Asynchronous Measurement Research Articles

Distributed Consensus Filtering Over Sensor Networks With Asynchronous Measurements

ABSTRACTIn practical sensor networks, sensor nodes may operate with different sampling periods and initial sampling time instants, and their observations may also be nonuniform. Unfortunately, the research on distributed state estimation problems over such asynchronous sensor networks is very limited. Thus, this article focuses on the distributed consensus filtering problem over sensor networks with asynchronous measurements. First, the asynchronous measurement from each sensor is synchronized by the continuous‐time state evolution equation to a unified filtering fusion time instant within a given filtering period. After measurement synchronization, the statistical characteristics of measurement noise change. The cross‐correlations between the converted measurement noises are analyzed, as well as one‐step correlations between the converted measurement noises and the process noise. Second, an optimal asynchronous distributed consensus filter is designed based on synchronization measurements under the criterion of minimum mean‐square error with the above correlations between various types of noises taken into account. Meanwhile, a suboptimal distributed consensus filtering algorithm is further proposed to reduce computational complexity. Finally, based on the Lyapunov function method, the stability of the estimation error is theoretically demonstrated with an appropriate selection of consensus filtering gain and validated through simulations.

Multi-visual-inertial system: Analysis, calibration, and estimation

In this paper, we study state estimation of multi-visual-inertial systems (MVIS) and develop sensor fusion algorithms to optimally fuse an arbitrary number of asynchronous inertial measurement units (IMUs) or gyroscopes and global and/or rolling shutter cameras. We are especially interested in the full calibration of the associated visual-inertial sensors, including the IMU/camera intrinsics and the IMU-IMU/camera spatiotemporal extrinsics as well as the image readout time of rolling-shutter cameras (if used). To this end, we develop a new analytic combined IMU integration with inertial intrinsics—termed ACI3—to pre-integrate IMU measurements, which is leveraged to fuse auxiliary IMUs and/or gyroscopes alongside a base IMU. We model the multi-inertial measurements to include all the necessary inertial intrinsic and IMU-IMU spatiotemporal extrinsic parameters, while leveraging IMU-IMU rigid-body constraints to eliminate the necessity of auxiliary inertial poses and thus reducing computational complexity. By performing observability analysis of MVIS, we prove that the standard four unobservable directions remain—no matter how many inertial sensors are used, and also identify, for the first time, degenerate motions for IMU-IMU spatiotemporal extrinsics and auxiliary inertial intrinsics. In addition to extensive simulations that validate our analysis and algorithms, we have built our own MVIS sensor rig and collected over 25 real-world datasets to experimentally verify the proposed calibration against the state-of-the-art calibration method Kalibr. We show that the proposed MVIS calibration is able to achieve competing accuracy with improved convergence and repeatability, which is open sourced to better benefit the community.

Measurement insights and error analysis of electronic parameters for ultrasonic transducers

Abstract Piezoelectric ultrasonic transducers with the function of energy conversation, as well as their numerous advantages in high-power density, quick response, flexible design, and service reliability, are involved in wide applications of industrial processing, precision driving, smart sensing, and medical services. The electromechanical equivalent circuit and Kirchhoff’s law indicate that mechatronics parameters are essential for performance evaluation, reliability analysis, and fault diagnosis of ultrasonic transducers. Importantly, the ultrasonic transducer is a time-variant system, data of one single parameter collected from a certain test cannot match with the data of another single parameter acquired from a different test. So, a synchronous and precise online measurement of electronic parameters is encouraged for performance evaluation and optimization design of ultrasonic transducers. With the combination of virtual instrument technology, an asynchronous measurement system of electrical excitation parameters for the ultrasonic transducers of linear driving motors was established in this study. Furthermore, the systematic measurement methods and error theory were illustrated, including the calculation methods and measuring circuits of electric signals. Experimental results proved that the proposed system and methods for measuring the input electronic power of ultrasonic transducer (e.g. effective value method for voltage and current, energy moment method for frequency, and spectrum analysis method for phase difference) are highly precise, quickly responsive, robust, and reliable for ultrasonic transducers. The findings of this study provide valuable references and suggestions for efficient, accurate, and online performance evaluation of ultrasonic transducers, particularly for piezoelectric transducers utilizing ultrasonic high-voltage exciting signals.

