Measurement Update Rate Research Articles

Fiber-optic spectrum monitoring of wavelength-division-multiplexed telecommunication signals with MHz update rates.

We propose a novel (to our knowledge) and simple real-time optical monitoring (RTOM) system for dynamic spectral analysis of telecommunication signals, involving electro-optic (EO) temporal sampling followed by dispersion-induced frequency-to-time mapping and high-speed photodetection. This system enables tracking of the presence and relative intensity of multiple wavelength-division-multiplexed (WDM) data streams that span over a broad frequency band with high resolution, accuracy, and fast measurement update rates. We derive the design conditions and trade-offs of the proposed scheme and report proof-of-concept experiments and a numerical result that demonstrate successful spectral monitoring of dense-WDM signals with different modulation formats and bit rates, over the full C-band, with the needed resolution to discern channels separated by a few tens of GHz, and with an unprecedented fast measurement update rate in the MHz range.

UWB-Based Indoor Positioning System With Infinite Scalability

The ultra-wide band radio technology (UWB) is currently considered the de-facto standard for implementing precise indoor positioning systems. Several positioning algorithms are currently being investigated for finding the best implementation in terms of scalability, refresh rate, and energy requirements. Among all the proposed approaches, the Downlink Time Difference of Arrival (DTDoA) is currently considered one of the most promising techniques capable of tracking any number of assets without decreasing the measurement update rate. This paper proposes a model for the DTDoA and validates the algorithms on UWB data, using a motion capture system as ground truth. Results highlight the validity of the previously proposed model, showing that the proposed UWB indoor positioning system achieves a maximum 30 cm uncertainty with only a simple wireless synchronisation, avoiding wired procedure that limits the usability of the infrastructure.

Silent speech command word recognition using stepped frequency continuous wave radar

Recovering speech in the absence of the acoustic speech signal itself, i.e., silent speech, holds great potential for restoring or enhancing oral communication in those who lost it. Radar is a relatively unexplored silent speech sensing modality, even though it has the advantage of being fully non-invasive. We therefore built a custom stepped frequency continuous wave radar hardware to measure the changes in the transmission spectra during speech between three antennas, located on both cheeks and the chin with a measurement update rate of 100 Hz. We then recorded a command word corpus of 40 phonetically balanced, two-syllable German words and the German digits zero to nine for two individual speakers and evaluated both the speaker-dependent multi-session and inter-session recognition accuracies on this 50-word corpus using a bidirectional long-short term memory network. We obtained recognition accuracies of 99.17% and 88.87% for the speaker-dependent multi-session and inter-session accuracy, respectively. These results show that the transmission spectra are very well suited to discriminate individual words from one another, even across different sessions, which is one of the key challenges for fully non-invasive silent speech interfaces.

Decentralized robust state estimation for hybrid AC/DC distribution systems with smart meters

Hybrid AC/DC distribution systems are becoming a popular means to accommodate the increasing penetration of distributed energy resources and flexible loads. This paper proposes a decentralized robust state estimation (DRSE) method for hybrid AC/DC distribution systems using multiple sources of data. In the proposed decentralized implementation framework, a unified robust linear state estimation model is derived for each AC and DC regions, where the regions are connected via AC/DC converters and only limited information exchange is needed. In this context, estimation accuracy may be suffering due to linearization. To enhance the estimation accuracy, a deep neural network (DNN) based on the smart meter data is used to extract hidden system statistical information and allow deriving nodal power injections that keep up with the real-time measurement update rate. This provides the way of integrating smart meter data, SCADA measurements and zero injections together for state estimation. Simulations on two hybrid AC/DC distribution systems show that the proposed DRSE has only slight accuracy loss by the linearization formulation but offers robustness of suppressing bad data automatically, as well as benefits of improving computational efficiency.

A passive wireless triboelectric sensor via a surface acoustic wave resonator (SAWR)

With the development of the Internet of Things (IoT), the requirement of wireless sensing operations is becoming increasingly desirable. Most of the current active wireless sensors require external power suppliers and complex active circuits, which limits their applications. A passive wireless sensor is a desired alternative. Hence, a passive wireless triboelectric sensor (PWTES) without active electronic components, a battery, or an energy harvester is proposed to meet the further demand for wireless monitoring. The key component of the PWTES is a surface acoustic wave resonator (SAWR). The sensing signal generated by the triboelectric nanogenerator (TENG) is applied to modulate the SAWR's response signal via a tuning network. A designed reader interrogates the SAWR and receives its response via the radiofrequency link, then demodulation is performed on the SAWR's response to obtain the sensing signal. Employing the designed PWTES, a wireless pressure sensor without a battery and an energy harvester is successfully demonstrated. The PWTES exhibited the wireless transmission of a sensing signal over a distance of 2 m, a sensitivity of 23.75 kHz/V within the TENG's voltage range of 0–5 V, and a measurement update rate of 12 kHz. The PWTES makes full use of the advantages of the TENG in sensing, and the properties of the SAWR in wireless communication, holding great potential for the miniaturization, integration, and continuous monitoring of wireless sensors in the era of the IoT.

