Delay Estimation Method Research Articles

A New Approach for Real-Time Traffic Delay Estimation Based on Cooperative Vehicle-Infrastructure Systems at the Signal Intersection

Confined by the real-time and accuracy of traditional traffic collecting parameters, the existing traffic delay estimation models are generally with poor performance in guiding practical applications. In the Cooperative Vehicle-Infrastructure System, the real-time entire space-time driving state information of a single intelligent vehicle provides new data supporting for road traffic status evaluation. Fully extracting the value of this kind of new data, this paper proposes a new real-time traffic delay estimation method based on the Webster signalized intersection delay model. Taking each intelligent vehicle as a benchmark point, the vehicle arriving/leaving characteristics of the signalized intersection are spatially interpolated by the stopping state of a small amount of benchmark vehicles. In order to obtain the critical queuing dissipation point, the linear fitting method is used to forecast the critical stopping time and further the Markov model is used to estimate the number of queuing vehicles at the critical stopping time. Based on the real-time vehicle queuing characteristics, a new traffic delay estimation model is built according to the Webster estimation mechanism. The case study shows that, compared with the traditional Webster model, the proposed method can effectively improve the traffic delay estimating accuracy.

Adaptive pulsar time delay estimation using wavelet-based RLS

Pulsar time delay needs to be quickly and accurately estimated. In this study, a novel pulsar time delay estimation (PTDE) method based on the wavelet transform and the recursive least squares (RLS) is proposed because of its good robustness and fast convergence of the RLS algorithm. However, the PTDE based on the RLS algorithm (RLSPTDE) leads to high complexity. To address this problem, we initially perform multilevel Haar wavelet transform on the pulsar profile to obtain low-frequency signal. Then, according to the low frequency signal, the adaptive filter based on the RLS algorithm is used to obtain the pre-estimated time delay value. Finally, according to the pre-estimated time delay value, we use the adaptive filter based on the RLS algorithm to perform locally accurate time delay estimation. Certain benefits can be derived from using adaptive filters, especially when underlying parameters, such as signal statistics, are unknown or have changed over time. The theoretical analysis and experimental results show that the proposed method can reduce computational complexity and achieve higher PTDE accuracy than the RLSPTDE.

Low‐complexity methods for joint delay and Doppler estimation of unknown wideband signals

A joint time delay and Doppler shift estimation of unknown wideband signals is studied in the sense that the variation of time delay over time and the migration of Doppler shift over signal frequency cannot be neglected. By partitioning the received signals into short time segments, a novel wideband signal model is proposed. Based on this model, the maximum likelihood estimate (MLE) of the time delay at the starting point of observation and the Doppler shift at the signal carrier frequency is derived. With well compensation of the migrations of these parameters, the MLE derived could achieve higher estimation accuracy. To lower the computational complexity, a fast estimation algorithm based on the Keystone transform is also presented. After correcting the migrations through the Keystone transform, successive one-dimensional Fourier transform, instead of two-dimensional grids search, is used to achieve coherent processing of the received signals. The Cramer-Rao lower bound analysis for wideband cases is presented and the computational complexity of the proposed algorithms is analysed. Simulation results demonstrate the superiority of the proposed methods for wideband cases.

Underwater Sound Source Localization by EMD-Based Maximum Likelihood Method

The underwater object localization is important in defense, underwater biological and environmental applications. Localization using a passive sonar system is a challenging task. It is more challenging when the source and receivers are in the reverberant environment. Time delay estimation (TDE)-based localization is a well-known technique to localize source for last few decades. In this work, empirical mode decomposition maximum likelihood (EMD ML TDE) method is used to estimate the time delay in a reverberant environment. The sound source location is estimated by intersecting spherical surfaces from the time delay. The experimental results prove that EMD ML time delay estimation method is effective to localize a sound source in a reverberant environment.

A Delay-Sensitive Multicast Protocol for Network Capacity Enhancement in Multirate MANETs

Due to significant advances in wireless modulation technologies, some MAC standards such as 802.11a, 802.11b, and 802.11g can operate with multiple data rates for QoS-constrained multimedia communication to utilize the limited resources of MANETs more efficiently. In this paper, by means of measuring the busy/idle ratio of the shared radio channel, a method for estimating one-hop delay is first suggested. Then, by constructing a multicast tree, a delay-sensitive multicast protocol for real-time applications in multirate MANETs is proposed. In order to increase the network capacity, the proposed multicast protocol intends to minimize the sum of the total transmission time of the forwarders and the total blocking time of the blocked hosts, by taking the neighboring information of the forwarders into account and properly adjusting the data rates of the forwarders. Simulation results show that the proposed delay estimation method is more accurate, as compared with previous works. Besides, the proposed multicast protocol can induce higher network capacity, while satisfying the delay requirement.

