Phase Error Correction Research Articles

Improved SPGD algorithm for optical phased array chip phase error correction in Lidar applications

Random phase errors in silicon-photonic-based OPA (optical phased array) chips can significantly affect their output beam quality, making efficient phase error correction an important requirement for Lidar systems utilizing OPA chip technology. We report an improved ASPGD algorithm for performing OPA random phase error correction with high efficiency and accuracy, especially for large channel count designs. We successfully demonstrated the ASPGD algorithm phase error calibration capability using a fabricated 16-channel chip, and we also showed that the ASPGD algorithm has significantly faster convergence and higher cosine similarity values for the corrected output beam profile compared with traditional SPGD and genetic algorithms, especially for higher channel count OPA chip designs. We believe our work can make an important contribution to the field deployment of OPA technology for chip scale long-range Lidar applications.

Simultaneous multislice diffusion imaging using navigator-free multishot spiral acquisitions.

This work aims to raise a novel design for navigator-free multiband (MB) multishot uniform-density spiral (UDS) acquisition and reconstruction, and to demonstrate its utility for high-efficiency, high-resolution diffusion imaging. Our design focuses on the acquisition and reconstruction of navigator-free MB multishot UDS diffusion imaging. For acquisition, radiofrequency-pulse encoding was used to achieve controlled aliasing in parallel imaging in MB imaging. For reconstruction, a new algorithm named slice-projection onto convex sets-enhanced inherent correction of phase errors (slice-POCS-ICE) was proposed to simultaneously estimate diffusion-weighted images and intershot phase variations for each slice. The efficacy of the proposed methods was evaluated in both numerical simulation and in vivo experiments. In both numerical simulation and in vivo experiments, slice-POCS-ICE estimated phase variations more precisely and provided results with better image quality than other methods. The intershot phase variations and MB slice aliasing artifacts were simultaneously resolved using the proposed slice-POCS-ICE algorithm. The proposed navigator-free MB multishot UDS acquisition and reconstruction method is an effective solution for high-efficiency, high-resolution diffusion imaging.

High-Contrast Imaging: Hide and Seek with Exoplanets

So far, most of the about 5700 exoplanets have been discovered mainly with radial velocity and transit methods. These techniques are sensitive to planets in close orbits, not being able to probearge star–planet separations. μ-lensing is the indirect method that allows us to probe the planetary systems at the snow-line and beyond, but it is not a repeatable observation. On the contrary, direct imaging (DI) allows for the detection and characterization ofow mass companions at wide separation (≤5–6 au). The main challenge of DI is that a typical planet–star contrast ranges from 10−6, for a young Jupiter in emittedight, to 10−9 for Earth in reflectedight. In theast two decades, aot of efforts have been dedicated to combiningarge (D ≥ 5 m) telescopes (to reduce the impact of diffraction) with coronagraphs and high-order adaptive optics (to correct phase errors induced by atmospheric turbulence), with sophisticated image post-processing, to reach such a contrast between the star and the planet in order to detect and characterize cooler and closer companions to nearby stars. Building on the first pioneering instrumentation, the second generation of high-contrast imagers, SPHERE, GPI, and SCExAO, allowed us to probe hundreds of stars (e.g., 500–600 stars using SHINE and GPIES), contributing to a better understanding of the demography and the occurrence of planetary systems. The DI offers a possible clear vision for studying the formation and physical properties of gas giant planets and brown dwarfs, and the future DI (space and ground-based) instruments with deeper detectionimits will enhance this vision. In this paper, we briefly review the methods, the instruments, the main sample of targeted stars, the remarkable results, and the perspective of this rising technique.

NMR Phase Error Correction with New Modelling Approaches

Nuclear Magnetic Resonance (NMR) spectroscopy is a highly sensitive analytical technique essential for precise molecular identification and quantification. However, accurate results depend on effective pre-processing to correct for various types of errors. Phase error correction, in particular, is crucial for ensuring the reliability of NMR data. Current methods often rely on a single linear model, which may not adequately address all types of phase errors. As a result, this limitation frequently requires manual intervention, making the process both time-consuming and prone to errors. To address these limitations, we propose three modelling approaches for NMR phase error correction: nonlinear shrinkage, multiple models, and a new optimization function called delta absolute net minimization (DANM). Our comparison of seven methods revealed that nonlinear shrinkage outperformed others in both simulated spectra and a diabetes study, followed by multiple models with DANM. Additionally, our spike-in experiments demonstrated that DANM performed quite well in both single and multiple models. Our nonlinear shrinkage approach is a simple yet effective solution. We provide an open-source R package, NMRphasing, available on CRAN (https://cran.r-project.org/web/packages/NMRphasing/) and on GitHub (https://github.com/ajiangsfu/NMRphasing).

