Multi-frequency Signal Research Articles

Stress Online Monitoring Method Based on Multifrequency SH0 Guided Wave Information Fusion

This article proposes a stress monitoring technique based on multifrequency SH0 guided wave information fusion. Its nondispersive acoustoelastic characteristic facilitates joint analysis in the whole frequency band. Moreover, the typical representation of broadband multifrequency signal is equivalent to realizing multiple measurements simultaneously, effectively improving the measurement efficiency and reliability. First, a generalized multifrequency comprehensive measurement model is established, which combines with specific data analysis and postprocessing criteria to construct a new stress characterization method. Then, the acoustoelastic effect of SH0 guided wave is investigated. Next, the wideband shear piezoelectric transducer based on the out-of-plane d15 mode is designed. The frequency-domain finite-element method (FDFEM) is applied to optimize the SH0 guided wave excitation and reception interval. Finally, the laboratory experiments of 6061-T6 aluminum plates with a thickness of 1 mm are conducted to verify the proposed strategy. The fitting result of multifrequency component fusion is better than that of any single-frequency algorithm. The actual measurements from the same batch are carried out through the calibration results. The maximum error does not exceed 2.5 MPa and the maximum relative standard deviation (RSD) is 7% in the range of 15–85 MPa, demonstrating good measurement accuracy and consistency.

Quantitative detection of multi-frequency disturbance signal by ϕ-OTDR system

Recently, the combination of pattern recognition technology and distributed fiber sensing systems has become increasingly common, so whether the disturbance signal can be well recovered has become increasingly important. To verify the recovery and linear response of a distributed fiber optic sensing system to multi-frequency disturbance signals, a heterodyne coherent detection system for phase-sensitive optical time-domain reflectometry is developed. The output beat signal is extracted using the digital in-phase/quadrature demodulation algorithm. The signal can be precisely located on a 7 km length range, and the disturbance signal can be restored well through the phase information. Not only the superposition signal composed of the same signal but also that composed of different kinds of signals can be successfully restored. A fast Fourier transform algorithm is used to obtain the frequency information of the superimposed signal. Combined with the use of a finite impulse response filter, the superposed signal is decomposed according to its frequency components, which perfectly restores the two signals before they are superimposed. In addition, their amplitude is highly linear with the driving voltage of the piezoelectric transducer. The system can fully retain the details of each frequency component in the recovery of multi-frequency disturbance signals. More importantly, in field experiments, the disturbance behavior is well recovered, which has broad prospects in the application of perimeter security.

Enhanced precise orbit determination of BDS-3 MEO satellites based on ambiguity resolution with B1C/B2a dual-frequency combination

Broadcasting the multi-frequency signals is one of the outstanding advantages of BDS-3 (BeiDou Navigation Satellite System). In addition to the legacy signals B1I and B3I, we are interested in the performance of two new signals B1C and B2a. For the purpose of improving the orbit accuracy of BDS-3 backbone MEOs (Medium Earth Orbits), this study focuses on Precise Orbit Determination (POD) using B1C/B2a dual-frequency measurements. First, the performance of POD will be benefit from an increasing observation quantity and qualities. Observations from the public MGEX (Multi-GNSS Experiment) network are statistically collected, and the number of stations able to track B1C and B2a signals is analyzed. In recent years, the sustainable growth number of stations is up to more than one hundred, which brings the new chance to improve the POD accuracy based on B1C/B2a linear combination. Then, the multipath and post-fit residuals of observations are compared between B1C/B2a and B1I/B3I to investigate the observation qualities. Second, as a key strategy, the ambiguities are successfully fixed during POD processing of BDS-3 MEOs. The ambiguity fixing percentage is as high as 93.1% on average using B1C/B2a combination. Compared with float solutions, the improvements of ambiguity fixed orbits reach 36.2%, 19.9% and 36.6% on the radial, along-track and cross-track components, respectively. For the fixed solutions of B1I/B3I and B1C/B2a, it is noticed that the orbits achieve further benefits from B1C/B2a combination for 8.4%, 6.9% and 8.0% on the radial, along-track and cross-track components, respectively. Finally, the performance of B1C/B2a combination POD is validated by orbital overlapping, the orbit signal-in-space range error (SISRE) analysis, independent technology Satellite Laser Ranging (SLR) and Precise Point Positioning (PPP), respectively. SLR residuals show the radial orbital accuracy has an improvement of 8.0% for C20, C21, C29 and C30 on average when employing B1C/B2a measurements. Compared with B1I/B3I, both static and kinematic PPP based on B1C/B2a orbits indicate the improvement on the vertical component. And a faster and more stable convergence performance is also observed using B1C/B2a combination.

