Search Results (120)

Recent advancements in quantum and quantum-inspired imaging techniques have enabled high-resolution 3D imaging through photon correlations. These techniques exhibit reduced degradation of image resolution for out-of-focus samples compared to conventional methods (i.e., intensity-based incoherent imaging). A key advantage of these correlation-based approaches is their independence from the system numerical aperture (NA). Interestingly, both improved resolution of defocused images and NA-independent scaling are linked to the spatial coherence of light. This suggests that while correlation measurements exploit spatial coherence, they are not essential for achieving this imaging advantage. This discovery has led to the development of optical systems that achieve similar performance by using spatially coherent illumination and relying on intensity measurements: direct 3D imaging with NA-independent resolution was recently demonstrated in a correlation-free setup using LED light. Here, we explore the physics behind the enhanced performance of defocused coherent imaging, showing that it arises from the modification of the sample’s spatial harmonic content due to diffraction, unlike the blurring seen in conventional imaging. The results we present are crucial for understanding the implications of the physical differences between coherent and incoherent imaging, and are expected to pave the way for the practical application of the discovered phenomena. Full article

With the rapid development of synthetic aperture radar (SAR), delivery platforms are gradually becoming diversified and miniaturized. The SAR flight process is susceptible to external influences, resulting in unsatisfactory imaging results, so it is necessary to optimize imaging processing in combination with the SAR imaging quality assessment (IQA) index. Based on the principle of SAR imaging, this paper analyzes the impact of defocusing on imaging results caused by mismatched filters and draws on the assessment algorithm of motion blur, proposing a SAR IQA index based on average blurred edge width (ABEW) in the salient area. In addition, the idea of decomposing the transfer function in the frequency domain and fitting the matched filter with a polynomial is also proposed. The estimation of the flight trajectory is changed to a correction of the matched filter, avoiding the precise estimation of Doppler parameters and complex calculations during the time–frequency conversion process. The effectiveness of ABEW was verified by using SAR images of real scenes, and the results were highly consistent with the actual image quality. The imaging processing was tested using the echo signals generated by the errors introduced during the flight process, and more satisfactory imaging results were obtained by using ABEW with the filter for correction. The imaging process was tested using the echo signal generated by introducing errors during the flight, and the filter was corrected using ABEW as an index, obtaining a comparatively ideal imaging result. Full article

Combining multiple data sources, Digital Earth is an integrated observation platform based on air–space–ground–sea monitoring systems. Among these data sources, the Inverse Synthetic Aperture Radar (ISAR) is a crucial observation method. ISAR is typically utilized to monitor both military and civilian ships due to its all-day and all-weather superiority. However, in complex scenarios, multiple targets may exist within the same radar antenna beam, resulting in severe defocusing due to different motion conditions. Therefore, this paper proposes a multiple-target ISAR imaging method with the removal of micro-motion connections based on the integration of joint constraints. The fully motion-compensated targets exhibit low rank and local similarity in the high-resolution range profile (HRRP) domain, while the micro-motion components possess sparsity. Additionally, targets display sparsity in the image domain. Inspired by this, we formulate a novel optimization by promoting the low-rank, the Laplacian, and the sparsity constraints of targets and the sparsity constraints of the micro-motion components. This optimization problem is solved by the linearized alternative direction method with adaptive penalty (LADMAP). Furthermore, the different motions of various targets degrade their inherent characteristics. Therefore, we integrate motion compensation transformation into the optimization, accordingly achieving the separation of rigid bodies and the micro-motion components of different targets. Experiments based on simulated data demonstrate the effectiveness of the proposed method. Full article

In the deep-sea environment, the volume available for an in-situ gene sequencer is severely limited. In addition, optical imaging systems are subject to real-time, large-scale defocusing problems caused by ambient temperature fluctuations and vibrational perturbations. To address these challenges, we propose an edge detection algorithm for defocused images based on grayscale gradients and establish a defocus state detection model with nanometer resolution capabilities by relying on the inherent critical illumination light field. The model has been applied to a prototype deep-sea gene sequencing microscope with a 20× objective. It has demonstrated the ability to focus within a dynamic range of ±40 μm with an accuracy of 200 nm by a single iteration within 160 ms. By increasing the number of iterations and exposures, the focusing accuracy can be refined to 78 nm within a dynamic range of ±100 μm within 1.2 s. Notably, unlike conventional photoelectric hill-climbing, this method requires no additional hardware and meets the wide dynamic range, speed, and high-accuracy autofocusing requirements of deep-sea gene sequencing in a compact form factor. Full article