Phase Error Correction in Sparse Linear MIMO Radar Based on the Equivalent Phase Center Principle

Multiple-input multiple-output (MIMO) technology is widely used in the field of radar imaging. Array sparse optimization reduces the hardware cost of MIMO radar, while virtual aperture and the equivalent phase center (EPC) principle simplify the radar signal model and reduce the computation and complexity of imaging algorithms. However, the application of sparse array structure and the EPC principle produces a non-negligible phase error, which affects the imaging quality. This paper simplifies the MIMO radar signal model based on the phase center approximation, analyzes the phase error generated by this method, and proposes an improved phase error correction method to solve the problem that the target cannot be well-focused at non-reference distance during imaging. In addition, this paper designs a sparse linear MIMO array with a periodic structure, which reduces the number of transmitting and receiving units, system complexity, and hardware costs. The proposed phase correction method was combined with the wavenumber domain algorithm to simulate and experiment on the designed antenna array, and good experimental results were obtained to verify the effectiveness of the proposed method.

High-resolution SAR optoelectronic processor based on sensor-less adaptive optics

Studying phase error is central to synthetic aperture radar (SAR) research. Phase error due to the real motion status of the SAR platform and propagation effects can reduce the utility of high-resolution SAR images even with theoretical estimation-based phase error correction. Adaptive optics (AO) can be used to correct optical aberrations. This study proposes an advanced, high-resolution SAR optoelectronic processor by integrating conventional processors with sensor-less AO techniques. This processor provides accurate adaptive phase error correction capabilities. The processing results of SAR echo data demonstrate the effectiveness of the proposed system in adaptive phase error correction and imaging improvement.

Design of wavefront detection system for eyeglasses based on transmissive phase measuring deflectometry using gamma error correction algorithm

With the increasingly widespread application of freeform lenses, the detection of lens dioptric power presents a challenge. To measure the surface dioptric power of freeform lenses, a wavefront detection system for eyeglass lenses based on transmissive phase measuring deflectometry has been developed. The system consists only of a monitor, an industrial camera, and the lens under test. In response to the phase errors introduced by nonlinear devices, a Frequency Domain Gamma Error Correction Algorithm based on Linear Regression (FDLR) is proposed to optimize the system detection process and enhance detection accuracy. In the experiments, the proposed system was used to measure the wavefront and surface dioptric power of both spherical lens and progressive addition lens. The results were compared with those obtained from a focimeter to verify the accuracy and reliability of the system. Furthermore, a comparison of the detection results for progressive addition lens before and after phase error correction was conducted to demonstrate the necessity and effectiveness of the proposed phase error correction algorithm.

Error analysis and correction of atmospheric disturbance for interferometric imaging radar altimeter

Error analysis and correction of atmospheric disturbance for interferometric imaging radar altimeter

A Clustering Approach for Atmospheric Phase Error Correction in Ground-Based SAR Using Spatial Autocorrelation.

When using ground-based synthetic aperture radar (GB-SAR) for monitoring open-pit mines, dynamic atmospheric conditions can interfere with the propagation speed of electromagnetic waves, resulting in atmospheric phase errors. These errors are particularly complex in rapidly changing weather conditions or steep terrain, significantly impacting monitoring accuracy. In such scenarios, traditional regression model-based atmospheric phase correction (APC) methods often become unsuitable. To address this issue, this paper proposes a clustering method based on the spatial autocorrelation function. First, the interferogram is uniformly divided into multiple blocks, and the phase consistency of each block is evaluated using the spatial autocorrelation function. Then, a region growing algorithm is employed to classify each block according to its phase pattern, followed by merging adjacent blocks based on statistical data. To verify the feasibility of the proposed method, both the traditional regression model-based method and the proposed method were applied to deformation monitoring of an open-pit mine in Northwest China. The experimental results show that for complex atmospheric phase scenarios, the proposed method significantly outperformed traditional methods, demonstrating its superiority.