Broadband optical frequency comb generation based on single electro-absorption modulation driven by radio frequency coupled signals

Broadband optical frequency comb (OFC) generation based on a single electro-absorption modulator (EAM) is proposed. The EAM is driven by a radio frequency (RF) multi-frequency signal generated by a multiplication coupler composed of an electrical power splitter and an arithmetic circuit. Thus the number of comb-lines of the generated OFC can be increased. A complete theoretical model of OFC generation by an EAM driven by nth power of the RF source is established, and the performance of the OFC is analyzed by using OptiSystem software. The results show that, the number of comb-lines of the OFC is positively correlated with the number of multiplication of the RF source signal. The frequency spacing of the comb-lines is twice the frequency of the RF source signal and is tunable by adjusting the frequency of the RF source signal. Increasing chirp factor and modulation index of EAM could increase the number of comb-lines of the generated OFC. The amplitude of the RF source signal had little impact on the flatness of the OFC and the average OFC power. The scheme developed is not only simple and low-cost, but also can produce a large number of comb-lines.Graphical

A mixed multi-frequency precise point positioning strategy based on the combination of BDS-3 and GNSS multi-frequency observations

Due to the traditional fixed model used in precise point positioning (PPP) solutions, multi-frequency and multi-Global Satellite Navigation System (GNSS) observations have not been fully introduced into positioning services. In consideration of the BDS-3 multi-frequency signals and the new development of other GNSS systems, a new multi-frequency and multi-GNSS PPP solution strategy should be proposed to flexibly model and use all observations. In this study, a preliminary mixed multi-frequency PPP solution strategy is analyzed and tested based on a combination of BDS-3 and GNSS observations. First, the multi-frequency observations are combined and their coefficients are rapidly estimated by least squares; then, the inter-system bias parameter and the stochastic model are introduced into the function model; and finally, the mixed PPP solution and its software are developed and verified by three groups of experiments. According to the experimental results of 96 stations and ten-day multi-GNSS experiment observations, it is indicated that the root-mean-square error of positioning and the convergence time are significantly optimized with the aid of additional frequencies, where the accuracy improvements of multi-frequency and multi-GNSS scheme in the east (E), north (N) and up (U) directions can respectively reach up to 23.2%, 13.3% and 23.8% compared with the traditional BDS-3 dual-frequency ionosphere-free (IF) PPP model; and the corresponding convergence time is reduced from 18.54 min to 13.18 min. Meanwhile, from the results of multi-frequency BDS-3 PPP experiments based on 53 stations, it is suggested that a better performance of positioning and convergence can be obtained by the mixed PPP solution, where the position RMS of the E, N and U directions are reduced by 38.2%, 23.9% and 26.3%, and the convergence time is decreased from 23.86 min to 12.43 min for the combined BDS-3 of all observations, compared with the BDS-3-only solution. Furthermore, in the vehicle experiment of multi-frequency kinematics PPP, a convergence process can be found for different scenarios of BDS-3 combination with other observations. Moreover, the residual series are different for each solution, in which reductions of 71.1%, 33.3% and 77.1% in the E, N and U directions, respectively, can be obtained compared with the traditional BDS-3 dual-frequency IF model in kinematics experiments based on multi-GNSS and multi-frequency scenarios. Therefore, it is meaningful to recommend the mixed PPP solution in the GNSS community to fully use multi-frequency and multi-GNSS observations by the adaptive combination of different observations.

A Switched Planar Multicoil Transmitter Antenna Designed With Nonuniform H-Field Forming for Small Device Localization

To monitor 3-D position and orientation of a small device having planar receiver (Rx) coil, a switched multicoil transmitter (Tx) antenna is proposed by adopting time-divisional approach. The existing multifrequency methods require eight or more input ports to feed the coils with multifrequency signals for localization. In contrast, the proposed Tx antenna is driven by a single frequency source and uses only three input ports for reduced complexity. Moreover, the multiple coils of the proposed antenna are optimally grouped to form nonuniform magnetic-field distribution using three switches (SWs) in such a manner that better localization accuracy is achieved as compared to the multifrequency design. Rigorous analysis and simulations are performed to investigate the performance of the proposed design and localization approach. To validate the claim, experimental study results proved the potential of the proposed antenna employed for tracking a planar Rx in applications like medical robots, navigation of people with limited vision, virtual reality, etc.