Highly accurate adaptive TOF determination method for ultrasonic thickness measurement

Determining the time of flight (TOF) is very critical for precise ultrasonic thickness measurement. However, the relatively low signal-to-noise ratio (SNR) of the received signals would induce significant TOF determination errors. In this paper, an adaptive time delay estimation method has been developed to improve the TOF determination’s accuracy. An improved variable step size adaptive algorithm with comprehensive step size control function is proposed. Meanwhile, a cubic spline fitting approach is also employed to alleviate the restriction of finite sampling interval. Simulation experiments under different SNR conditions were conducted for performance analysis. Simulation results manifested the performance advantage of proposed TOF determination method over existing TOF determination methods. When comparing with the conventional fixed step size, and Kwong and Aboulnasr algorithms, the steady state mean square deviation of the proposed algorithm was generally lower, which makes the proposed algorithm more suitable for TOF determination. Further, ultrasonic thickness measurement experiments were performed on aluminum alloy plates with various thicknesses. They indicated that the proposed TOF determination method was more robust even under low SNR conditions, and the ultrasonic thickness measurement accuracy could be significantly improved.

Adaptive fuzzy exponential terminal sliding mode controller design for nonlinear trajectory tracking control of autonomous underwater vehicle

This paper addresses an adaptive fuzzy exponential terminal sliding mode trajectory tracking control design for autonomous underwater vehicle (AUV) using time delay estimation. The proposed control scheme assures quick convergence due to a nonlinear expression in to an integral augmented sliding surface results in nonlinear sliding mode termed as integral-fast terminal sliding mode control (IFTSMC). Furthermore, control law requires no prior knowledge about highly nonlinear underwater vehicle model due to the time delay estimation method. Meanwhile, fuzzy logic system incorporated as adaptation mechanism afford for varying switching function and adaptive exponential reaching law utilized for faster reaching time in path tracking control performance. Finally, the effectiveness and robustness of the proposed control strategy are demonstrated through numerical simulations with Cyclops AUV in presence of parameter perturbations and unidentified disturbances like ocean current, wave and measurement noise.

A Robust and Higher Precision Time Delay Estimation Method Facing Low Signal to Noise Ratio Conditions

Many available signals in the real world are usually weak with impulse noises and/or outliers, and we also need to have higher estimation precision in applications. Our focus of attention is pretty much on integrating robustness and accuracy under lower signal to noise ratio (SNR) with impulse noises. Although traditional fractional adaptive time delay estimation (TDE) methods have higher precision, the results of estimation are unreasonable when the signals contain some impulse noises. While, most proposed robust algorithms later can work well mainly with high SNR. In this paper, considering the practical problem in equipment fault acoustic localization based on TDE methods, an improved robust fractional adaptive time delay estimation method is addressed facing lower SNR conditions. First, the impulse noises are modeled as Alpha stable distribution, and the integer part of TDE is getting by using covariate correlation approach. Then, the integer estimation value is used as initial parameter value of time delay. Covariant sequence is the input of time delay estimator. Next, fractional TDE value is adaptive obtained by iteration under minimum average <i>p</i> norm criterion. Covariant sequence weakens irrelevant noises, meanwhile preserves time delay information between original sequences. Computer simulations and comparative experiments show that improved method has better estimation results. This method is robust and higher precision, and especially under impulse environment and low SNR conditions.

