,该技术基于自动聚焦压缩全息原理,融合了压缩传感与自动对焦机制,有效提升了重建图像的轴向分辨率和粒子检测的准确性。通过模拟和实验测试,该技术的轴向分辨率误差小于3μm,确保了优异的检测精度。实验数据进一步证实,与传统的角谱法相比,本技术在观察散射介质中微粒的三维分布和评估粒子直径方面具有明显优势。本研究成果为相关领域的科学研究和实际应用提供了一种创新的技术途径。