Multiparty quantum anonymous voting with discrete modulated coherent states and an optical frequency comb.

A key challenge for quantum information science is to realize large-scale, precisely controllable, practical systems for multiparty secure communications. Recently, Guidry etal. [Nat. Photonics16, 52 (2022)10.1038/s41566-021-00901-z] have investigated the quantum optics of a Kerr-based optical frequency comb (OFC), which lays out the way for OFC acting as a quantum resource to realize a low-cost and stable multiparty continuous-variable quantum information processing. In this work, we propose a distributed quantum anonymous voting (DQAV) protocol based on discrete modulated coherent states, in which a Kerr-based OFC serves as the resource to generate multi-frequency quantum signals for multiparty voting. We consider both the single-selection and multiple-selection ballot scenarios, and design the phase compensation method for the OFC-based protocol. Voting security is ensured by the basic laws of quantum mechanics, while voting anonymity is achieved by the random assignment of different frequency sources and the homogeneity of the quantum operations taken on the same voting choice. Numerical analysis calculates the secure voting distance over the thermal-lossy channel, showing the advancement of the proposed protocol under multiparty and multivalued voting tasks.

Temporal Disentanglement of Wireless Signal Carriers Based on Quasi-Light-Storage

High-speed communication systems mandate instantaneous microwave frequency measurement for an efficient utilization of the available spectrum. We propose and experimentally demonstrate a novel, real-time microwave frequency measurement approach based on the time-frequency coherence representation of each signal. The temporal discrimination between the spectral components of the incoming microwave signal is realized through the harnessing of stimulated Brillouin scattering-based quasi light storage (QLS). The QLS is achieved by equidistant sampling of a signal spectrum. Consequently, several copies of that signal will be produced in the time domain and can be discriminated from other spectral components. By tuning the central frequency of the comb, the proposed method is fully reconfigurable and feasible for centimeter, millimeter and even THz signals. Here, we present simultaneous discrimination of single and two frequency components of multi-frequency microwave signals. Since the method can be integrated and supports real-time processing, it might become an integral part for efficient bandwidth usage in future wireless communication systems.

Crest Factor Optimization for Multisine Excitation Signals with Logarithmic Frequency Distribution Based on a Hybrid Stochastic-Deterministic Optimization Algorithm

For diagnosis of batteries and fuel cells based on impedance spectroscopy, excitation signals are required, including low frequencies down to the mHz range. This leads to a long measurement time and compromises the stability condition for impedance spectroscopy. Multisine excitation signals with logarithmic frequency distribution can significantly reduce the measurement time but need optimization of the crest factor to realize a high signal-to-noise ratio at all excitation frequencies and maintain at the same time the linearity and stability conditions of impedance spectroscopy. Crest factor optimization is challenging, as the obtained results strongly depend on the initial phase values and many trials are necessary. It takes a very long time and can not be easily performed automatically up to now. In this paper, we propose a time-efficient hybrid stochastic-deterministic crest factor optimization method for multisine signals with logarithmic frequency distribution. A sigmoid transform on the multisine signal gradually transforms the multi-frequency signal into a binary-alike signal. The crest factor is significantly decreased, but the phases of the singular frequency signals remain sub-optimal. Further optimization based on the Gauss-Newton algorithm can determine the final phases, realizing a lower crest factor. The proposed method is less sensitive to initial phase values and provides more reasonable results in a reasonable time. The validation on a Samsung INR-18650-25R Lithium-ion battery cell shows that the crest factor of the optimized multisine signals has a median of 3.62 ± 0.7 within 6 min of run time, which is significantly better than the best previous work in the state-of-the-art of 3.85 ± 0.11 for the same run time.

