Measured Noise Power Research Articles

Dynamic Range Improvements for Beacon Receivers Using Noise Power Measurements

Dynamic Range Improvements for Beacon Receivers Using Noise Power Measurements

Application of empirical mode decomposition for denoising and ground clutter removal on weather radar signals

Proper detection and estimation of signal and noise power measurements are important to generate the best quality of meteorological data products such as Reflectivity, Velocity and Spectrum width. In order to obtain the best quality radar products, it is desirable to compute meteorological parameters by estimating noise power and removal of ground clutter. This paper attempts to study the Empirical Mode Decomposition (EMD) denoising techniques on weather radar signals in the presence of noise and ground clutter. Different methods of EMD based denoising techniques have been considered and applied to the weather signals to check the best performance of the denoising and clutter removal technique. The limitations of these methods are brought out through simulation analysis. To overcome these limitations, this paper proposes a new method for denoising and clutter removal in weather signals. This method is a modified version of the correlation-based EMD Interval Threshold (IT) measurements. Moments have been estimated from these techniques and compared with conventional methods like Pulse pair techniques.

Quasi-planar InGaAsSb p-B-n photodiodes for spectroscopic sensing.

An InGaAsSb p-B-n structure has been designed and characterized for zero bias low power detection applications. Devices were grown by molecular beam epitaxy and fabricated into quasi-planar photodiodes with a 2.25 µm cut-off wavelength. Maximum responsivity was measured to be 1.05 A/W at 2.0 µm, achieved at zero bias. D* of 9.4 × 1010 Jones was determined from room temperature spectra of noise power measurements with calculated D* remaining >1 × 1010 Jones up to 380 K. With a view to simple miniaturized detection and measurement of low concentration biomarkers, optical powers down to 40 pW were detected, without temperature stabilization or phase-sensitive detection, indicating the photodiode's potential.

Careful least squares active noise control with no prior secondary path model

SummaryIn feedforward active noise and vibration control (ANVC) or active noise control (ANC), with online secondary path modeling, fast converging overall modeling algorithms may give high modeling errors. These errors are due to the highly correlated inputs, namely the reference and antinoise signals. These high modeling errors can result in poor performance if ignored. However, it is possible to consider these modeling errors in the control filter design, resulting in a careful controller and good performance, as proposed in this work. Careful control is a dual controller feature, which is the solution to the optimal control problem, but this has not been proposed before in the context of ANC. The modeling error covariance matrix (Sigma(n)) is available in the Kalman filter. However, this requires the knowledge of the time‐varying measurement noise power q(n) and state noise. Instead, this work uses a different approach in which the corresponding linear system is solved in a non‐recursive manner. The resulting maximum error is used for a worst‐case estimate of q(n), and, as it turns out, this can be used to get a worst‐case estimate of Sigma(n). A lower control filter update frequency and other optimizations keep computational complexity similar to other approaches. The resulting algorithm has very few easily selected parameters, good performance, does not require any prior secondary path estimate, and adapts to slow and sudden changes in the physical paths without loss of performance or noise overshoots. However, performance can be impaired by large background noise levels.

Temperature-Dependent Threshold Voltage Extraction of FinFETs Using Noise Measurements