Insights into Nuclear Magnetic Resonance Data Preprocessing: A Comprehensive Review

Nuclear Magnetic Resonance (NMR) and its derivatives play a pivotal role in molecular analysis across research and clinical domains. However, the intricate nature of NMR data pre-processing, which is integral for accurate analysis, is not easily understood despite the availability of numerous software tools. This comprehensive review aims to unravel the complexities of pre-processing algorithms in both the time and frequency domains. It covers essential steps such as direct current offset removal, eddy current correction, shift and linear prediction, weighting, zero filling, domain transformation, phase error correction, baseline correction, solvent filtering, calibration and alignment, reference deconvolution, binning/bucketing, peak picking, peak fitting/deconvolution, compound identification, integration and quantification, normalization, and transformation. The review uses plain language to enhance accessibility and understanding. By demystifying the algorithms behind these pre-processing steps, we seek to help researchers and practitioners in navigating the nuances of NMR data pre-processing, ultimately fostering better understanding and practical application in molecular analysis. Received:1 February 2024| Revised: 20 May 2024| Accepted: 30 May 2024 Conflicts of Interest Aixiang Jiang is an Editorial Board Member for Journal of Data Science and Intelligent Systems and was not involved in the editorial review or the decision to publish this article. The author declares that she has no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Aixiang Jiang: Conceptualization, Methodology, Software, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration.

Heimdallr, Baldr, and Solarstein: designing the next generation of VLTI instruments in the Asgard suite

High angular resolution imaging is an increasingly important capability in contemporary astrophysics. Of particular relevance to emerging fields such as the characterization of exoplanetary systems, imaging at the required spatial scales and contrast levels results in forbidding challenges in the correction of atmospheric phase errors, which in turn drives demanding requirements for precise wavefront sensing. Asgard is the next-generation instrument suite at the European Southern Observatory’s Very Large Telescope Interferometer (VLTI), targeting advances in sensitivity, spectral resolution, and nulling interferometry. In this paper, we describe the requirements and designs of three core modules: Heimdallr, a beam combiner for fringe tracking, low order wavefront correction, and visibility science; Baldr, a Zernike wavefront sensor to correct high order atmospheric aberrations; and Solarstein, an alignment and calibration unit. In addition, we draw generalizable insights for designing such system and discuss integration plans.

An Extended Polar Format Algorithm for Joint Envelope and Phase Error Correction in Widefield Staring SAR with Maneuvering Trajectory

Polar format algorithm (PFA) is a widely used high-resolution SAR imaging algorithm that can be implemented in advanced widefield staring synthetic aperture radar (WFS-SAR). However, existing algorithms have limited analysis in wavefront curvature error (WCE) and are challenging to apply to WFS-SAR with high-resolution and large-swath scenes. This paper proposes an extended polar format algorithm for joint envelope and phase error correction in WFS-SAR imaging with maneuvering trajectory. The impact of the WCE and residual acceleration error (RAE) are analyzed in detail by deriving the specific wavenumber domain signal based on the mapping relationship between the geometry space and wavenumber space. Subsequently, this paper improves the traditional WCE compensation function and introduces a new range cell migration (RCM) recalibration function for joint envelope and phase error correction. The 2D precisely focused SAR image is acquired based on the spatially variant inverse filtering in the final. Simulation experiments validate the effectiveness of the proposed method.

A Phase Correction Model for Fourier Transform Spectroscopy

In Fourier transform spectroscopy (FTS), the conventional Mertz method is commonly used to correct phase errors of recovered spectra, but it performs poorly in correcting nonlinear phase errors. This paper proposes a phase correlation method–all-pass filter (PCM-APF) model to correct phase errors. In this model, the proposed improved phase correlation method can correct linear phase errors, and all-pass filters are applied to correct the residual nonlinear phase errors. The optimization algorithm for the digital all-pass filters employs an improved algorithm which combines the subtraction-average-based optimizer (SABO) and the golden sine algorithm (Gold-SA). The proposed PCM-APF model demonstrates high correction precision, and the optimization algorithm for the filters converges faster than traditional intelligent optimization algorithms.

Combining MIMO DBF With Automotive Synthetic Aperture Radar Imaging and Phase Error Correction

Combining MIMO DBF With Automotive Synthetic Aperture Radar Imaging and Phase Error Correction