Performance Analysis of Oscillator-Based Read-Out Circuit for LVDT

The performance of an oscillator-based read-out circuit for the linear variable differential transformer used as a displacement sensor is studied and various aspects of improving it are presented in this paper. The proposed read-out electronics treats the sensor’s secondary inductance as an unknown reactance, thereby incorporating an active oscillator circuit as a resonator to derive the position information. This method avoids the excitation of the primary coil using low-distortion sine-wave oscillators and the associated phase compensation circuitry as used in traditional signal conditioning circuits. The tradeoffs involved in choosing the frequency counter master clock frequency, the measurement update rate, and the achievable resolution are presented. Various factors that contribute to the nonlinearity have been studied from the standpoint of direct difference versus ratiometric formulas for deriving position information. It is shown that for the oscillator-based read-out procedure, resolutions in the range of 8–16 bits with update rates per channel ranging from 10 Hz to 7.86 kHz, and depending on the procedure used, a worst case full-scale nonlinearity error of ±0.14% are feasible.

Cooperative vehicle positioning with multi-sensor data fusion and vehicular communications

Vehicular positioning with multi-sensor fusion has achieved promising results in recent years. Having potential benefit from the emerging vehicular communications based on IEEE 802.11p dedicated short-range communication (DSRC), cooperative positioning opens new opportunities to support several vehicular applications. In addition, radar based active safety functions and GPS are being integrated into modern vehicles. With the availability of information from multiple sources, exchange of sensor information and multi-sensor fusion can be applied to obtain the precise positioning of vehicle without substantial additional cost. However, the main challenge in data fusion is the inherent data association problem due to dissimilar measurement update rate of DSRC and automotive radar. To overcome these challenges, this paper proposes a robust positioning approach considering track-to-track matching and fusion of position information obtained from multiple on-board sources such as GPS receiver, Vehicle-to-vehicle communication and automotive radar. Realistic 3D road traffic and wave propagation model is developed using a ray-tracing tool and the effectiveness of the proposed concept was evaluated. The system concept is validated by conducting extensive simulation considering realistic car following model. Results show that the proposed cooperative positioning method exhibits significant improvement in terms of positioning accuracy.

Reader Architectures for Wireless Surface Acoustic Wave Sensors.

Wireless surface acoustic wave (SAW) sensors have some unique features that make them promising for industrial metrology. Their decisive advantage lies in their purely passive operation and the wireless readout capability allowing the installation also at particularly inaccessible locations. Furthermore, they are small, low-cost and rugged components on highly stable substrate materials and thus particularly suited for harsh environments. Nevertheless, a sensor itself does not carry out any measurement but always requires a suitable excitation and interrogation circuit: a reader. A variety of different architectures have been presented and investigated up to now. This review paper gives a comprehensive survey of the present state of reader architectures such as time domain sampling (TDS), frequency domain sampling (FDS) and hybrid concepts for both SAW resonators and reflective SAW delay line sensors. Furthermore, critical performance parameters such as measurement accuracy, dynamic range, update rate, and hardware costs of the state of the art in science and industry are presented, compared and discussed.

Resonance-Enhanced Coupling for Range Extension of Electromagnetic Tracking Systems

This paper investigates the use of resonance-enhanced coupling to increase the received signal level in a six-degree-of-freedom electromagnetic tracking system. Resonant coupling is found to increase the efficiency of the transmitter and increase the gain of the sensing coil, resulting in improved range. However, the measurement update rate is reduced due to the settling time of the transmitter circuit and the limited bandwidth of the sensing circuit. A resistive tuning approach is proposed to balance the tradeoff between a decreased measurement bandwidth and an improved signal level.

