Target Amplitude Research Articles

Ship Contour Extraction from Polarimetric SAR Images Based on Polarization Modulation

Ship contour extraction is vital for extracting the geometric features of ships, providing comprehensive information essential for ship recognition. The main factors affecting the contour extraction performance are speckle noise and amplitude inhomogeneity, which can lead to over-segmentation and missed detection of ship edges. Polarimetric synthetic aperture radar (PolSAR) images contain rich target scattering information. Under different transmitting and receiving polarization, the amplitude and phase of pixels can be different, which provides the potential to meet the uniform requirement. This paper proposes a novel ship contour extraction framework from PolSAR images based on polarization modulation. Firstly, the image is partitioned into the foreground and background using a super-pixel unsupervised clustering approach. Subsequently, an optimization criterion for target amplitude modulation to achieve uniformity is designed. Finally, the ship’s contour is extracted from the optimized image using an edge-detection operator and an adaptive edge extraction algorithm. Based on the contour, the geometric features of ships are extracted. Moreover, a PolSAR ship contour extraction dataset is established using Gaofen-3 PolSAR images, combined with expert knowledge and automatic identification system (AIS) data. With this dataset, we compare the accuracy of contour extraction and geometric features with state-of-the-art methods. The average errors of extracted length and width are reduced to 20.09 m and 8.96 m. The results demonstrate that the proposed method performs well in both accuracy and precision.

MTD precise jamming technology based on intra-pulse and inter-pulse frequency-phase joint modulation

For moving target detection (MTD) radar, existing jamming systems face problems such as poor controllability and strong regularity of two-dimensional false target characteristics. Time-frequency-phase modulation technology has great potential for active jamming and has received widespread attention. In this article, we propose a precise jamming method based on intra-pulse and inter-pulse frequency-phase joint modulation to control the two-dimensional distribution of false targets. First, construct periodic phase and segmented frequency modulation functions. Secondly, the intra-pulse phase modulation period Ts1 and frequency modulation amount ξl1 accurately control the positions of multiple false targets; the inter-pulse phase modulation period Ts2 and frequency modulation amount ξl2 accurately control the velocity of multiple false targets. Finally, the amplitude of the two-dimensional false target is accurately controlled by adjusting the phase modulation coefficient φi, phase modulation and frequency modulation duty cycles ηs, ηl. Compared with other jamming algorithms, the jamming distribution is more flexible and controllable, which verifies the superiority of this method.

Interdependence of movement amplitude and tempo during self-paced finger tapping: evaluation of a preferred velocity hypothesis.

This study examined the relation between movement amplitude and tempo during self-paced rhythmic finger tapping to test a preferred velocity account of the preferred tempo construct. Preferred tempo refers to the concept that individuals have preferences for the pace of actions or events in their environment (e.g., the desired pace of walking or tempo of music). The preferred velocity hypothesis proposes that assessments of preferred tempo do not represent a pure time preference independent of spatial movement characteristics, but rather reflects a preference for an average movement velocity, predicting that preferred tempo will depend on movement amplitude. We tested this by having participants first perform a novel spontaneous motor amplitude (SMA) task in which they repetitively tapped their finger at their preferred amplitude without instructions about tapping tempo. Next, participants completed the spontaneous motor tempo (SMT) task in which they tapped their finger at their preferred tempo without instructions about tapping amplitude. Finally, participants completed a target amplitude version of the SMT task where they tapped at their preferred tempo at three target amplitudes (low, medium, and high). Participants (1) produced similar amplitudes and tempi regardless of instructions to produce either their preferred amplitude or preferred tempo, maintaining the same average movement velocity across SMA and SMT tasks and (2) altered their preferred tempo for different target amplitudes in the direction predicted by their estimated preferred velocity from the SMA and SMT tasks. Overall, results show the interdependence of movement amplitude and tempo in tapping assessments of preferred tempo.

The Use of Event Related Potentials to Predict Amyloid PET Status Among Patients from a Memory Disorders Clinic.