Neurologically Motivated Simulation of Ensemble Performance

A “rhythmic agent” is simulated based on the foundation of a previously published behavioral sensorimotor synchronization (SMS) model. The model is adjustable to control the auditory and tactile modalities of the tap's feedback. In addition to the conventional mechanisms of phase and period error correction, as well as their activation conditions, the period is estimated by modeling a central timekeeper impacted by a novel short-term memory. Inspired by The ADaptation and Anticipation Model (ADAM), a mechanism for linearly extrapolating anticipation is also tested. To better match the perceptual and motor cognitive functions, the model's parameters have been tuned to observations from experimental neurosensory literature with an emphasis on transduction delays. The agent is programmed to synchronize with various external rhythmic input signals while accounting for both adaptive and predictive mechanisms. The definition of the agent is based on a minimal set of rules yet has successfully replicated results of real-world observations: against a metronome; it produces the well-known negative mean asynchrony. In a rhythmic joint action, the simulation of joint delayed coordination shows a behavior previously observed in human subjects: in a rhythmic collaboration, a moderate amount of delay is necessary to keep the tempo steady, and below that threshold, the rhythm tends to speed up. It is also shown that giving more weight to the tactile afferent feedback than the auditory intensifies this effect. Moreover, it is observed that including anticipation in addition to the reactive mechanism will decrease the effect. The proposed model as a rhythmic engine, combined with other standard modules such as a beat detection algorithm, can be used to implement musical co-performers that could improvise with a human rhythmically or perform a given score in a way that feels human-like.

Correction of phase errors introduced by nonlinearity and specular reflection based on double N-step phase-shifting profilometry

Correction of phase errors introduced by nonlinearity and specular reflection based on double N-step phase-shifting profilometry

Error correction algorithm of array time-varying amplitude and phase based on autoencoder

As array antennas are widely used in various mobile platforms, the time-varying amplitude and phase error has become an important factor affecting the application of array signal processing technology. A deep learning-based algorithm for the correction of time-varying amplitude and phase errors in arrays is proposed in terms of the idea of autoencoder. The algorithm makes full use of the data feature extraction and reconstruction capability of the autoencoder network, designs a deep learning network for the correction of time-varying amplitude phase error of the channel, gives a double-driven learning mechanism without time-varying amplitude phase error data (unperturbed data) and time-varying amplitude phase error data (perturbed data), completes the extraction of the array stream shape hidden features based on the principle of minimising the mean square error of the desired output and the ideal model. The simulated experiments show that the algorithm can effectively correct the time-varying amplitude and phase errors of each channel, and the mean square error of the corrected amplitude and phase errors are within 0.5% and 1.5% respectively when there are ±80% random time-varying amplitude errors and ±5° random time-varying phase errors. The effectiveness of the proposed algorithm is verified.

Optical pilot tone correction of phase errors in photodetection chains

The phase delay introduced by photodetectors can be affected by intensity, reverse bias, and temperature through different effects. An optical pilot tone superimposed on the detected signal allows an independent measurement of such phase errors in the complete photodetection chain and provides an opportunity to correct them. This allows to further separate readout noise from the measurement, providing a more performant and intensity-invariant phase readout. We test the functional principle on a setup demonstrating an improved phase noise performance and a reduced phase walk below 10 mHz in particular. This benefits applications that require accurate timing or signal phase determination with photodiodes.

A low-jitter and low-phase noise switched-loop filter PLL using fast phase-error correction and dual-edge phase comparison technique

A low-jitter and low-phase noise switched-loop filter PLL using fast phase-error correction and dual-edge phase comparison technique

Improving magnetic resonance spectroscopy in the brainstem periaqueductal gray using spectral registration.

Functional understanding of the periaqueductal gray (PAG), a clinically relevant brainstem region, can be advanced using 1 H-MRS. However, the PAG's small size and high levels of physiological noise are methodologically challenging. This study aimed to (1) improve 1 H-MRS quality in the PAG using spectral registration for frequency and phase error correction; (2) investigate whether spectral registration is particularly useful in cases of greater head motion; and (3) examine metabolite quantification using literature-based or individual-based water relaxation times. Spectra were acquired in 33 healthy volunteers (50.1 years, SD = 17.19, 18 females) on a 3 T Philipps MR system using a point-resolved spectroscopy (PRESS) sequence optimized with very selective saturation pulses (OVERPRESS) and voxel-based flip angle calibration (effective volume of interest size: 8.8 × 10.2 × 12.2 mm3 ). Spectra were fitted using LCModel and SNR, NAA peak linewidths and Cramér-Rao lower bounds (CRLBs) were measured after spectral registration and after minimal frequency alignment. Spectral registration improved SNR by 5% (p = 0.026, median value post-correction: 18.0) and spectral linewidth by 23% (p < 0.001, 4.3 Hz), and reduced the metabolites' CRLBs by 1% to 15% (p < 0.026). Correlational analyses revealed smaller SNR improvements with greater head motion (p = 0.010) recorded using a markerless motion tracking system. Higher metabolite concentrations were detected using individual-based compared to literature-based water relaxation times (p < 0.001). This study demonstrates high-quality 1 H-MRS acquisition in the PAG using spectral registration. This shows promise for future 1 H-MRS studies in the PAG and possibly other clinically relevant brain regions with similar methodological challenges.