Circular synthetic aperture radar (CSAR) has attracted a lot of interest, recently, for its excellent performance in civilian and military applications. However, in CSAR imaging, the result is to be defocused when the height of an object deviates from a reference height. Existing approaches for this problem rely on digital elevation models (DEMs) for error compensation. It is difficult and costly to collect DEM using specific equipment, while the inversion of DEM based on echo is computationally intensive, and the accuracy of results is unsatisfactory. Inspired by multi-focus image fusion in optical images, a spatial-domain fusion method is proposed based on the sum of modified Laplacian (SML) and guided filter. After obtaining CSAR images in a stack of different reference heights, an all-in-focus image can be computed by the proposed method. First, the SMLs of all source images are calculated. Second, take the rule of selecting the maximum value of SML pixel by pixel to acquire initial decision maps. Secondly, a guided filter is utilized to correct the initial decision maps. Finally, fuse the source images and decision maps to obtain the result. A comparative experiment has been processed to verify the exceptional performance of the proposed method. The final processing result of real-measured CSAR data demonstrated that the proposed method is effective and practical. Full article

In recent years, with the miniaturization of high-precision position and orientation systems (POS), precise motion errors during SAR data collection can be calculated based on high-precision POS. However, compensating for these errors remains a significant challenge for multi-rotor UAV-borne SAR systems. Compared with large aircrafts, multi-rotor UAVs are lighter, slower, have more complex flight trajectories, and have larger squint angles, which result in significant differences in motion errors between building targets and ground targets. If the motion compensation is based on ground elevation, the motion error of the ground target will be fully compensated, but the building target will still have a large residual error; as a result, although the ground targets can be well-focused, the building targets may be severely defocused. Therefore, it is necessary to further compensate for the residual motion error of building targets based on the actual elevation on the SAR image. However, uncompensated errors will affect the time–frequency relationship; furthermore, the ω-k algorithm will further change these errors, resulting in errors in SAR images becoming even more complex and difficult to compensate for. To solve this problem, this paper proposes a novel improved precise topography and aperture-dependent (PTA) method that can precisely compensate for motion errors in the UAV-borne SAR system. After motion compensation and imaging processing based on ground elevation, a secondary focus is applied to defocused buildings. The improved PTA fully considers the coupling of the residual error with the time–frequency relationship and ω-k algorithm, and the precise errors in the two-dimensional frequency domain are determined through numerical calculations without any approximations. Simulation and actual data processing verify the effectiveness of the method, and the experimental results show that the proposed method in this paper is better than the traditional method. Full article

With the increasingly complex electromagnetic environment faced by radar, random stepped frequency (RSF) has garnered widespread attention owing to its remarkable Electronic Counter-Countermeasure (ECCM) characteristic, and it has been universally applied in inverse synthetic aperture radar (ISAR) in recent years. However, if the phase error induced by the translational motion of the target in RSF ISAR is not precisely compensated, the imaging result will be defocused. To address this challenge, a novel 2D method based on sparse Bayesian learning, denoted as 2D-autofocusing complex-value inverse-free SBL (2D-AFCIFSBL), is proposed to accomplish joint ISAR imaging and autofocusing for RSF ISAR. First of all, to integrate autofocusing into the ISAR imaging process, phase error estimation is incorporated into the imaging model. Then, we increase the speed of Bayesian inference by relaxing the evidence lower bound (ELBO) to avoid matrix inversion, and we further convert the iterative process into a matrix form to improve the computational efficiency. Finally, the 2D phase error is estimated through maximum likelihood estimation (MLE) in the image reconstruction iteration. Experimental results on both simulated and measured datasets have substantiated the effectiveness and computational efficiency of the proposed 2D joint imaging and autofocusing method. Full article

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time–domain Gaussian fitting method is proposed in this paper. The concept of a time–domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time–domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time–domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms. Full article