In this article, a temperature-dependent threshold voltage extraction method based on noise measurement is proposed. This method induces a mathematical solution for acquiring channel temperatures ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> ) of transistors in the saturation region to extract threshold voltages. In order to gain accurate channel temperature, a small-signal equivalent circuit model was established to determine transconductance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula> ). Then, the extracted transconductance and measured noise power spectral density (NPSD) were used to obtain channel temperatures. On this basis, the temperature-dependent threshold voltage ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {th}}$ </tex-math></inline-formula> ) was derived. To validate the reliability of this method, a four-Fin six-finger N-FinFET and a four-Fin eight-finger N-FinFET were fabricated using the 14-nm bulk FinFET technology. In this study, the scattering parameters were obtained from 0.2 to 40.2 GHz. Also, the NPSDs were measured from 1 to 500 Hz, while gate voltage and drain voltage were set as 0.3, 0.49, and 0.75 V. Besides, the transistor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I_{\mathrm {ds}}$ </tex-math></inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {ds}}$ </tex-math></inline-formula> characteristics was also investigated when drain–source bias voltage changed from 0.05 to 0.9 V. Compared with the measurement results, the calculation results of drain–source current model using temperature-dependent threshold voltage achieved higher accuracy. Also, the root mean square errors (RMSEs) were less than 0.60% for four-Fin six-finger N-FinFET and less than 0.51% for four-Fin eight-finger N-FinFET. Therefore, the proposed extraction method can be applied to accurately predict transistor temperature-dependent threshold voltage.

On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

Most mobile phones today have capacitive micro-electro-mechanical systems (MEMSs) microphones that use either single or dual diaphragms. Methods to detect failures easily and non-invasively have become of critical importance for microphones mobile phone manufacturers as a basis for built-in self-test (BIST) and self-repair (BISR) strategies. In that regard, a four-layer framework is presented that includes lumped element modeling (LEM), failure mode simulation, failure mode discrimination, and recovery. The frequency response of the microphone is taken as the main output to analyze. To experimentally validate this framework, this article provides a failure mode induction method based on bias voltage sweeping and four new techniques, based solely on acoustic measurements to discriminate the states of electrostatic capture for single diaphragm capacitive MEMS microphones. These include 1) analysis of an acoustic signature that is unique to electrostatic capture based on cosine similarity analysis; 2) −3 dB point measurement; 3) +3 dB point measurement; and 4) cluster analysis. Measurement of pull-in voltage and snapback voltage ranges is further demonstrated based on sensitivity measurements in laboratory conditions and response magnitude and noise power measurements in non-laboratory conditions. Up to 100% success rate in detecting electrostatic capture of diaphragm is reported for this type of device.

An Optimized Zero-Attracting LMS Algorithm for the Identification of Sparse System

This paper introduces an optimized zero-attractor to improve the performance of least mean square (LMS)-based algorithms for the identification of sparse system. Compared with previous LMS-based algorithms for sparse system identification, the performance of the proposed optimized zero-attracting LMS (OZ-LMS) is much less sensitive to the tuning parameters and measurement noise power, and performs much better for sparse system. Comprehensive performance analysis of the mean-square deviation (MSD) of OZ-LMS is derived in detail. Moreover, the parameter selection rules for optimal steady-state MSD are discussed. Simulation results, using white Gaussian noise and speech input signals, show improved performance over existing methods. Furthermore, we show that the numerical results of OZ-LMS agree with the theoretical predictions.

Conditional Covariances for the Signal Lag Measurements in Fluoroscopic Imaging.

In fluoroscopic imaging, we can acquire X-ray image sequences using a flat-panel dynamic detector. However, lag signals from previous frames are added to the subsequently acquired images and produce lag artifacts. The lag signals also inflate the measured noise power spectrum (NPS) of a detector. In order to correct the measured NPS, the lag correction factor (LCF) is generally used. However, the nonuniform temporal gain (NTG), which is from inconsistent X-ray sources and readout circuits, can significantly distort the LCF measurements. In this paper, we propose a simple scheme to alleviate the NTG problem in order to accurately and efficiently measure the detector LCF. We first theoretically analyze the effects of NTG, especially on the correlation-based LCF measurement methods, where calculating the correlation coefficients are required. In order to remove the biases due to NTG, a notion of conditional covariance is considered for unbiased estimates of the correlation coefficients. Experiments using practical X-ray images acquired from a dynamic detector were conducted. The proposed approach could yield accurate LCF values similarly to the current approaches of the direct and U-L corrections with a low computational complexity. By calculating the correlation coefficients based on conditional covariance, we could obtain accurate LCF values even under the NTG environment. This approach does not require any preprocessing scheme of the direct or U-L correction and can provide further accurate LCF values than the method of IEC62220-1-3 does.