Chaff Cloud Integrated Communication and TT&C: An Integrated Solution for Single-Station Emergency Communications and TT&C in a Denied Environment

In response to potential denial environments such as canyons, gullies, islands, and cities where users are located, traditional Telemetry, Tracking, and Command (TT&C) systems can still maintain core requirements such as availability, reliability, and sustainability in the face of complex electromagnetic environments and non-line-of-sight environments that may cause service degradation or even failure. This paper presents a single-station emergency solution that integrates communication and TT&C (IC&T) functions based on radar chaff cloud technology. Firstly, a suitable selection of frequency bands and modulation methods is provided for the emergency IC&T system to ensure compatibility with existing communication and TT&C systems while catering to the future needs of IC&T. Subsequently, theoretical analyses are conducted on the communication link transmission loss, data transmission, code tracking accuracy, and anti-multipath model of the emergency IC&T system based on the chosen frequency band and modulation mode. This paper proposes a dual-way asynchronous precision ranging and time synchronization (DWAPR&TS) system employing dual one-way ranging (DOWR) measurement, a dual-way asynchronous incoherent Doppler velocity measurement (DWAIDVM) system, and a single baseline angle measurement system. Next, we analyze the physical characteristics of the radar chaff and establish a dynamic model of spherical chaff cloud clusters based on free diffusion. Additionally, we provide the optimal strategy for deploying chaff cloud. Finally, the emergency IC&T application based on the radar chaff cloud relay is simulated, and the results show that for severe interference, taking drones as an example, under a measurement baseline of 100 km, the emergency IC&T solution proposed in this paper can achieve an accuracy range of approximately 100 m, a velocity accuracy of 0.1 m/s, and an angle accuracy of 0.1°. In comparison with existing TT&C system solutions, the proposed system possesses unique and potential advantages that the others do not have. It can serve as an emergency IC&T reference solution in denial environments, offering significant value for both civilian and military applications.

Distributed asynchronous measurement system fusion estimation based on inverse covariance intersection algorithm

For state estimation of multi-source asynchronous measurement systems with measurement missing phenomena, this paper proposes a distributed sequential inverse covariance intersection (DSICI) fusion algorithm based on conditional Kalman filtering method. It is mainly divided into synchronized state space module, local filtering module and fusion estimation module. The missing measurements occurring in the system are modelled and described by a set of random variables obeying a Bernoulli distribution. The synchronized state space module uses a state iteration method to synchronize the asynchronous measurement system at the moment of measurement update and it ensures the integrity of the measurement information. The local filtering module uses a conditional Kalman filtering algorithm for filter estimation. The reliability of the local filtering results is guaranteed because the local estimator designs a method to interact information with the domain sensors. The fusion estimation module designs a DSICI fusion algorithm with higher accuracy and satisfying consistency, which fuses the filtering results provided by each sensor when the relevant information between multiple sensors is unknown. Simulation examples demonstrate the excellent performance of the proposed algorithm, with a 33% improvement in accuracy over existing algorithms and an iteration time of less than 3 ms.

Further Development of Rotating Beamforming Techniques Using Asynchronous Measurements

When rotating noise sources, such as turbomachinery, are investigated using phased microphone array measurements and beamforming, sidelobes appear on the resulting beamforming maps. Sidelobes can be decreased by increasing the number of microphones. However, if the investigated phenomenon is steady, then there is a cost-effective alternative: performing asynchronous measurements using phased arrays having a limited number of microphones. The single beamforming maps can be combined in order to arrive at results that are superior in resolution and sidelobe levels. This technique has been investigated in the literature, but according to the authors’ best knowledge, has not yet been applied to turbomachinery. This article introduces a means for applying the asynchronous measurement technique and the combination methods for rotating noise sources. The combination methods are demonstrated on two rotating point sources (both in simulations and measurements), and then on an axial flow fan test case. In the case of the two rotating point sources, the achievable improvement in resolution, average-, and maximum sidelobe levels are shown as compared to the single results. In the case of the axial flow fan, it is demonstrated that the combination methods provide more reliable noise source locations and reveal further noise sources.