In recent years, optical systems near the diffraction limit have been widely used in high-end applications. Evidently, an analytical solution of the point spread function (PSF) will help to enhance both understanding and dealing with the imaging process. This paper analyzes the Fresnel diffraction of diffraction-limited optical systems in defocused conditions. For this work, an analytical solution of the defocused PSF was obtained using the series expansion of the confluent hypergeometric functions. The analytical expression of the defocused optical transfer function is also presented herein for comparison with the PSF. Additionally, some characteristic parameters for the PSF are provided, such as the equivalent bandwidth and the Strehl ratio. Comparing the PSF obtained using the fast Fourier transform algorithm of an optical system with known, detailed parameters to the analytical solution derived in this paper using only the typical parameters, the root mean square errors of the two methods were found to be less than 3% in the weak and medium defocus range. The attractive advantages of the universal model, which is independent of design details, objective types, and applications, are discussed. Full article

Sub-Nyquist synthetic aperture radar (SAR) based on pseudo-random time–space modulation has been proposed to increase the swath width while preserving the azimuthal resolution. Due to the sub-Nyquist sampling, the scene can be recovered by an optimization-based algorithm. However, these methods suffer from some issues, e.g., manually tuning difficulty and the pre-definition of optimization parameters, and a low signal–noise ratio (SNR) resistance. To address these issues, a reweighted optimization algorithm, named pseudo-ℒ₀-norm optimization algorithm, is proposed for the sub-Nyquist SAR system in this paper. A modified regularization model is first built by applying the scene prior information to nearly acquire the number of nonzero elements based on Bayesian estimation, and then this model is solved by the Cauchy–Newton method. Additionally, an error correction method combined with our proposed pseudo-ℒ₀-norm optimization algorithm is also present to eliminate defocusing in the motion-induced model. Finally, experiments with simulated signals and strip-map TerraSAR-X images are carried out to demonstrate the effectiveness and superiority of our proposed algorithm. Full article

Imaging maritime targets requires a high resolution and wide swath (HWRS) in a synthetic aperture radar (SAR). When operated with a variable pulse repetition interval (PRI), a staggered SAR can realize HRWS imaging, which needs to be reconstructed due to echo pulse loss and a nonuniformly sampled signal along the azimuth. The existing reconstruction algorithms are designed for stationary scenes in a staggered SAR mode, and thus, produce evident image defocusing caused by complex target motion for moving targets. Typically, the nonuniform sampling and complex motion of maritime targets aggravate the spectrum aliasing in a staggered SAR mode, causing inevitable ambiguity and degradation in its reconstruction performance. To this end, this study analyzed the spectrum of maritime targets in a staggered SAR system through theoretical derivation. After this, a reconstruction method named MBLCFD (Modified Best Linear Unbaised and Complex-Lag Time-Frequency Distribution) is proposed to refocus the blurred maritime target. First, the signal model of the maritime target with 3D rotation accompanying roll–pitch–yaw movement was established under the curved orbit of the satellite. The best linear unbiased (BLU) method was modified to alleviate the coupling of nonuniform sampling and target motion. A precise SAR algorithm was performed based on the method of inverse reversion to counteract the effect of a curved orbit and wide swath. Based on the hybrid SAR/ISAR technique, the complex-lag time-frequency distribution was exploited to refocus the maritime target images. Simulations and experiments were carried out to verify the effectiveness of the proposed method, providing precise refocusing performance in staggered mode. Full article

Inverse synthetic-aperture radar (ISAR) can achieve precise imaging of targets, which enables precise perception of battlefield information, and it has become one of the most important tasks for radar systems. In multi-target scenarios, a resource scheduling method is required to improve the sensing ability and the overall efficiency of a radar system due to the limited resources. Considering the motion state of the target will change as the observation distance increases and image defocusing can occur due to the prolonged coherence accumulation time and significant changes in the target’s motion state, the optimal observation period should be an important consideration factor in the resource scheduling method to further improve the imaging efficiency of radar system, which has not yet been involved in existing research. In this paper, we first derive the expressions of the target’s effective rotation angle and the equivalent rotation angular velocity and then define the target’s optimal observation period. Then, for multi-target imaging scenarios, we allocate pulse resources within a given time period based on sparse-aperture ISAR imaging technology. An adaptive radar resource scheduling algorithm for multi-target ISAR imaging is proposed, which prioritizes allocating resources based on the optimal observation periods for the targets. In the algorithm, a radar resource scheduling model for multi-target ISAR imaging is established, and a feedback-based closed-loop search optimization method is proposed to solve the model. Finally, the best scheduling strategy can be obtained, which includes imaging task duration and the pulse allocation sequence for each target. Simulation results validate the effectiveness of the algorithm. Full article