Amyloid positron emission tomography (PET) scans provide in vivo evidence of Alzheimer's disease (AD); however, their high cost limits their use in standard clinical care. Event related potentials (ERPs) may represent an inexpensive and non-invasive additional method for detecting AD pathology. We investigated whether ERPs, along with neuropsychological data, serve as predictors of amyloid PET status in patients with memory complaints. Veterans aged 50-100 were recruited from a memory disorders clinic. Participants underwent a neuropsychological battery and an ERP auditory oddball protocol. Twenty-eight patients had a positive amyloid PET scan, and thirty-nine patients had a negative scan. ERP-P200 target amplitude and P200 standard latency were predictors of amyloid PET status. When submitting to ROC analysis, P200 standard latency exhibited the highest specificity and sensitivity in predicting amyloid PET positivity, correctly classifying the amyloid PET status for 86% of patients. ERP-P200 measures are strong indicators of amyloid-β presence in patients from a memory disorder clinic. Increased P200 amplitude and decreased P200 latency in patients with a positive amyloid PET scan may be attributed to hyperactivation of perceptual bottom-up processes compensating for AD-related synaptic loss in the fronto-parietal networks.

The relationship between Event‐Related Potentials and MRI cortical atrophy in a memory disorders clinic

AbstractBackgroundThere is a need for accessible and affordable ways to assess biomarkers of Alzheimer’s disease (AD). Event‐related potentials (ERPs) are associated with disease severity of AD (Fruehwirt et al., 2019) and are a candidate biomarker for AD (Olichney et al., 2022). There is, however, little understanding of how ERP components relate to neurodegeneration of specific brain structures in AD.MethodWe investigated the correlation between electrophysiology, as measured by ERPs and brain structure using quantitative structural MRI measurements using FreeSurfer. A dataset containing older veteran memory disorders patients (N = 25) from VA Boston Healthcare System was analyzed. Participants completed an MRI and an auditory oddball task ERP paradigm.ResultAn exploratory analysis was performed using a Pearson correlation coefficient to evaluate the relationship between ERPs and the thickness and volume of different cortical areas. There was a negative relationship between P300 target amplitude and inferior temporal volume (p < .05), as well as P300 target latency and thickness of the superior temporal (p < .05) and transverse temporal regions (p < .01). P200 standard amplitude had a positive correlation with thickness in the middle temporal (p < .01), and superior temporal regions (p ≤ .05), and P200 target latency had a negative correlation with thickness of the superior temporal region (p < .05). N200 target amplitude had a negative correlation with the superior parietal volume (right hemisphere = p ≤ .05, left hemisphere = p ≤ .01), left inferior temporal volume (p ≤ .05), and the middle temporal volume (left = p ≤ .05, right = p ≤ .01). N200 target latency was negatively correlated with right superior parietal volume (p ≤ .05).ConclusionA correlation was found between ERP measures P200, N200 and P300 with cortical thickness and volume of areas that are commonly impacted by AD pathology, further substantiating use of ERPs as possible AD biomarkers. We conclude that ERPs provide insights as to structural changes of brain structures affected by AD pathology. ERPs could help inform areas of brain atrophy and related patterns of cognitive impairment.

Robust Radar Waveform Optimization Under Target Interpulse Fluctuation and Practical Constraints via Sequential Lagrange Dual Approximation

This correspondence considers the problem of robust radar waveform design against target interpulse fluctuation with constraints on the transmit energy, similarity, and signal dynamic range. We aim to make robust the transmit waveform and receive filter with respect to the Target Amplitude Vector (TAV) uncertainties by enhancing the worst-case Signal-to-Noise-Ratio (SNR) over the modeled ellipsoidal set. First of all, the filter is directly solved leveraging on the existence of saddle point condition, which leads to a suitable simplification of the original non-convex problem. Then, to handle the resultant max-min problem, the Sequential Lagrange Dual Approximation (SLDA) procedure is devised. Specifically, we update the transmit waveform via solving a sequence of max-min approximate problems, which are proven to be hidden convex relying on the theory of Lagrange duality. Finally, the filter is synthesized after solving a Quadratical Constraint Quadratic Programming (QCQP) problem based on the optimized waveform. Numerical results highlight the robustness of the proposed design which guarantees an enhanced worst-case SNR with respect to TAV uncertainties.