Kalman Filtering with Uncertain and Asynchronous Measurement Epochs

Kalman Filtering with Uncertain and Asynchronous Measurement Epochs

On the low-cost asynchronous one-way range measurement method and the device for micro to nano deep space probes

Recent startups and university space activities extend to cis-lunar and near-Earth interplanetary field. One of the biggest hurdles in those missions is in the orbit determination based on the range measurements, while the radio transmission and reception capability becomes within those small organizations' facilities. Also, about the navigation in cis-lunar space, conventional GNSS (Global Navigation Satellite System) real time positioning is hardly available and some alternative methods have been sought. The most straight forward approach is to be supported by the space agencies' facilities for the range measurement with the transponders onboard the probes. However, it depends on the facilities availability and also on the relatively expensive, old and analogue transponders. This paper presents a new method deriving from the GNSS based devices. It does not require the transponders but inexpensive radio circuits easily built. And both the probes and the ground stations have only to be equipped with the common and simple inexpensive devices. The method enables the small organizations to perform autonomous operation of the probes in a distance beyond the moon's orbit. The paper first presents the latest test data obtained during the development using the Software Defined Radio (SDR) boards.

Improving Pediatric Procedural Skills for EMS Clinicians: A Longitudinal Simulation-Based Curriculum with Novel, Remote, First-Person-View Video-Based Outcome Measurement

Objective Emergency medical services (EMS) clinicians are expected to provide expert care to all patients, but face obstacles in maintaining skillsets required in the care of critically ill or injured children. The objectives of this study were to describe and assess the effectiveness of a pediatric-focused, simulation-based, procedural training program for EMS clinicians, delivered on-site by a pediatric simulation education team. We also describe a novel, remote, asynchronous performance outcome measurement system using first-person-view video review. Methods This was a prospective study of simulation-based training and procedural outcomes. The study population involved EMS clinicians at three fire-based EMS agencies stratified as urban, suburban, and rural sites. The primary outcome was performance of intraosseous catheterization (IO), bag-valve-mask ventilation (BVM), and supraglottic device placement (SGD), measured across three time points. Secondary outcomes were identification of differences across EMS agencies and participant survey responses. Results We obtained video data from 122 clinicians, totaling 561 videos, with survey response rates of 89.0–91.3%. Pre-intervention scores were high: least-square means (95% confident-intervals) 9.5 (8.9, 10.2) for IO; 9.6 (9.3, 9.9) for BVM; and 11.6 (10.9, 12.2) for SGD. There was significant improvement post-intervention: 11.5 (10.7, 12.3) for IO; 11.0 (10.7, 11.4) for BVM; and 13.6 (12.8, 14.4) for SGD. Improvement was maintained at follow-up after a median of 9.5 months: 10.5 (9.8, 11.2) for IO; 10.2 (9.9, 10.6) for BVM; and 12.4 (11.7, 13.1) for SGD. There were no statistical differences between sites. Of survey respondents, half had not cared for a critically ill or injured child in at least a year, the vast majority had not had hands-on pediatric training in over 6 months, and the majority felt that training should occur at least every 6 months. Conclusions Our pediatric-focused, simulation-based procedural training program was associated with improvement and maintenance of high-baseline procedural performance for EMS clinicians over the study period. Findings were consistent across sites. Remote assessment was feasible. Participant surveys emphasized a desire for more pediatric-focused training and highlighted the low frequency of clinical exposure to procedures potentially needed in the care of critically ill or injured pediatric patients.

Analysis for flow termination in the decentralized and centralized pre-congestion notification architecture

This paper discusses decentralized and centralized pre-congestion notification (PCN)-based measured-rate flow termination (FT) in the case of a single bottleneck. The paper finds out that asynchronous measurement periods between ingress–egress aggregates (IEAs) cause overtermination in the decentralized PCN although RFC6661 states that the operation of PCN is not affected if the starting and ending times of the measurement periods for IEAs are different. Also, the paper finds that the asynchronous measurement periods can prevent a FT for one IEA from terminating enough flows in one shot. Furthermore, the paper proves that overtermination occurs in the decentralized PCN due to asynchronous measurement periods regardless of the same or different round trip time (RTT) and synchronous measurement period with different RTTs. In contrast, the centralized PCN can avoid overtermination due to effects of the asynchronous measurement periods and different RTTs.