Targets faced by inverse synthetic aperture radar (ISAR) are often non-cooperative, with target maneuvering being the main manifestation of this non-cooperation. Maneuvers cause ISAR imaging results to be severely defocused, which can create huge difficulties in target identification. In addition, as the ISAR bandwidth continues to increase, the impact of migration through resolution cells (MTRC) on imaging results becomes more significant. Target non-cooperation may also result in sparse aperture, leading to the failure of traditional ISAR imaging algorithms. Therefore, this paper proposes an algorithm to realize MTRC correction and sparse aperture ISAR imaging for maneuvering targets simultaneously named whale optimization algorithm–fast iterative shrinkage thresholding algorithm (WOA-FISTA). In this algorithm, FISTA is used to perform MTRC correction and sparse aperture ISAR imaging efficiently and WOA is adopted to estimate the rotational parameter to eliminate the effects of maneuvering on imaging results. Experimental results based on simulation and measured datasets prove that the proposed algorithm implements sparse aperture ISAR imaging and MTRC correction for maneuvering targets simultaneously. The proposed algorithm achieves better results than traditional algorithms under different signal-to-noise ratio conditions. Full article

Synthetic Aperture Ladar (SAL) is a sensor that combines laser detection technology with synthetic aperture technology to achieve ultra-high-resolution imaging. Due to its extremely short wavelength, SAL is more sensitive to motion errors. The micrometer-level motion will affect the target’s azimuth focus. This article proposes an SAL motion compensation method based on Symmetric Triangular Linear Frequency Modulation Continuous Wave (STLFMCW) segmented interference, utilizing the characteristics of a triangular wave, to solve the problem of target azimuth defocusing. This article first establishes an STLFMCW echo signal model based on the SAL system under the influence of motion errors. Secondly, the radial velocity gradient along the azimuth direction is extracted using the triangular-wave-positive and -negative frequency modulation signals segmented interference method. Then, for the initial phase wrapping problem, the frequency spectral cross-correlation method is used to accurately estimate the initial radial velocity error. The radial velocity gradient is integrated along the azimuth to obtain the platform motion trajectory. Finally, the compensation functions are constructed to complete the echo Range Cell Migration (RCM) correction and residual phase compensation, resulting in a focused SAL image. This article verifies the practical effect of this method in eliminating motion errors using only one-period STLFMCW signal through simulation and real experiments. The quantitative results show that compared with the traditional method, the proposed method reduces the azimuth Peak Sidelobe Ratio (PSLR) by 8dB and the Integrated Sidelobe Ratio (ISLR) by 9 dB. This method has significant improvements and is of great significance for high-resolution FMCW SAL imaging. Full article

Micro/nano structures with morphological gradients possess unique physical properties and significant applications in various research domains. This study proposes a straightforward and precise method for fabricating micro/nano structures with morphological gradients utilizing single-voxel synchronous control and a nano-piezoelectric translation stage in a two-photon laser direct writing technique. To address the defocusing issue in large-scale fabrication, a methodology for laser focus dynamic proactive compensation was developed based on fluorescence image analysis, which can achieve high-precision compensation of laser focus within the entire range of the nano-piezoelectric translation stage. Subsequently, the fabrication of micro/nano dual needle structures with morphological gradients were implemented by employing different writing speeds and voxel positions. The minimum height of the tip in the dual needle structure is 80 nm, with a linewidth of 171 nm, and a dual needle total length reaching 200 μm. Based on SEM (scanning electron microscope) and AFM (atomic force microscope) characterization, the dual needle structures fabricated by the method proposed in this study exhibit high symmetry and nanoscale gradient accuracy. Additionally, the fabrication of hexagonal lattice periodic structures assembled from morphological gradient needle structures and the size gradient Archimedean spiral structures validate the capability of the single voxel-based fabrication and proactive focus compensation method for complex gradient structure fabrication. Full article