Time Delay Estimation Method Research Articles

Improvement of Flow Velocity Measurement Algorithms Based on Correlation Function and Twin Plane Electrical Capacitance Tomography.

This article discusses the correlation method for time delay estimation, its disadvantages, and drawbacks. It is shown that the correlation method for material velocity measurement based on images of instantaneous changes of the concentration material inside measured by twin planes electrical tomography has serious limitations, especially in the case of plug regime. The basic problem is the non-stationarity of measured data, therefore the requirement of correlability of input data should be fulfilled. The requirement correlatability of input data imposes limitations on the possibility of continuous velocity measurement. This means that the material velocity can only be calculated when data are correlatable. An original algorithm of automatic extraction of the suitable time intervals to calculate material velocity is proposed. The algorithm allows measuring the flow velocity in a proper and accurate way. The examples of the correct velocity calculation, using the proposed concept for the gas-solid flow regime, are presented.

An Adaptive Time Delay Estimation Method for Broadcast Audio Based on Power Cepstrum

Abstract This paper proposes an adaptive time delay estimation method for broadcast audio based on power cepstrum. First, it adds two real-time broadcast audio signals with the same content but with a time delay to obtain a mixed signal, then segment the mixed signal, and obtain a power cepstrum for each mixed signal. Afterwards, the time delay of the two audio signals is determined by using the feature that the power cepstrum of the mixed signal can peak at the time delay. The experimental results show that this method can obtain more accurate time delay results. And it has higher robustness and faster than traditional methods such as generalized cross-correlation time delay estimation algorithm.

Tensor-Based Framework With Model Order Selection and High Accuracy Factor Decomposition for Time-Delay Estimation in Dynamic Multipath Scenarios

Global Navigation Satellite Systems (GNSS) are crucial for applications that demand very accurate positioning. Tensor-based time-delay estimation methods, such as CPD-GEVD, DoA/KRF, and SECSI, combined with the GPS3 L1C signal, are capable of, significantly, mitigating the positioning degradation caused by multipath components. However, even though these schemes require an estimated model order, they assume that the number of multipath components is constant. In GNSS applications, the number of multipath components is time-varying in dynamic scenarios. Thus, in this paper, we propose a tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios. Our proposed approach exploits the estimates of the model order for each slice by grouping the data tensor slices into sub-tensors to provide high accuracy factor decomposition. We further enhance the proposed approach by incorporating the tensor-based Multiple Denoising (MuDe).

A fast pulse time-delay estimation method for X-ray pulsars based on wavelet-bispectrum

X-ray pulsar-based navigation technology provides real-time aerospace information for spacecraft through the received X-ray photons. The time-delay estimation accuracy of the pulse integrated profile is one of the determinants of navigation accuracy. To reduce the computational complexity of the time-delay estimation algorithm for X-ray pulsar integrated pulse profile, we propose a fast time-delay estimation method based on the bispectral algorithm. This method reduces computational complexity by reducing the calculated frequency bands. Wavelet is first used to decompose the pulse profiles and obtain the low-frequency component with a high signal-to-noise ratio. Then, the low-frequency component is used to estimate the time delay of the integrated pulse profile via the bispectral method. Theoretical analysis and experimental results show that the bispectrum-based time-delay estimation method can ignore high-frequency components with considerable noise. Moreover, using only the low-frequency component can substantially reduce computational complexity whilst slightly improving estimation accuracy.

Discrete sliding mode control based on exponential reaching law and time delay estimation for an asymmetrical six‐phase induction machine drive

This study deals with the problem of controlling rotor speed and stator currents of an asymmetrical six-phase induction machine with uncertain dynamics, disturbances, and unmeasurable rotor currents and proposes a robust non-linear variable structure controller. First of all, an outer control loop based on a proportional–integral regulator is performed to control the rotor speed and to construct the desired stator current references. Then, the inner loop is performed based on the proposed method that combines the time delay estimation method and discrete sliding mode control based on exponential reaching law. This structure allows an accurate and simple estimation of uncertainties and rotor currents, a high-tracking precision, a convergence of the stator currents to their known desired references in finite-time and chattering reduction. The design procedure is detailed step by step and the stability analysis and the convergence time are established for the current closed-loop system. Experimental work was carried out on an asymmetrical six-phase induction motor drive to show the effectiveness and performance of the proposed robust non-linear discrete method. The results obtained highlighted the good tracking performance of the stator currents.