On the use of decision feedback equalization for continuous active sonar

Continuous Active SONAR (CAS) systems allow duty cycles up to 100% and so lower target association errors are possible as compared to Pulse Active Sonar (PAS). Large time-bandwidth product Linear Frequency Modulated (LFM) signals are the de facto standard for this type of SONAR systems, yet, these signals suffer from low processing gains when the ocean exhibits low-spatio temporal coherence. In this work, we depart from the typical sub-band matched filter processing and propose to adopt signal processing techniques used in underwater acoustic communications. In particular, we analyze Binary Phase Shift Keying (BPSK) signals via an adaptive Decision-Feedback Equaliser (DFE). The DFE is able to adapt to environmental changes based on the known transmitted bits. The operational bandwidth is 1500–4000 Hz and the BPSK signals are transmitted in two non-overlapping bands to avoid transmit interference during reception. The performance of the proposed system is demonstrated based on field data recorded during a sea experiment off the Coast of La Spezia in October 2017. The key result here is that the Doppler measurement update rate of the echoes is as fast as the bit rate of the transmitted BPSK signal.Continuous Active SONAR (CAS) systems allow duty cycles up to 100% and so lower target association errors are possible as compared to Pulse Active Sonar (PAS). Large time-bandwidth product Linear Frequency Modulated (LFM) signals are the de facto standard for this type of SONAR systems, yet, these signals suffer from low processing gains when the ocean exhibits low-spatio temporal coherence. In this work, we depart from the typical sub-band matched filter processing and propose to adopt signal processing techniques used in underwater acoustic communications. In particular, we analyze Binary Phase Shift Keying (BPSK) signals via an adaptive Decision-Feedback Equaliser (DFE). The DFE is able to adapt to environmental changes based on the known transmitted bits. The operational bandwidth is 1500–4000 Hz and the BPSK signals are transmitted in two non-overlapping bands to avoid transmit interference during reception. The performance of the proposed system is demonstrated based on field data recorded during a ...

High-Speed Resonant Surface Acoustic Wave Instrumentation Based on Instantaneous Frequency Measurement

Surface acoustic wave (SAW) resonators are used for a broad range of wireless sensing applications, some of them having high demands on the resolution as well as the measurement update rate. This paper presents a new interrogation method for precise and fast frequency determination of passive SAW resonators based on instantaneous frequency measurement by a low-cost six-port interferometer. Using a delay line, the frequency measurement is reduced to a phase measurement that can be instantaneously evaluated by the six-port network. No complex signal processing is necessary providing high update rates and low hardware costs. An in-depth analysis of the system concept and its building blocks is presented, and the advantages as well as the limitations are discussed and compared with the current state of the art. Finally, a demonstrator in the 2.4-GHz frequency band shows the feasibility and the precision of the concept with measurement times of only a few microseconds.

Optical Beacon Sensor for Small Unmanned Aerial System State Estimation

A new optical sensor system is presented that measures a reference vector direction relative to the body frame of a small unmanned aircraft system (sUAS) at medium ranges in daylight conditions with high precision and without drift using a low‐power, nonlaser, eye‐safe optical beacon. The beacon operates as a monochromatic, time‐modulated optical source, and the airborne sensor uses both optical band‐pass filtering and frequency domain signal processing to separate the beacon signal from reflected and scattered sunlight incident on the sensor's aperture, thus providing increased sensitivity. Characterization of the prototype sensor shows that the reference‐vector direction angles can be measured with an accuracy of better than 0.5% of the field of view, resulting in 0.1° accuracy over a 30 degree range, at a measurement update rate of 200 Hz. This result is based on an operating range of 134 m using a 1 W beacon with a 9° beamwidth. The prototype system was integrated into and tested on a small UAS. Flight test results are presented comparing the prototype sensor system's output to an estimate of the reference‐vector direction produced by fusing inertial measurement and GPS information, thus demonstrating how this sensor system offers a method of validating sUAS attitude estimation systems. The sensor system may also be used to augment sUAS attitude estimation systems, or for other purposes such as in a precision sUAS landing system or for state estimation in GPS‐denied environments.

Tracking With a High-Resolution 2D Spectral Estimation Based Automotive Radar

This paper concerns the tracking of automotive radar targets by a radar using a high-resolution 2D spectral estimator in order to detect the radar targets. We show how to implement the tracking, discuss the measurement variances, and show how we can exploit the high resolution in order to make a better tracking filter. Existing automotive radar systems are affected by a limited field of view, poor angular accuracy, or low measurement update rate. By using a combination of a waveform solving, the target ambiguity problem within a short measurement time and a conformal array design, we eliminate these problems and by the use of the 2D APES estimator, we achieve a high angular resolution, which is used in order to improve the tracking. The simulation results show that we are able to track a laterally moving vehicle very accurately and that the new improved tracking filter achieves more robust and accurate tracking along with a short initialization time. These attributes can be very important for safety critical applications.

Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation.

In this study, simulation tests for gravity gradient referenced navigation (GGRN) are conducted to verify the effects of various factors such as database (DB) and sensor errors, flight altitude, DB resolution, initial errors, and measurement update rates on the navigation performance. Based on the simulation results, requirements for GGRN are established for position determination with certain target accuracies. It is found that DB and sensor errors and flight altitude have strong effects on the navigation performance. In particular, a DB and sensor with accuracies of 0.1 E and 0.01 E, respectively, are required to determine the position more accurately than or at a level similar to the navigation performance of terrain referenced navigation (TRN). In most cases, the horizontal position error of GGRN is less than 100 m. However, the navigation performance of GGRN is similar to or worse than that of a pure inertial navigation system when the DB and sensor errors are 3 E or 5 E each and the flight altitude is 3000 m. Considering that the accuracy of currently available gradiometers is about 3 E or 5 E, GGRN does not show much advantage over TRN at present. However, GGRN is expected to exhibit much better performance in the near future when accurate DBs and gravity gradiometer are available.