Research on Asynchronous Information Fusion Technology of the Distributed Active/Passive Imaging Detection System

In the process of target cooperative tracking of the distributed multi-imaging detection system, aiming at the problem of asynchronous measurement information from different detectors, a distributed Asynchronous and Heterogeneous Information Matrix Fusion algorithm based on the Cubature Kalman Filter (CKF-AHIMF) is proposed. According to the Local Detector Driven Communication (LDDC) method and CKF nonlinear mapping, IMF distributed fusion algorithm is generalized into nonlinear, asynchronous, and heterogeneous cases to integrate the information from a multi-imaging detection system and to obtain global high-precision target trajectory. Through the digital simulation, it is verified that the CKF-AHIMF algorithm under the LDDC method proposed in this paper is more effective and has higher tracking accuracy than other distributed fusion algorithms in dealing with the problem of target cooperative tracking under asynchronous information from local imaging detectors, which is also valid to implement in precision detection and guidance system.

State Estimation for High-Speed Train Based on Multirate Asynchronous Sensors Fusion With Missing Measurements

In this paper, a state estimation method is proposed based on the multi-rate asynchronous sensors fusion with missing measurements for high-speed train. Firstly, considering the actual operating environment, a multi-rate asynchronous speed measurement state space model is established. Then, a maximum likelihood evaluation criterion is constructed, and the multiple imputation fusion is proposed for the recovery of intermittent and continuous missing data. Finally, based on the improved adaptive attenuation particle filter-unscented Kalman filter (PF-UKF) and the matrix weighted fusion, the global estimation is fused by linear-weighted summation of the local estimations of train state. The simulation results show that the train state can be accurately fused and estimated by the proposed method while ensuring real-time performance, whether the monitoring data is intermittent missing or continuous missing, and the effectiveness and feasibility of the method can be verified.

Distributed Optimal Voltage Control Considering Latency and Asynchronous Communication for Three Phase Unbalanced Distribution Systems

Integration of distributed energy resources (DERs) helps realize sustainability and reduce carbon footprint, but may cause voltage control issues in the distribution power system. The impact is mainly driven by the intermittency and variability of DERs typically connected at the edge. Traditional centralized optimal voltage control lacks scalability, and local voltage controls are not optimal. Distributed algorithms are scalable, robust to failures, and possibly require less communication resources compared to centralized. This paper presents a new online distributed voltage control algorithm with primal-dual updates and auxiliary variables for three-phase unbalanced distribution systems. The phase-specific active and reactive power of participating voltage control agents is regulated considering the power converter operational limits. The algorithm is validated to regulate voltage for both static and dynamic loading conditions for three-phase unbalanced IEEE 13 and 123 bus systems modeled in the OpenDSS. The robustness of the algorithm is validated for delayed asynchronous communication, modeling errors, and measurement noises. Simulation results and convergence analysis show the superior performance of the proposed algorithm.

A time asynchronous parameters calibration method of high-precision FOG-IMU based on a single-axis continuous rotation scheme

There is a time asynchronous problem with the output signals between each inertial sensor in an actual high-precision fiber optic gyro inertial measurement unit (FOG-IMU), which reduces the velocity update accuracy of the strap-down inertial navigation system in the actual applications. Firstly, the velocity error formulas are derived in the coordinate navigation system considering three time asynchronous errors between the three-axis accelerometers and gyros. Then an error-state Kalman filter is designed with respect to the time asynchronous parameters measurement model in angular dynamic environments. Afterward, a single-axis continuous rotation scheme is developed to calibrate the time asynchronous parameters. In particular, a simple observability analysis model is proposed to verify the rationality of the calibration scheme. Furthermore, the time asynchronous parameters are calculated effectively based on the proposed indirect calibration scheme. Finally, the proposed method is verified effectively through simulations and turntable experiments, which can significantly reduce the measurement errors of high-precision FOG-IMU. As a result, compared with the traditional three-parameter direct calibration method, the eastward and northward velocity errors are reduced by 7.01% and 2.48%, respectively.