A Sound Source Localization Device Based on Rectangular Pyramid Structure for Mobile Robot

A sound source localization device based on a multimicrophone array with the rectangular pyramid structure is proposed for mobile robot in some indoor applications. Firstly, a time delay estimation method based on the cross-power spectral phase algorithm and a fast search strategy of peak value based on the geometric distribution of microphones are developed to estimate the sound propagation delay differences between two microphones. Moreover, a rejection strategy is presented to evaluate the correctness of the delay difference values. And then, the device’s geometric equations based on the time-space mapping relationship are established to calculate the position of the sound source. For fast solving the equations, the multimicrophone array space is divided into several subspaces to narrow the solution range, and Newton iteration algorithm is introduced to solve the equations, while its solution is evaluated by an evaluation mechanism based on coordinate thresholds. Finally, some experiments are carried out to verify the performance of the device, of which the results show that the device can achieve sound source localization with a high accuracy.

Improvement of acoustic water leak detection based on dual tree complex wavelet transform-correlation method

Water leakage is one of the important agendas across the globe thus several effectual systems for leakage detection had been developed with the aim to improve sustainable use of water. Among the methods, acoustic leak detection technique had been proven as a promising approach to detect and localize leaks in water or gas pipeline. However, existence of noise in acoustic signals complicated the leak detection practices. Traditional de-noising methods like filtering and wavelet de-noising are not suitable for non-stationary and broadband acoustic signals. Therefore, Dual Tree Complex Wavelet Transform (DTCWT) is applied in this paper to reduce acoustic noise and decompose signals into several frequency bands. DTCWT decomposition is intended to resolve the problem encountered by the typical correlation-based leak localization method. Due to dispersive and frequency-dependent nature of wave propagation, correlation-based method normally assumes constant wave velocity which results in inaccurate leak source localization. In this paper, signal will be de-noised and decomposed by employing DTCWT. Wave velocity is evaluated based on the dominant frequency and dispersion curve. Then, time delay can be estimated via comparison study among cross correlation, CWT localization and convolution. CWT localization and convolution are proposed as new time-delay estimation method attributable to enhance localization accuracy. Experimental results validated that the proposed method, DTCWT-correlation outperforms other methods with a localization error of 4.67 %. Both CWT localization and convolution are also capable to pinpoint the location of leaks. Besides, leaking and non-leaking condition can be differentiated after multilevel decomposition of DTCWT.

Passive actuator-fault-tolerant path following control of autonomous ground electric vehicle with in-wheel motors

This paper investigates the fault-tolerant path following control problem of autonomous ground electric vehicles with in-wheel motors through hierarchical control strategy. The sliding mode observer with boundary layer is designed to estimate the vehicle state, and the time-delay estimation method is used to compute the actuator fault. Considering the actuator fault, the fault-tolerant path following control strategy is proposed, in which the upper layer controller is developed to achieve path following control and guarantee vehicle stability simultaneously by sliding mode control method, and the lower layer controller is presented to achieve the control efforts of upper layer controller by adaptive orientated tire force allocation method. The simulations are implemented in the CarSim-Simulink co-simulation platform, and the simulation results have verified the effectiveness of proposed fault-tolerant path following control method.

A Cumulative-signals-based Method for Time Delay Estimation

Abstract An original method for time delay estimation is presented. It is based on changing input signals into cumulative ones, followed by determination of inflection points of cumulative curves, and estimation of time delay as time difference of these points’ occurrences. To determine the inflection points, a suitable algorithm is proposed. The preliminary results show that the proposed method is sufficiently efficient, especially in the case of flow measurements based on tomography technique when the cross-correlation function of the signals has no evident peak. This method has no limitations on its application for different types of input signals.

A discrete time domain approach on time delay estimation

A time delay estimation method based on the discrete time domain approach is introduced here. In this dual-channel time delay estimation model, the criterion function compares the time differences of time sequences between channels, not the magnitude values of time functions as in the conventional cross-correlation method. An estimation task is formulated as an extreme value problem in discrete index space. Using the index delay giving extreme value to the criterion function, it is possible to find the best estimate for time delay distribution in the meaning of that criterion. Using this method, the estimated delay distribution and criterion function are clearly separated. Thus, there are no theoretical problems in the determination of the average time delay or velocity in the non-constant or changing time delay case as long as a sufficient statistical similarity (correlation) exists between channel signals. <p class="Abstract">The theoretical values of several criterion functions and the probability of occurrence of an anomalous estimate with the cross-covariance criterion function are derived. A basic performance analysis of the estimation method is presented. Some potential real-time supervision methods based on the use of criterion functions in the detection of the possible unreliability of the time delay estimate are outlined.</p>

Global Ultrasound Elastography in Spatial and Temporal Domains.