Hygienic Assessment of Population Health Effects of Cellular Base Stations: A Literature Review

Introduction: A cellular base station is a sophisticated object, a source of radio and industrial frequency electromagnetic fields and of noise pollution. Cell sites generate a complex, time-varying, modulated multi-frequency signal of low intensity, yet having local gradients. The World Health Organization has introduced the notion of electromagnetic pollution of environment, the main source of which is a mobile phone base station. It is the fastest-growing anthropotechnogenic environmental impact since the 1950s. Objective: To analyze the impact of mobile phone base stations on the health of population using data of domestic and foreign literary sources. Materials and methods: A literature search was conducted for the years 2008 to 2022 on human health effects of radiofrequency electromagnetic radiation from cellular base stations using the relevant keywords in the PubMed, Scopus, Web of Science, Medline, the Cochrane Library, EMBASE, Global Health, CyberLeninka, RSCI, and other databases. The initial sample included 50 articles, of which 15 were excluded after primary screening. Experimental studies on animals were not eligible for inclusion. Results: The review of 35 full-text publications on the topic revealed a sufficient amount of evidence of adverse health effects of radiofrequency electromagnetic fields, including the radio frequency sickness, cancer, changes in biochemical parameters, DNA damage, etc. Currently, there is an urgent need to resolve the problem of the so-called electrosmog. Conclusion: In order to prevent the diseases associated with the use of novel technologies, it is important to apply a preventive approach by limiting the exposure of groups at risk, such as children, adolescents, patients with chronic diseases etc., to sources of radiofrequency electromagnetic fields.

INCREASING THE RELIABILITY OF THE LOW STRAIN INTEGRITY TESTING OF PILES UNDER EXISTING STRUCTURES

Inspection of piles located under the pile cap or an existing building is a common task in the practice of capital construction. The low strain impact testing allows us to estimate the pile length and the presence of defects in its body. This provides designers and builders with information on structures, which can be considered when planning the further operation of the foundation. Improving the reliability of test results for examining piles under cap is the issue of interest. On the example of field test results, the application of the multifrequency signal excitation during data collection and the wavelet analysis of signals during data processing are shown.

Photonic approach for precise and efficient distance measurement via utilization of multi-frequency broadband optical carrier-based microwave signal

Distance measurement has received a growing demand with the development of scientific research and modern industry. However, most of the high-precision measure approaches hold stringent requirements on hardware equipment, manufacture accuracy, and operation environment. In this article, a photonic approach for distance measurement that utilizes broadband optical carrier-based microwave signal is proposed. Through switching between multiple modulation frequencies and applying the heterodyne process, a series of synthetic frequencies is constructed. Phase extraction is achieved based on all-phase fast Fourier transform (apFFT) for derivation of the distance. Moreover, we develop a phase unwrapping procedure to resolve phase ambiguity and derive the corresponding criterion for evaluation of reliability. The proposed method can realize tunable measurement range and high resolution within a relatively narrow bandwidth. Experiments verify the feasibility for distance measurement and align well with theoretical analysis. The results show good accuracy and stability with relative errors lower than 0.05%. Discussion demonstrates that apFFT is capable to suppress spectral leakage and mitigate the influence of signal truncation. As the presented approach maintains a simple configuration and competitive performance, it has great potential to become a useful tool for distance measurement in various practical applications.

Variational Mode Decomposition-based Synchronous Multi-Frequency Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) can perform non-invasive, low-cost, safe, fast, and simple system structure and functional imaging to map the distribution and changes of root zone. Multi frequency EIT solves the problem that single-frequency EIT can only carry more impedance information than a given single excitation frequency. It still remains challenges to simultaneously obtain multi-frequency electrical impedance tomography. To address the problem, a mixed signal superimposed by multiple frequencies is injected to the object. Essentially, separating the measured mixed voltage signals, which can be used to obtain electrical impedance information at different frequencies at the same time quickly. Since the measurement signal is a multi-frequency signal, the effect of decomposing the multi-frequency signal directly affects the accuracy of imaging. In order to obtain more accurate data, this article used the variational mode decomposition (VMD) method to decompose the measured multi-frequency signal. Accurate amplitude and phase information could be obtained simultaneously at the same time in multi-frequency excitation, and these data could be used to reconstruct electrical impedance distribution The results showed that the proposed method can achieve the expected imaging effect. It was concluded that using the variational modal decomposition method to process the data of multi-frequency signals is more accurate and the imaging effect is better, and it can be applied to multi-frequency electrical impedance imaging in practice.