Biases and Uncertainties of RF Noise Power Measurements

In this paper, we explore various methods of measuring noise power in RF systems. We discuss some of the systems commonly used to make such measurements, then analyze each system's architecture to obtain the measurement bias and uncertainty for six different combinations of noise models (real and complex noise) and methods of averaging (linear power, magnitude, and logarithmic). Equipped with this knowledge, users can correct for post-measurement biases and determine the number of averages required to yield a desired uncertainty level.

Source/Load-Pull Noise Measurements at Ka Band

This paper is focused on the extraction of the noise parameters of a linear active device by exploiting both forward and reverse noise power measurements associated with different terminations. In order for load-pull measurements to yield a significant marginal improvement (as compared to forward measurements only) it is expected that the device under test should appreciably deviate from unidirectionality. For this reason, the source/load-pull technique is applied to frequencies at which the considered devices are still usable but their reverse noise factor exhibits a measurable dependence on the output terminations. Details on the test bench set up to the purpose, covering the 20–40 GHz frequency range, are provided. A characterization campaign on a 60 nm gate length, 4×35 µm GaN-on-Si HEMT fabricated by OMMIC is illustrated.

Bench-Top Cooling of a Microwave Mode Using an Optically Pumped Spin Refrigerator.

We experimentally demonstrate the temporary removal of thermal photons from a microwave mode at 1.45GHz through its interaction with the spin-polarized triplet states of photo-excited pentacene molecules doped within a p-terphenyl crystal at room temperature. The crystal functions electromagnetically as a narrowband cryogenic load, removing photons from the otherwise room-temperature mode via stimulated absorption. The noise temperature of the microwave mode dropped to 50_{-32}^{+18} K (as directly inferred by noise-power measurements), while the metal walls of the cavity enclosing the mode remained at room temperature. Simulations based on the same system's behavior as a maser (which could be characterized more accurately) indicate the possibility of the mode's temperature sinking to ∼10 K (corresponding to ∼140 microwave photons). These observations, when combined with engineering improvements to deepen the cooling, identify the system as a narrowband yet extremely convenient platform-free of cryogenics, vacuum chambers, and strong magnets-for realizing low-noise detectors, quantum memory, and quantum-enhanced machines (such as heat engines) based on strong spin-photon coupling and entanglement at microwave frequencies.

Target Localization in Multistatic Systems Without the Bistatic Range Measurement Noise Power

This letter investigates the problem of determining the static target in multistatic systems using bistatic range (BR) measurements, which can be obtained by some local sensor signal processing methods. The localization problem is first formulated as a semidefinite programming problem by using the semidefinite relaxation technique. Then, an initial position estimate is given by augmenting the unknown parameter space, which is required for solving the SDP problem. Specifically, this initialization is also a closed-form solution. Compared with existing algorithms, the proposed estimator has the advantage of not relying on the prior knowledge of BR measurement noise power. Simulation results validate the performance of the proposed estimator.

Measurement of the Lag Correction Factor in Low-Dose Fluoroscopic Imaging.

Lag signals occur at images sequentially acquired from a flat-panel (FP) dynamic detector in fluoroscopic imaging due to charge trapping in photodiodes and incomplete readouts. This lag signal produces various lag artifacts and prevents analyzing detector performances because the measured noise power spectrum (NPS) values are reduced. In order to design dynamic detectors, which produce low lag artifacts, accurately evaluating the detector lag through its quantitative measurement is required. A lag correction factor can be used to both examine the detector lag and correct measured NPS. To measure the lag correction factor, the standard of IEC62220-1-3 suggests a temporal power spectral density under a constant potential generator for the x-rays. However, this approach is sensitive to disturbing noise and thus becomes a problem in obtaining accurate estimates especially at low doses. The Granfors-Aufrichtig (GA) method is appropriate for noisy environments with a synchronized pulse x-ray source. However, for the x-ray source of a constant potential generator, gate-line scanning to read out charges produces a nonuniform lag signal within each image frame and thus the conventional GA method yields wrong estimates. In this paper, we first analyze the GA method and show that the method is an asymptotically unbiased estimate. Based on the GA method, we then propose three algorithms considering the scanning process and exposure leak, in which line estimates along the gate line are exploited. We extensively conducted experiments for FP dynamic detectors and compared the results with conventional algorithms.