The use of Event Related Potentials to predict amyloid PET status among patients from a memory disorders clinic

AbstractBackgroundAmyloid PET scans provide in vivo evidence of Alzheimer’s Disease (AD) however, due to high cost and limited insurance coverage, they are not available as part of standard clinical care. Event Related Potentials (ERPs) are inexpensive, and non‐invasive method to directly measure brain physiology that may allow an alternative method for detection of AD pathology.MethodWe investigated whether ERPs together with neuropsychological data are predictors of amyloid PET status in patients with memory complaints. Older veterans aged 50‐100 were recruited from a memory disorders clinic at VA Boston Healthcare System. Participants underwent a standard neuropsychological battery and an ERP auditory oddball protocol. Twenty‐eight patients had a positive amyloid PET scan, and thirty‐nine patients had a negative amyloid PET scan.ResultsTwo neuropsychological measures (CERAD Delayed Recall and MMSE) were predictors of amyloid PET status. Increased P200 target amplitude (Figure 1B), and decreased P200 standard latency (Figure 1A) in patients with amyloid PET positive scan were found. ERP‐P200 amplitude in response to target tones and ERP‐P200 latency in response to standard tones were also predictors of amyloid PET status. The highest classification accuracy was obtained when combining CERAD Delayed Recall, MMSE and ERP‐P200 standard latency.ConclusionERP‐P200, especially when combined with cognitive measures of delayed memory and overall cognitive function, was predictive of amyloid beta (Aβ) load in the brain of patients from a memory disorder clinic. Increased P200 amplitude, and decreased P200 latency in patients with amyloid PET positive scan might suggest hyperactivation of perceptual bottom‐up processes to compensate for AD‐related synaptic loss in the fronto‐parietal networks.

Comparing Gaze, Head and Controller Selection of Dynamically Revealed Targets in Head-mounted Displays.

This paper presents a head-mounted virtual reality study that compared gaze, head, and controller pointing for selection of dynamically revealed targets. Existing studies on head-mounted 3D interaction have focused on pointing and selection tasks where all targets are visible to the user. Our study compared the effects of screen width (field of view), target amplitude and width, and prior knowledge of target location on modality performance. Results show that gaze and controller pointing are significantly faster than head pointing and that increased screen width only positively impacts performance up to a certain point. We further investigated the applicability of existing pointing models. Our analysis confirmed the suitability of previously proposed two-component models for all modalities while uncovering differences for gaze at known and unknown target positions. Our findings provide new empirical evidence for understanding input with gaze, head, and controller and are significant for applications that extend around the user.

Effects of target-amplitude and background-contrast uncertainty predicted by a normalized template-matching observer.

When detecting targets under natural conditions, the visual system almost always faces multiple, simultaneous, dimensions of extrinsic uncertainty. This study focused on the simultaneous uncertainty about target amplitude and background contrast. These dimensions have a large effect on detection and vary greatly in natural scenes. We measured the human performance for detecting a sine-wave target in white noise and natural-scene backgrounds for two levels of prior probability of the target being present. We derived and tested the ideal observer for white-noise backgrounds, a special case of a template-matching observer that dynamically moves its criterion with the background contrast (the DTM observer) and two simpler models with a fixed criterion: the template-matching (TM) observer and the normalized template-matching (NTM) observer that normalizes template response by background contrast. Simulations show that, when the target prior is low, the performance of the NTM observer is near optimal and the TM observer is near chance, suggesting that manipulating the target prior is valuable for distinguishing among models. Surprisingly, we found that the NTM and DTM observers better explain human performance than the TM observer for both target priors in both background types. We argue that the visual system most likely exploits contrast normalization, rather than dynamic criterion adjustment, to deal with simultaneous background contrast and target amplitude uncertainty. Finally, our findings show that the data collected under high levels of uncertainty have a rich structure capable of discriminating between models, providing an alternative approach for studying high dimensions of uncertainty.