Analytic Optimization of Implemented Discrete Time for Kalman Filter during Stationary North-Finding

According to the mechanization of the Kalman filter, the processing load of implementing a Kalman filter can be different under various system propagation rates and measurement update rates. With the definitions of uniform and complete observability, uniform and complete controllability, an analytic method of evaluating the effects of various system propagation rates and measurement update rates on the azimuth error during stationary north-finding was proposed. Variance calculations and experimental tests were presented to demonstrate the applicability of the proposed analytic method and let analysts maintain good physical insight into the estimation behavior of the final azimuth error. In conclusion, the proposed analytic method will help analysts optimize system propagation rate and measurement update rate to make the computational load fall within the available processing capacity.

Characterization of a Flexible UWB Sensor for Indoor Localization

This paper presents research to develop an ultrawideband ranging sensor for personnel indoor localization based on the measurement of the pulse round-trip time. An approach combining flexibility, a high measurement update rate, and asynchronous operation with digital processing capability has been employed in the design of the sensor. The principle of operation, the architecture of the realized sensor, and the experimental setup are described. Finally, the results of a ranging calibration and validation test are presented and discussed. In the validation procedure, a root-mean-square error of 29 cm and a maximum absolute error of 81 cm with an operational range of approximately 10 m were observed.

Remote vibration measurement: A wireless passive surface acoustic wave resonator fast probing strategy

Surface acoustic wave (SAW) resonators can advantageously operate as passive sensors which can be interrogated through a wireless link. Amongst the practical applications of such devices, structural health monitoring through stress measurement and more generally vibration characteristics of mechanical structures benefit from the ability to bury such sensors within the considered structure (wireless and battery-less). However, measurement bandwidth becomes a significant challenge when measuring wideband vibration characteristics of mechanical structures. A fast SAW resonator measurement scheme is demonstrated here. The measurement bandwidth is limited by the physical settling time of the resonator (Q/π periods), requiring only two probe pulses through a monostatic RADAR-like electronic setup to identify the sensor resonance frequency and hence stress on a resonator acting as a strain gauge. A measurement update rate of 4800 Hz using a high quality factor SAW resonator operating in the 434 MHz Industrial, Scientific and Medical band is experimentally demonstrated.

Input-state model matching and ripple-free response for dual-rate systems

In this paper, we address the model matching problem for dual-rate systems where the controller output is generated at a faster rate than the measurement update rate. The model matching problem that has been studied in the literature requires the input–output properties of the closed-loop multirate system to match those of a desired single-rate linear time-invariant (LTI) system. In this paper, we consider the model matching problem from the input-state viewpoint: given a desired LTI system, find conditions and provide a controller design procedure to achieve matching between the closed-loop system and the desired system state variables at the measurement update rate. We provide a solution to this problem using a particular time-varying controller structure. In addition, we give conditions to avoid ripples in the steady-state output of the continuous-time plant; in particular, we show that some constraints on the input matrix of the desired system have to be posed. Numerical examples are given to illustrate the proposed method.

Complex-field measurement of ultrafast dynamic optical waveforms based on real-time spectral interferometry

Several methods are now available for single-shot measurement of the complex field (amplitude and phase profiles) of optical waveforms with resolutions down to the sub-picosecond range. As a main critical limitation, all these techniques exhibit measurement update rates typically slower than a few Hz. It would be very challenging to directly upgrade the update rate of any of these available methods beyond a few kHz. By combining spectral interferometry with dispersion-induced real-time optical Fourier transformation, here we demonstrate single-shot complex-field measurements of optical waveforms with a resolution of approximately 400 fs over a record length as long as approximately 350 ps, corresponding to a large record-length-to-resolution ratio of approximately 900. This performance is achieved at a measurement update rate of approximately 17 MHz, i.e. at least one thousand times faster than with any previous single-shot complex-field THz-bandwidth optical signal characterization method.

A wideband sampling voltmeter

A high-accuracy sampling voltmeter, designed to span the frequency range of 10 Hz-200 MHz, is described. The instrument operates autonomously, at a measurement update rate of at least one per second. A novel quasiequivalent time sampling process is used, with a custom strobed comparator as the sampling device and decision element. The architecture and control are presented, along with the time-base design principles. Major error sources associated with the time-base are also discussed.