In this paper, a novel computationally efficient quasi-static ultrasound elastography technique is introduced by optimizing an energy function. Unlike conventional elastography techniques, three radio frequency (RF) frames are considered to devise a nonlinear cost function consisting of data intensity similarity term, spatial regularization terms and, most importantly, temporal continuity terms. We optimize the aforesaid cost function efficiently to obtain the time-delay estimation (TDE) of all samples between the first two and last two frames of ultrasound images simultaneously, and spatially differentiate the TDE to generate axial strain map. A novelty in our spatial and temporal regularizations is that they adaptively change based on the data, which leads to substantial improvements in TDE. We handle the computational complexity resulting from incorporation of all samples from all three frames by converting our optimization problem to a sparse linear system of equations. Consideration of both spatial and temporal continuity makes the algorithm more robust to signal decorrelation than the previous algorithms. We name the proposed method GUEST: Global Ultrasound Elastography in Spatial and Temporal directions. We validated our technique with simulation, experimental phantom, and in vivo liver data and compared the results with two recently proposed TDE methods. In all the experiments, GUEST substantially outperforms other techniques in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and strain ratio (SR) of the strain images.

Time delay estimation in reverberant and low SNR environment by EMD based maximum likelihood method

In recent times, time delay estimation (TDE) has received significant practical importance in sonar, radar, GPS, and various other fields. In a passive sonar system, estimation of time delay for low frequency and low signal to noise (SNR) acoustic source is a difficult task. If the source and receivers are kept inside the reverberation environment, time delay estimation becomes more difficult because of sound source echo’s. This research work proposes a new TDE approach named empirical mode decomposition maximum likelihood time delay estimation (EMD ML TDE) method, for the low-frequency and low SNR underwater machinery acoustic signal in a reverberant environment. EMD ML TDE method is based on maximum likelihood (ML) method, and it is using empirical mode decomposition (EMD) denoising technique to estimate acoustic sound signal and noise from the noisy reverberant signal. The experimental results are provided that this new approach is better to estimate time delay in reverberant environments.

Adaptive time delay estimation based on the maximum correntropy criterion

In this paper, a novel adaptive time delay estimation (TDE) method under the existence of amplitude attenuation is proposed for the impulsive noise environment. We present a closed form of the recursive solution for the TDE by using the maximum correntropy criterion (MCC). First, a two-step TDE method, which has the advantage of simplicity, is proposed. In this approach, the coefficients in the noncausal finite impulse response (FIR) filter are employed to model the time delay. Furthermore, to improve the robustness of the proposed two-step algorithm, a closed form of the recursive solution for the direct TDE is proposed, which does not have any free parameter, as in the two-step algorithm in gradient-based techniques. Finally, the convergence property regarding the direct TDE algorithm is performed.

Adaptive Phase Transform Method for Pipeline Leakage Detection.

In leak noise correlation surveys, time delay estimation (TDE) is of great importance in pinpointing a suspected leak. Conventional TDE methods involve pre-filtering processes prior to performing cross-correlation, based on a priori knowledge of the leak and background noise spectra, to achieve the desired performance. Despite advances in recent decades, they have not proven to be capable of tracking changes in sensor signals as yet. This paper presents an adaptive phase transform method based on least mean square (LMS) algorithms for the determination of the leak location to overcome this limitation. Simulation results on plastic water pipes show that, compared to the conventional LMS method, the proposed adaptive method is more robust to a low signal-to-noise ratio. To further verify the effectiveness of the proposed adaptive method, an analysis is carried out on field tests of real networks. Moreover, it has been shown that by using the actual measured data, improved performance of the proposed method for pipeline leakage detection is achieved. Hence, this paper presents a promising method, which has the advantages of simple implementation and ability to track changes in practice, as an alternative technique to the existing correlation-based leak detection methods.

Structure and Performance Evaluation of Fractional Lower-Order Covariance Method in Alpha-Stable Noise Environments

Background: All existing time delay estimation methods, i.e. correlation and covariance, depend on second or higher-order statistics which are inapplicable for the correlation of alpha-stable noise signals. Therefore, fractional lower order covariance is the most appropriate method to measure the similarity between the alpha-stable noise signals. Methods: In this paper, the effects of skewness and impulsiveness parameters of alpha-stable distributed noise on fractional lower order covariance method have been analyzed. Results: It has been found that auto-correlation, i.e. auto fractional lower order covariance,\ of non delayed alpha-stable noise signals follows a specific trend for specific ranges of impulsiveness and skewness parameters of alpha-stable distributed noise. The results also depict that, by maintaining the skewness and impulsiveness parameters of α-stable noise signals in a certain suggested range, better auto-correlation can be obtained between the transmitted and the received alpha-stable noise signals in the absence and presence of additive white Gaussian noise. Conclusion: The obtained results would improve signal processing in alpha-stable noise environment which is used extensively to model impulsive noise in many noise-based systems. Mainly, it would optimize the performance of random noise-based covert communication, i.e. random communication.