Fast Characterization of Phased-Array Elements Using Orthogonal Codes

This article presents a fast-phased array characterization of a 5G millimeter-wave (mmWave) base station (BS). The amplitude, phase, and inter-modulation distortion of multiple antenna elements are characterized simultaneously using an orthogonal code. The proposed orthogonal code suppresses dynamic range and realizes multiple vector measurements with a single capture. The phase drift estimation enables the asynchronous measurement of BS and instruments. The method is demonstrated using 256-element phased-array antennas (PAAs) for 5G mmWave BS.

Breaking the Rate-Loss Bound of Quantum Key Distribution with Asynchronous Two-Photon Interference

Twin-field quantum key distribution can overcome the secret key capacity of repeaterless quantum key distribution via single-photon interference. However, to compensate for the channel fluctuations and lock the laser fluctuations, the techniques of phase tracking and phase locking are indispensable in experiment, which drastically increase experimental complexity and hinder free-space realization. Inspired by the duality in entanglement, we herein present an asynchronous measurement-device-independent quantum key distribution protocol that can surpass the secret key capacity even without phase tracking and phase locking. Leveraging the concept of time multiplexing, asynchronous two-photon Bell-state measurement is realized by postmatching two interference detection events. For a 1 GHz system, the new protocol reaches a transmission distance of 450 km without phase tracking. After further removing phase locking, our protocol is still capable of breaking the capacity at 270 km. Intriguingly, when using the same experimental techniques, our protocol has a higher key rate than the phase-matching-type twin-field protocol. In the presence of imperfect intensity modulation, it also has a significant advantage in terms of the transmission distance over the sending-or-not-sending type twin-field protocol. With high key rates and accessible technology, our work provides a promising candidate for practical scalable quantum communication networks.

State estimation of distribution network based on hybrid measurement combined with multi-source asynchronous data

At present, the redundancy of real-time measurement in distribution network is low and the mixed measurement is incompatible, Hybrid measurement combined with multi-source asynchronous data such as SCADASCADA/ smart distribution transformer information acquisition system (SDTIAS), anew state estimation based on SCADASCADA and SDTIAS is proposed in this paper. Firstly, SDTIAS and SCADA measurements are matched and synchronized; Then, the quadratic multi-source asynchronous measurement model is constructed, the quadratic equality constraint is established, the unified modeling of multi-source asynchronous measurement is realized; Finally, the proposed model and algorithm are simulated and verified in the standard test system, The results show the error seven times lower than traditional methods, and the calculation efficiency (100 Statistics) is increased by 35%, indicating better accuracy and higher efficiency.

Distributed consensus problem with caching on federated learning framework

Federated learning framework facilitates more applications of deep learning algorithms on the existing network architectures, where the model parameters are aggregated in a centralized manner. However, some of federated learning participants are often inaccessible, such as in a power shortage or dormant state. That will force us to explore the possibility that the parameter aggregation is operated in an ad hoc manner, which is based on consensus computing. On the contrary, since caching mechanism is indispensable to any federated learning mobile node, it is necessary to investigate the connection between it and consensus computing. In this article, we first propose a novel federated learning paradigm, which supports an ad hoc operation mode for federated learning participants. Second, a discrete-time dynamic equation and its control law are formulated to satisfy the demands from federated learning framework, with a quantized caching scheme designed to mask the uncertainties from both asynchronous updates and measurement noises. Then, the consensus conditions and the convergence of the consensus protocol are deduced analytically, and a quantized caching strategy to optimize the convergence speed is provided. Our major contribution is to give the basic theories of distributed consensus problem for federated learning framework, and the theoretical results are validated by numerical simulations.

Proposal of Virtual Transformer-based Back-to-Back Asynchronous Loss Measurement using a Single Set of Measurement Instruments for One Inverter and Experimental Verification

Proposal of Virtual Transformer-based Back-to-Back Asynchronous Loss Measurement using a Single Set of Measurement Instruments for One Inverter and Experimental Verification

Distribution State Estimation using Multiple Stages considering Asynchronous Measurement Data by Dependable Parallel Multi-population Global-best Brain Storm Optimization with Differential Evolution Strategies

Distribution State Estimation using Multiple Stages considering Asynchronous Measurement Data by Dependable Parallel Multi-population Global-best Brain Storm Optimization with Differential Evolution Strategies