Enhancing the quality of amplitude patterns using time-multiplexed virtual acoustic fields

Ultrasonic fields can push and levitate particles, heat up materials, induce contactless tactile stimuli, or affect the blood-brain barrier. Current phased-arrays can create dynamic amplitude patterns, but their quality may be insufficient due to the limited density of emitters. On the other hand, passive modulators can provide high quality, but only static patterns can be generated. Here, we show and evaluate how the average of multiple time-multiplexed amplitude fields improves the resolution of the obtained patterns when compared with the traditional single-emission method. We optimize the non-linear problem of decomposing a target amplitude field into multiple fields considering the limitations of the phased-array. The presented technique improves the quality for existing setups without modifying the equipment, having the potential to improve bio-printing, haptic devices, or ultrasonic medical treatments.

Effective implementation of text{L}{0}-regularised compressed sensing with chaotic-amplitude-controlled coherent Ising machines

Coherent Ising machine (CIM) is a network of optical parametric oscillators that can solve large-scale combinatorial optimisation problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et al., proposed a quantum-classical hybrid system to solve optimisation problems of l_0-regularisation-based compressed sensing. In the hybrid system, the CIM was an open-loop system without an amplitude control feedback loop. In this case, the hybrid system is enhanced by using a closed-loop CIM to achieve chaotic behaviour around the target amplitude, which would enable escaping from local minima in the energy landscape. Both artificial and magnetic resonance image data were used for the testing of our proposed closed-loop system. Compared with the open-loop system, the results of this study demonstrate an improved degree of accuracy and a wider range of effectiveness.

Fusion detection in distributed MIMO radar under hybrid-order Gaussian model

In this paper, we deal with the point-like target fusion detection in a partially homogeneous environment with distributed MIMO radar. Specifically, we consider the imperfect waveform separation problem, which means that the matched filter output contains not only the auto-correlation term of the current matched waveform but also the cross-correlation terms, called waveform residuals, with the remaining transmitted waveforms. To this end, a hybrid-order Gaussian (HOG) model is utilized, where the target amplitude is deterministic but unknown, and the waveform residuals obey the Gaussian distribution. Then two adaptive detectors are developed according to the GLRT and Wald test, named HOG-GLRT and HOG-Wald respectively. At the fusion detection stage, we focus on the problem of signal-to-noise ratio (SNR) diversity, i.e., the detection performance degradation due to the average weighting of spatial diversity channels when the echo SNR differs. Combined with the Model Order Selection criterion and multiple hypothesis test, two modified fusion detectors based on channel selection are proposed, named MHOG-GLRT and MHOG-Wald. Finally, the numerical simulation results show that the HOG-GLRT is sensitive against waveform residuals, while the HOG-Wald exhibits strong robustness. And it also demonstrates the effectiveness of the MHOG-GLRT and MHOG-Wald facing the extreme scene of SNR diversity.

A Modified OMP Method for Multi-Orbit Three Dimensional ISAR Imaging of the Space Target

The conventional two dimensional (2D) inverse synthetic aperture radar (ISAR) imaging fails to provide the targets' three dimensional (3D) information. In this paper, a 3D ISAR imaging method for the space target is proposed based on mutli-orbit observation data and an improved orthogonal matching pursuit (OMP) algorithm. Firstly, the 3D scattered field data is converted into a set of 2D matrix by stacking slices of the 3D data along the elevation direction dimension. Then, an improved OMP algorithm is applied to recover the space target's amplitude information via the 2D matrix data. Finally, scattering centers can be reconstructed with specific three dimensional locations. Numerical simulations are provided to demonstrate the effectiveness and superiority of the proposed 3D imaging method.

Complex amplitude field recovery of a scattering media obstructed object with multi-captured images.

An iterative-based method for recovering the complex amplitude field behind scattering media is presented in this Letter. This method compensates the random phase modulation of scattering media by using multiple captured scattered light fields. Complex amplitude reconstruction with local iterative averaging of scattered light fields, and double weighted feedback is efficiently applied. Two feasible types of system setups, with varying detector positions and wavelength, are proposed. Simulations and proof-of-concept experiments are employed to demonstrate the effectiveness of the proposed method in reconstructing complex amplitude of a hidden target.

Strength-duration properties and excitability of motor and sensory axons across different target thresholds.