Pulsar time delay estimation method based on two-level compressed sensing

In the traditional compressed sensing algorithms, the precision of the time delay estimation is closely related to the number of atoms in the dictionary. The bigger the atom number, the smaller the atomic interval becomes, thus the higher the accuracy of the time delay estimation will be. However, the bigger atom number leads to a higher calculation load. Considering the limited calculation capacity of on-board computer, in order to fast obtain high-accuracy time delay estimation value of the integrated pulsar profile of pulsar in the X-ray pulsar-based navigation, we propose a time delay estimation method based on two-level compression sensing. Compressed sensing mainly includes three parts:the dictionary, the measurement matrix, and the recovery algorithm. Among them, the dictionary size is one of the most important factors that affect the estimation accuracy of the compressed sensing. Aiming to solve the problem of the greater computational load with the increase of the atom number in the dictionary of compressed sensing while improving the accuracy of estimation, we combine the rough estimation with the precision estimation as a two-level dictionary. In the first level, the global phase estimation of the low-dimensional integrated pulsar profile is carried out by making use of the feature of the large atomic interval and the small atomic amount of the rough estimation dictionary. Specifically, first, construct a coarse estimation dictionary according to the low-dimensional standard pulsar profile. Then make dimension reduction sampling on the low-dimensional integrated pulsar profile by the rough estimation measurement matrix based on low-dimensional Hadamard matrix. Finally, use an orthogonal matching pursuit method to obtain the predictive estimation of delay value. In the second level, by taking advantage of the small atomic intervals and numbers of the precise estimation dictionary which are suitable for local estimation, the exact time delay estimation of the high dimensional integrated pulsar profile is performed. Specifically, the original position is first corrected by using the predictive estimation of time delay value, that is, shifting the initial high-dimensional integrated pulsar profile as the input signal of the second level. Then the precise estimation dictionary is constructed according to the partial signal of the length of the high dimension standard pulse profile, using the precise estimation measurement matrix sampling on high-dimensional integrated pulsar profile to obtain measurement value. Finally, the optimal matching position is obtained through the recovery algorithm, which is then combined with the predictive estimation of delay value to calculate the prcis time delay estimation value. Theoretical analysis and experimental results show that the quantity of data in the two level dictionary is two orders of magnitude smaller than in the traditional dictionary. The proposed method reduces the computational complexity greatly compared with traditional compression sensing method in the same time delay estimation accuracy. Therefore, this method has the advantages of high precision and small calculation load.

Channel and delay estimation for asynchronous physical layer network coding

Relative Delay estimation is an important issue for asynchronous physical layer network coding (PLNC). In this paper, an fast Fourier transform (FFT) based channel and delay estimation method for asynchronous PLNC is proposed. The extended properties of discrete Fourier transform are exploited to design the pilots, which makes the pilots from different nodes orthogonal in frequency domain. Then channels between relay and different terminal nodes are estimated separately in frequency domain. Finally, after inverse FFT, the relative delay is extracted from the estimated time domain channel information. Compared with the existing approaches, the proposed method can achieve almost the same performance, but with significant improvement in computational complexity.

Chain-Based Approach for Fast Through-Silicon-Via Coupling Delay Estimation

A chain-based coupling delay estimation method for through-silicon-vias (TSVs) in 3-D integrated circuits is proposed. Existing works target the worst case scenarios and this leads to inaccurate TSV coupling delay estimations, as the worst case may not occur during normal operation. The proposed method calculates the TSV coupling delay using simulation-based switching data. In addition, our TSV chain method allows us to capture the effects of nonneighboring TSVs accurately. Our simulations show that the error introduced by our method without using HSPICE is less than 10 ps even in TSV-crowded regions.

A Fast Accurate Time Delay Estimation Method in the Digital Predistortion Subsystem

The traditional time delay methods cannot obtain the time delay efficiently in the digital predistortion subsystem (DPDS) when the wide bandwidth, multi-carrier signals with large frequency space is used in the communication system. A time delay estimation method, which can estimate the loop delay between the time delayed feedback signal and the input signal in DPDS with high accuracy and high efficiency, is proposed in this paper. The piecewise-parabolic filter and the bisection method are used to change the sampling start of the feedback signal and to choose the loop delay adjustment range, respectively. Compared with the conventional, the proposed loop delay estimation method can obtain the accurate loop delay using various configuration communication signals in DPDS. Results from experiments validate the proposed method.

Adaptive neural super twisting controller based on terminal sliding mode and time delay estimation method for robotic manipulator

In this paper a robust control approach based on sliding mode theory and artificial neural network technique was proposed for trajectory tracking mode of n-DOF robot manipulator. Time delay estimation method and non-singular terminal sliding mode control were used to design the nominal control part of the sliding mode control without any knowledge about the robot model. Super twisting algorithm was designed using radial based function neural networks to replace the discontinuous control part. In order to test the effectiveness of the proposed approach, it was applied to 2-DOF robotic manipulator and compared with a classical approach.

Adaptive neural super twisting controller based on terminal sliding mode and time delay estimation method for robotic manipulator

Adaptive neural super twisting controller based on terminal sliding mode and time delay estimation method for robotic manipulator

Automatic dependent surveillance‐broadcast time delay estimation based on extended recursive maximum correntropy algorithm

In this study, a novel adaptive algorithm, termed extended recursive maximum correntropy (EX-RMC), is proposed to estimate the time delay of automatic dependent surveillance-broadcast (ADS-B), an up-to-date surveillance technology in civil aviation. The proposed algorithm is designed to deal with both the random time-varying delay and the impulsive noise. The superiority of EX-RMC in tracking time-varying state of an unknown plant has been verified by simulation experiments. On-site experiments are also carried out to demonstrate the practical value of the ADS-B time delay estimation method based on EX-RMC.