The Impact of Ambient Sensing on the Recognition of Electrical Appliances

Smart spaces are characterized by their ability to capture a holistic picture of their contextual situation. This often includes the detection of the operative states of electrical appliances, which in turn allows for the recognition of user activities and intentions. For electrical appliances with largely different power consumption characteristics, their types and operational times can be easily inferred from data collected at a single metering point (typically, a smart meter). However, a disambiguation between consumers of the same type and model, yet located in different areas of a smart building, is not possible this way. Likewise, small consumers (e.g., wall chargers) are often indiscernible from measurement noise and spurious power consumption events of other appliances. As a consequence thereof, we investigate how additional sensing modalities, i.e., data beyond electrical signals, can be leveraged to improve the appliance detection accuracy. Through a set of practical experiments, recording ambient influences in eight dimensions and testing their effects on 21 appliance types, we evaluate the importance of such added features in the context of appliance recognition. Our results show that electrical power measurements already yield a high appliance recognition accuracy, yet further accuracy improvements are possible when considering ambient parameters as well.

Source localisation using TDOA and FDOA measurements under unknown noise power knowledge

In this study, the authors develop a new algorithm for passive source localisation using time-difference-of-arrival (TDOA) and frequency-difference-of-arrival (FDOA) measurements. In this algorithm, the position and velocity of the target source are successively estimated by formulating two alone semidefinite programming problems, where the variances of the TDOA and FDOA measurement noises can be separated and neglected. Unlike the traditional methods, the authors’ approach does not require the prior knowledge of the TDOA/FDOA measurement noise power. Simulation results indicate that the proposed algorithm outperforms the existing methods under unknown noise power knowledge.

Adaptive model predictive control design for the speed and temperature control of a V94.2 gas turbine unit in a combined cycle power plant

Abstract This paper proposes an adaptive model predictive control (AMPC) approach with online parameter estimation for a V94.2 gas turbine mounted in the Damavand combined cycle power plant (CCPP). The AMPC is designed to simultaneously maintain the speed and temperature responses of the gas turbine within their desired levels in the presence of frequency drop or change in load demand. It implements an online parameter estimation and adaptive mechanism to enable the model parameters to follow any change in the V94.2 gas turbine power plant (GTPP) model and provide the best control performance possible. The effectiveness of the AMPC approach is assessed using an estimated model of a V94.2 gas turbine mounted in the Damavand CCPP. Additional analysis is also performed via a comparison study encompassing a classical MPC, H ∞ , and μ − s y n t h e s i s robust control strategies and considering reference tracking performance, transient and steady-state responses, disturbance rejection capabilities, and robustness to parameter variations. The obtained results confirmed the effectiveness of the proposed approach in improving the robust stability and dynamics of the V94.2 GTPP in the presence of measurement noise, frequency disturbance, and unmodeled power plant dynamics along with its superior performance in terms of tracking capability and disturbance rejection properties.