The present series of studies aimed to investigate the biophysical basis underlying differences in behavior between motor and sensory axons at different target response levels. In 24 healthy individuals, axonal excitability protocols measured strength-duration properties and latent addition across several axonal populations, with target amplitudes set at 10%, 20%, 40%, and 60%. Strength-duration time constants (SDTCs) were typically longer at lower target levels for both motor and sensory axons. Threshold change at 0.2 ms during assessment of latent addition, representing a persistent Na+ current (Nap), was higher in sensory axons. Passive membrane properties were not different across target levels. Significant relationships were evident between the threshold change at 0.2 ms and SDTC across all target levels for motor and sensory axons. These differences were explored using mathematical modeling of excitability data. With decreasing target size, as the internodal leak conductance increased in sensory axons, the Barrett-Barrett conductance decreased, whereas the hyperpolarization-activated cation current (Ih) channels became more depolarized. A similar pattern was observed in motor axons. As such, it was concluded that Nap was not responsible for the differences observed in SDTC between different target levels, although within specific target levels, Nap changes contributed to the variability of SDTC. This study provides a comprehensive assessment of Nap current, SDTC, and outlines key factors operating at different target levels in motor and sensory axons. Findings from the present study may point to the contributing factors of symptom development in human neuropathy.NEW & NOTEWORTHY This study provides a comprehensive assessment concerning the strength-duration behavior of motor and sensory axons at differing target levels of the compound nerve response. Strength-duration time constant was increased at lower target response levels particularly for sensory axons, whereas threshold change at 0.2 ms and passive membrane properties were not different. The results have established templates for axonal behavior in normal human axons, demonstrating altered adaptive responses, presumably secondary to different patterns of nerve activation.

Spectrally matching pulse‐like records to a target RotD100 spectrum

AbstractThis article evaluates two different approaches to generate pulse‐like spectrally matched earthquake records pairs compatible with a target RotD100 spectrum. One is the conventional approach of separately matching each horizontal component to the target RotD100 spectrum, the other approach simultaneously modifies both horizontal components to tightly match the target RotD100. The characteristics of the resulting records are evaluated using amplitude scaled pulse records as baseline for comparison. It is shown that, using a target spectrum that includes a narrow‐band modification to accommodate the presence of a pulse, largely increases both methodologies likelihood of generating spectrally matched records that preserve the pulse‐like nature of the seeds. However, the records generated through independent component matching exhibit RotD100 spectral amplitudes that largely surpass the target amplitudes, and instantaneous power (IP) and peak ground velocities (PGV) substantially larger than the observed for the amplitude scaled records. Consequently, these motions generated unrealistically large inelastic demands when used as input for nonlinear response history analyses (NRHA), with mean peak inelastic demands up to 60% larger than the expected from amplitude scaled records. Conversely, the approach based on simultaneous modification of the two horizontal components generated the largest number of successful matches and the resulting records exhibited IP and PGV values close to the obtained for the amplitude scaled records. When used as input for NRHA, the mean peak inelastic demands were very close to the demands imposed by the amplitude scaled set. These results suggest that current 10% spectral amplitude penalization for spectrally matched records in ASCE7 is unnecessary for pulse‐like motions.

Waveform design for higher-resolution localization with MIMO radar

To improve the accuracy and resolution of angle estimation with multiple signal classification (MUSIC) algorithm, we study the design of low peak-to-average-power-ratio waveforms for multiple-input-multiple-output (MIMO) radar. Assuming that the prior knowledge about the target directions and amplitudes is available (e.g., by transmitting initial probing waveforms), we formulate a waveform design problem based on minimizing the asymptotic mean square error of MUSIC. An alternating direction method of multipliers is developed to tackle the encountered nonconvex optimization problem. Compared with the competing waveforms, the waveforms designed by the proposed algorithm exhibit higher resolution and lower estimation error.

Cues to reduce modulation informational masking.