Stochastic resonance: The response to envelope modulation signal for neural networks with different topologies

Neurons receive complex multiple signals from different regions in the biology system, and the neuron information carried by the multi-frequency signals can be detected by the neural system. Noise can induce stochastic resonance and promote the response of the neural network to a weak signal. The responses to weak envelope modulation signals for the neural networks with different topologies are investigated under electromagnetic induction and Gaussian white noise. We analyze and compare the stochastic resonance with tuning system parameters. The results show that in the three different networks, network systems exhibit double resonance with the variation of noise and beat frequency. Appropriate noise and electromagnetic induction can promote the generation of stochastic resonance and affect the response of envelope modulation signal in the neural network. The difference is that the three different networks differ in the noise intensity required to induce stochastic resonance and the effective range of the electrical coupling strength. Unlike the other two networks, the Fourier coefficient in scale-free network increases with the electromagnetic induction, and the number of neurons has no affect on stochastic resonance. Our results are conducive to understanding the mechanism of stochastic resonance in envelope modulation signals and electromagnetic induction.

A Novel Improved Threshold Adaptive Forgetting Variable Step Size Blind Separation Model for Weak Signal Detection

The online blind source separation (BSS) is seriously disturbed by strong noise when extracting weak signals and has the defects that it cannot both give consideration to convergence speed and steady-state error. In order to solve the abovementioned problems, a novel improved threshold adaptive forgetting variable step size blind separation model (ITAFBS) for weak signal detection is proposed. Firstly, an improved lifting wavelet transform (ILWT) is proposed to reduce the noise of weak signals. In ILWT, a threshold function containing an adjustment factor is proposed to reduce the constant deviation so as to ensure a high signal-to-noise ratio and low distortion after denoising. Then, the separation index (SI) is constructed according to the convergence conditions of the BSS model. An adaptive variable step size blind separation model based on the SI is studied. At the initial stage of separation, the step size is increased to obtain a fast convergence rate, and at the end of separation and the step size is shortened to obtain a small steady-state error. Finally, the forgetting factor is introduced into the model to reduce the error accumulation in the early stage of the algorithm, and the Fourier norm is introduced to improve the convergence speed and separation accuracy of the model. The simulation and experimental results show that ITAFBS has a good performance in multi-frequency weak signal detection. Compared with other methods, the ITAFBS has a faster convergence speed and minimum steady-state error.

Toward BDS/Galileo/GPS/QZSS triple-frequency PPP instantaneous integer ambiguity resolutions without atmosphere corrections

Multi-frequency precise point positioning (PPP) has drawn attention along with the modernization of the Global Navigation Satellite Systems. There are now nearly 90 satellites providing multi-frequency signals. This contribution aims to achieve fast convergence of a few seconds for BDS/Galileo/GPS/QZSS integrated triple-frequency PPP with integer ambiguity resolution (IAR) without atmosphere corrections. A unified model of an uncombined and undifferenced manner for PPP-IAR with dual- and triple-frequency observations is presented. The uncalibrated phase delays (UPD) of extra wide-lane (EWL), wide-lane (WL), and N1 ambiguities for triple-frequency PPP are estimated with standard deviations of 0.02, 0.05, and 0.10 cycles achieved, respectively. The PPP-IAR validation based on 20 stations evenly distributed in China is conducted using UPD products generated from a regional network covering a large part of China. The EWL, WL, and N1 ambiguities are sequentially fixed utilizing the least-squares ambiguity decorrelation adjustment (LAMBDA) technique. In terms of convergence time, PPP instantaneous IAR is achievable without using atmosphere corrections, thanks to the contribution of the multi-frequency and multi-constellation observations. This has been proved by performing PPP-IAR restart every 10-min over 2520 times in our case study. For PPP-IAR solutions produced with BDS/Galileo/GPS/QZSS triple-frequency observations with an interval of 1 s, the convergence is fulfilled within 1 s for the horizontal components with an accuracy of better than 5 cm, while 2 s for the vertical component with better than 10 cm accuracy, and both are at 95% confidence level.