Research on the location of acoustic emission source of rock breaking point by using phase difference method and Geiger algorithm

Geiger iterative algorithm is very strict to the initial value. If the initial value is not selected suitably, it is difficult to enter the convergence range, thus increasing the number of iterations. The acoustic emission source location based on phase difference time delay estimation method reduces the error of acoustic emission location, but it has some shortcomings in accuracy. Based on the above problems, this paper presents a new algorithm for Geiger optimization based on source localization. Firstly, the initial value of Geiger is obtained by using the phase difference method. Then, the optimal solution is obtained by the iterative solution of Geiger algorithm and the least square method. The simulation results show that this method can effectively solve the problem of selecting the initial value of Geiger, so that it can quickly enter the convergence range, improving the convergence speed and positioning accuracy, comparing the positioning results of the United States PCI-2 type acoustic emission instrument, the average error reduced by about 5 mm.

Estimating the unknown time delay in chemical processes

Although time delay is an important element in both system identification and control performance assessment, its computation remains elusive. This paper proposes the application of a least squares support vector machines driven approach to the problem of determining constant time delay for a chemical process. The approach consists of two steps, where in the first step the state of the system and its derivative are approximated based on the LS-SVM model. The second step consists of modeling the delay term and estimating the unknown model parameters as well as the time delay of the system. Therefore the proposed approach avoids integrating the given differential equation that can be computationally expensive. This time delay estimation method is applied to both simulation and experimental data obtained from a continuous, stirred, heated tank. The results show that the proposed method can provide accurate estimates even if significant noise or unmeasured additive disturbances are present.

A Continuous Wavelet Transform Based Time Delay Estimation Method for Long Range Fiber Interferometric Vibration Sensor

We propose a time delay estimation (TDE) method based on a continuous wavelet transform (CWT), which can be applied to the different-wavelength-based fiber interferometric vibration sensors. Using a CWT-based characteristic extraction algorithm, we successfully eliminate the asymmetry of the interference outputs that would seriously deteriorate the positioning accuracy of the sensor. A positioning measurement experiment using an asymmetric dual Mach-Zehnder interferometric sensor was carried out to verify the effectiveness of the proposed method. The experiment achieved a positioning accuracy of 0.029% at the sensing length of 85 km, with a mean processing time of 591.2 ms.

Model‐based super‐resolution time‐delay estimation with sample rate consideration

Time delay estimation is of great significance in multipath propagation to recover overlapped signals and identify the channel characteristics. However, achieving a high accuracy in this purpose may pose many problems in ultra-wideband (UWB) applications. In UWB systems, capturing a signal with high sampling rates cannot readily be done; hence classical methods for time delay estimation substantially lose their precision. To overcome this challenge, the authors incorporate a robust estimation approach and supplementary sampling process in a unified algorithm to retrieve time delays from signals with low sampling rates. Toward that pursuit, a model based least squares estimator is proposed as the main approach to calculate time delays and a modified method based on multiple signal classification (MUSIC) is also presented for comparison aim. Then, the authors have developed the algorithm by embedding two additional pre-processing steps of under sampling and interpolation to achieve a higher sampling rate and a better resolution. To show the high accuracy of work, root mean square error is computed in different values of time delay. Simulation and experiment results show the considerably higher precision of the proposed algorithm in comparison with presented MUSIC type method and also previously proposed methods in literature.

On Data-Driven Delay Estimation for Media Cloud

It is well known that delay announcement is an economical and efficient way to improve the user satisfaction since the waiting time (delay) is an important performance metric for media cloud. However, how to accurately estimate the delay in an online-implementation manner is still an open and challenging problem. In this study, we study the data-driven delay estimation in a practical cloud media with heavy traffic, and propose an accurate estimation strategy only with a small amount of dataset. Importantly, we explicitly model the subjective announcement-dependent user response via an objective response function through the elaborate data analysis and model. On the theoretical end, the user response in terms of the estimated delay is characterized by the time window data-cleaning, where an appropriate dataset is set up through the window function analysis. On the technical end, we analyze the conditions for data-driven delay estimation, and prove that the proposed method is able to obtain a near-optimal solution within a finite time period. Extensive simulation results demonstrate the efficiency of the proposed delay estimation method.