The detectability of target amplitude modulation (AM) can be reduced by masker AM in the same carrier-frequency region. It can be reduced even further, however, if the masker-AM rate is uncertain [Conroy and Kidd, J. Acoust. Soc. Am. 149, 3665-3673 (2021)]. This study examined the effectiveness of contextual cues in reducing this latter, uncertainty-related effect (modulation informational masking). Observers were tasked with detecting fixed-rate target sinusoidal amplitude modulation (SAM) in the presence of masker SAM applied simultaneously to the same broadband-noise carrier. A single-interval, two-alternative forced-choice detection procedure was used to measure sensitivity for the target SAM; masker-AM-rate uncertainty was created by randomly selecting the AM rate of the masker SAM on each trial. Relative to an uncued condition, a pretrial cue to the masker SAM significantly improved sensitivity for the target SAM; a cue to the target SAM, however, did not. The delay between the cue-interval offset and trial-interval onset did not affect the size of the masker-cue benefit, suggesting that adaptation of the masker SAM was not responsible. A simple model of within-AM-channel masking captured important trends in the psychophysical data, suggesting that reduced masker-AM-rate uncertainty may have played a relatively minor role in the masker-cue benefit.

Performance evaluation of online motion synchronizing systems for patient-specific respiratory movements with helical tomotherapy

Background and purpose. The introduction of online motion synchronizing system on helical tomotherapy paves way for robust motion tracking. A recent upgrade launches modifications on both hardware and software of the kV tracking system. An evaluation on the kV subsystems, prior (Version1) and post upgrade (Version2), was performed to compare tracking accuracy by means of fiducial tracking error and resulted root-mean-square (RMS). Impacts influenced by various patient-specific breathing pattern regularities and target movements were also investigated to refine motion tracking error estimations upon future selection of possible candidates. Materials and methods. Respiratory patterns from twenty-five lung cases were imported individually into a commercial dynamic platform model. Situating a phantom implanted with gold fiducial markers on the platform, superior-inferior (SI) movements of corresponding targets were simulated. Each case was delivered via an identical treatment plan in Version1 and was repeated in Version2. Motion tracking accuracy, by means of discrepancies between subsystem predicted model and raw data motion recorded in patient CT simulation, was analyzed statistically. Wilcoxon signed ranked test was employed to evaluate the difference in tracking error range between the two versions. Statistical model was fitted to inspect the dependence of internal target movement towards fiducial tracking errors. Results. A small difference of ±1 mm was exhibited in 99% of fiducial tracking errors for all cases experimented under both versions. RMS errors were all below 0.5 mm. Version2 demonstrated a greater extremity in fiducial tracking error (p = 0.04). A positive correlation was depicted between internal target amplitudes and 95% interval of fiducial tracking errors (p < 0.02). Overall, irregular respiratory patterns tended to have greater fiducial tracking errors. Conclusions. The excellent tracking performance in both kV subsystem versions offers motion compensations benefits, yet Version1 outperformed Version2 in fiducial tracking accuracy. It is noticeable that greater magnitude in internal target movement and irregular breathing patterns yield greater tracking error.

An image-driven model for pattern detection, resistant to Birdsall linearisation

If detection were governed by an isolated (and possibly nonlinear) transducer, then a linearisation of the psychometric function (d-prime vs target amplitude) must accompany any threshold elevation due to the addition of external noise. This is the Birdsall theorem. From the fact that noise can elevate threshold without linearising the psychometric function, we can safely infer that detection is not governed by an isolated transducer. Heretofore, image-driven models, which accept images or numerical descriptions thereof as input, have proven incompatible with this failure of Birdsall linearisation, unless they incorporate the principle of intrinsic uncertainty, which asserts that detection is governed by the maximum activity in several independent (noisy) sensors. One image-driven model incompatible with the failure of Birdsall linearisation is Watson and Solomon’s (J. Opt. Soc. Am. A, 14 (1997), 2379) model of visual contrast gain control and pattern masking. Here I report a simple modification – pooling sensor outputs before, instead of after the comparison of input images – allowing that model to predict curved psychometric functions, even when external noise elevates threshold by more than 20 dB, without any detrimental effect to the quality of its fit to pattern-masking thresholds in the absence of noise. The failure of Birdsall linearisation, therefore, does not necessarily imply independent samples of performance-limiting noise in multiple visual sensors. Instead, performance-limiting noise may arise after the visual system combines output from mutually inhibitory sensors.