Current Control of a Six-Phase Induction Machine Drive Based on Discrete-Time Sliding Mode with Time Delay Estimation

This paper proposes a robust nonlinear current controller that deals with the problem of the stator current control of a six-phase induction motor drive. The current control is performed by using a state-space representation of the system, explicitly considering the unmeasurable states, uncertainties and external disturbances. To estimate these latter effectively, a time delay estimation technique is used. The proposed control architecture consists of inner and outer loops. The inner current control loop is based on a robust discrete-time sliding mode controller combined with a time delay estimation method. As said before, the objective of the time delay estimation is to reconstruct the unmeasurable states and uncertainties, while the sliding mode aims is to suppress the estimation error, to ensure robustness and finite-time convergence of the stator currents to their desired references. The outer loop is based on a proportional-integral controller to control the speed. The stability of the current closed-loop system is proven by establishing sufficient conditions on the switching gains. Experimental work has been conducted to verify the performance and the effectiveness of the proposed robust control scheme for a six-phase induction motor drive. The results obtained have shown that the proposed method allows good performances in terms of current tracking, in their corresponding planes.

Methods for mutual time delay estimation of wideband signals based on nonlinear digital filtering

Methods for mutual time delay estimation of wideband signals propagating in satellite communication systems are proposed. The signals are propagated in different channels and received with low signal-to-noise ratio. A characteristic feature of satellite channel is the presence of the Doppler Effect, which leads to a shift and scaling the signal spectrums. The proposed approaches are based on the separation of narrow-band channels from the studied signals, using non-linear digital filtering algorithms in each channel, and subsequent optimal (correlation) processing. The accuracy of the proposed methods and the reliability of the determination of time delay are investigated.

Compressed Sensing OFDM Time Delay Estimation Based on Atomic Evolution and Elimination

Aiming at the problem of time delay estimation for orthogonal frequency division multiplexing (OFDM) signals with small samples, a new compressed sensing time delay estimation method based on atomic evolution and elimination is proposed. This method introduces the idea of evolution and elimination from Darwin's evolutionism, abandons the fixed and invariable way of grid points in the traditional algorithm, takes grid points as adjustable parameters, and updates grid points in each iteration process to promote the evolution of atoms. In order to deal with the off-grid effect, the exponential function is directly modified instead of linear approximation, which effectively eliminates the modeling error caused by the original off-grid algorithm. In the process of calculation, the atomic elimination mechanism is adopted, which reduces the amount of calculation and improves the speed of it. The simulation results show that the proposed algorithm can significantly improve the performance of time delay estimation, especially when using coarse grids. Based on the universal software radio peripheral (USRP), the validity of the proposed algorithm is verified by the actual signal.

PRIDE: Path Integration Based Delay Estimation in Multi-Device Multi-Path Environments

Massive connectivity in the near future puts forward an urgent demand for the accurate time delay estimation (TDE). However, the accuracy of the traditional TDE methods is severely degraded by the multi-path interference (MPI) and multi-device interference. In this paper, we propose a path integration based delay estimation (PRIDE) method. For the first time, the unique delay structure of each device is utilized, and the MPI is converted to an assistance. Considering the practical case where multi-path delays are non-integer times of the sampling period, PRIDE is carried out in two steps to estimate the integer and fractional parts of the delay sequentially. Theoretical analysis and simulations show that the TDE accuracy in the multi-device multi-path environment can be greatly improved by the proposed PRIDE method with comparatively low computational complexity.

Online monitoring of furnace exit gas temperature in power plants

Furnace exit gas temperature (FEGT) is an important physical parameter of energy conservation and environmental protection in a coal-fired boiler furnace; however, to date, there is no effective method for monitoring it continuously online. The recently developed acoustic pyrometry is a comparatively advanced method of temperature measurement which possesses the essential characteristics of traditional temperature measurement approaches. We experimentally implemented online FEGT monitoring using acoustic pyrometry, and we could successfully replace the flue gas temperature probes successfully. Two key problems of the acoustic pyrometry technique, i.e. the acoustic signal and time delay estimation, were solved. We adopted the linear sweeping frequency signal as a sound source signal; its sweeping frequency ranged from 500 to 4000 Hz and the sweeping cycle was 0.1 s. We used a generalized cross-correlation technique with PHAT (Phase Transformation) and ML (Maximum Likelihood) as the time delay estimation method when the boiler was in different states. The actual operation of the monitor indicated that the acoustic pyrometry system was accurate and reliable.