Steady-state mean-square deviation analysis of improved ℓ0-norm-constraint LMS algorithm for sparse system identification

The ℓ0-norm-constraint LMS (ℓ0-LMS) algorithm is one of the widely used sparse LMS algorithms for the identification of sparse system, and its performance is quite attractive compared to other precursors. However, ℓ0-LMS is still confronted with some limitations on the optimal parameter selection and the estimated coefficient accuracy of sparse system identification. In this paper, we proposed an improved ℓ0-LMS (ℓ0-ILMS) algorithm to address these limitations. The convergence condition and the parameter selection rules for optimal steady-state mean-square deviation (MSD) of ℓ0-ILMS are discussed. Compared with ℓ0-LMS, the steady-state MSD of ℓ0-ILMS is lower and less sensitive to the tuning parameters and measurement noise power. Numerical simulations comparing the performance of standard LMS, ℓ0-LMS and ℓ0-ILMS demonstrate the effectiveness of ℓ0-ILMS.

Compact Simulation of Chip-to-Chip Active Noise Coupling on a System PCB Board

A chip-to-chip active noise coupling demonstrator integrates two identical complementary metal oxide silicon (CMOS) chips on a printed circuit board (PCB), where each chip has the capability of power noise generation by CMOS shift resister array circuits (noise source; NS) and also power noise measurements by on-chip voltage monitoring circuits (OCM). For establishing the noise aware design strategy and methodology, a full-system level noise coupling simulation technique is evaluated on the demonstrator representing a multi-chip mixed-signal PCB. In an experimental scenario, an IC chip (Aggressor IC) operates the NS to generate power noise and the OCM measures the voltage fluctuation of the power delivery network (PDN) within the chip. On the other hand, another IC (Victim IC) holds the NS in no operation while uses the OCM to monitor its PDN voltage fluctuation caused by the conducted noise from the aggressor IC. For the verification of simulation accuracy, two chip power models (CPM), package wire models, discrete de-cap models and a single PCB model are combined into a chip-package-system (CPS) integrated model. The simulation was performed in about 2 hours for CPS integrated noise simulation including S-parameter extraction of the PCB. It is demonstrated that the full-system model with the two CPMs successfully simulates chip-to-chip active noise coupling, namely noise propagation from internal circuits of an aggressor chip to those on a victim chip. The chip-to-chip noise coupling simulation exhibited good agreements with measurements in case studies. The simulation methodology enables conductive noise aware design for multi-chip mixed-signal PCB in its design stage.

A Measurement of Noise Wave Correlation Matrix Using Noise Power Ratios

In this paper, we propose a novel technique for the measurement of noise wave correlation matrix (NWCM) of a two-port network using measured noise power ratios. The ratio of two measured noise powers is observed to show significantly reduced fluctuations compared with absolutely measured noise powers. Based on this observation, the equations to compute the NWCM are formulated using the noise power ratios. Since the NWCM has four unknowns, five absolute output noise powers of a device under test (DUT) are measured to obtain four noise power ratios. The conventional noise parameters can then be obtained by converting the NWCM. In order to demonstrate this technique, we measured the NWCM of an active DUT with a noise figure of less than 1 dB. The noise parameters resulting from the measured NWCM show minimal fluctuations as expected.

Reactivity and Delayed Neutron Precursors’ Concentration Estimation Based on Recursive Nonlinear Dynamic Data Reconciliation Technique

Reactivity is widely used as the paramount means for defining nuclear reactor status, but there is no physical sensor available to measure this parameter directly. Similarly delayed neutron precursors’ concentrations, the source of the delayed neutrons which play important role in reactor control cannot be measured directly. Hence, these quantities must be calculated or estimated from observed neutron flux transients. Recently, Kalman filter (KF) and its variants have been used for the reactivity estimation. A key limitation of KF and all of its variants is that they cannot account for the constraints on state variables systematically, which may cause the filter’s instability. In this paper, a constrained estimator based on the recursive nonlinear dynamic data reconciliation technique is proposed for the estimation of reactivity and delayed neutron precursors’ concentrations in the nuclear reactor. The effectiveness of the proposed technique has been evaluated through the step test signal in the presence of measurement noise and experimental power variation data sets collected from one of the Indian reactors.