Modeling and performance assessment of precise point positioning with multi-frequency GNSS signals

The development of global navigation satellite system (GNSS), especially BeiDou-3 Navigation Satellite System (BDS-3) and Galileo system, promotes the progress of the precise point positioning (PPP) technology. Considering deep integration and full utilization of GNSS signals, this study dedicates to developing three triple-frequency PPP models apply to multi-constellation including BDS-3. Besides, some biases such as differential code bias (DCB), inter-frequency bias (IFB) and inter-system bias (ISB) are also addressed. Through the ten-day datasets collected from 160 stations, the multi-frequency PPP models for single- and multi-constellation solutions are analyzed and compared from static positioning performance, Zenith Tropospheric Delay (ZTD) estimates, ISB estimates, and IFB estimates. The results indicate that the triple-frequency PPP models, especially two dual-frequency ionosphere-free (IF) model namely TIF with triple-constellation which can provide the positioning accuracy of 4.89, 7.31, 12.1 mm after the convergence time of 10.75 min in east, north and up directions, perform better than the dual-frequency model, apart from the a single IF model with GPS. Interestingly, the positioning performance is not effectively improved with the addition of GLONASS constellation. But the performance of GAL/BDS combined constellation is comparable to GPS single constellation in TIF model.

EMD-based time–frequency denoising algorithm for the self-sensing of vibration signals in ultrasonic-assisted grinding

An empirical mode decomposition (EMD)-based time–frequency denoising algorithm is derived in this paper to accomplish the extraction of active ingredients for multi-frequency mixed signals, and then the self-sensing of vibration signals is realized without additional sensors for an ultrasonic-assisted grinding device. EMD is employed to accomplish the signal decomposition, and multiple intrinsic mode function components and the residual are obtained. Then, the weighted factors used for signal reconstruction are obtained based on innovation statistical distance, which is selected as a criterion to evaluate the time–frequency domain correlation between decomposition results and the original signal. Next, the maximum correntropy criterion-based similarity detection method is designed to adaptively modify the weighted factors, and the signal is reconstructed on the foundation of the modified weighted factors. Finally, numerical simulations and a self-sensing experiment are conducted to verify the denoising performance of the proposed algorithm. The self-sensing of the 4.59 dB vibration signal is realized for an ultrasonic-assisted grinding device.

Fault Size Estimation of Bearings Using Multiple Decomposition Techniques with Artificial Neural Network

A running machine generates multi-frequency vibration signals which can be captured by accelerometers. Empirical mode decomposition, wavelet decomposition, and wavelet packet decomposition are the commonly used methods to decompose the multi-frequency signal. Quick fault classification, accurate signal decomposition, and fault size detection are still a problem in machines with rotary components. In the proposed work, fault diameter in rotary part of machine is detected and classified using the machine learning methods. In the first stage, we have employed empirical mode decomposition (EMD) for high-frequency noise removal. Residue signal is obtained by removing first IMF from base signal considering first IMF as a high-frequency noisy signal, followed by wavelet decomposition. Entropy of the wavelet coefficient obtained from 3rd level decomposition of residue signal is calculated which acts as an input parameter to the machine learning techniques to determine the diameter for fault. Three different sets have been taken for inner race, outer race, and ball race correspondingly. The proposed method classifies and detects the fault diameter up to 99.5%. The proposed method can be used for different types of continuous as well as discrete wavelets.

Iterative reconstruction with multifrequency signal recognition technology to improve low-contrast detectability: A phantom study.

BackgroundBrain CT needs more attention to improve the extremely low image contrast and image texture.PurposeTo evaluate the performance of iterative progressive reconstruction with visual modeling (IPV) for the improvement of low-contrast detectability (IPV-LCD) compared with filtered backprojection (FBP) and conventional IPV.Materials and methodsLow-contrast and water phantoms were used. Helical scans were conducted with the use of a CT scanner with 64 detectors. The tube voltage was set at 120 kVp; the tube current was adjusted from 60 to 300 mA with a slice thickness of 0.625 mm and from 20 to 150 mA with a slice thickness of 5.0 mm. Images were reconstructed with the FBP, conventional IPV, and IPV-LCD algorithms. The channelized Hotelling observer (CHO) model was applied in conjunction with the use of low-contrast modules in the low-contrast phantom. The noise power spectrum (NPS) and normalized NPS were calculated.ResultsAt the same standard and strong levels, the IPV-LCD method improved low-contrast detectability compared with the conventional IPV, regardless of contrast-rod diameters. The mean CHO values at a slice thickness of 0.625 mm were 1.83, 3.28, 4.40, 4.53, and 5.27 for FBP, IPV STD, IPV-LCD STD, IPV STR, and IPV-LCD STR, respectively. The normalized NPS for the IPV-LCD STD and STR images were slightly shifted to the higher frequency compared with that for the FBP image.ConclusionIPV-LCD images further improve the low-contrast detectability compared with FBP and conventional IPV images while maintaining similar FBP image appearances.