scholarly journals Detection of Direction-Of-Arrival in Time Domain Using Compressive Time Delay Estimation with Single and Multiple Measurements

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5431
Author(s):  
Youngmin Choo ◽  
Yongsung Park ◽  
Woojae Seong
Keyword(s):  
Time Delay ◽  
Time Domain ◽  
Time Delays ◽  
Matched Filter ◽  
Measurement Data ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Multiple Measurements

The compressive time delay estimation (TDE) is combined with delay-and-sum beamforming to obtain direction-of-arrival (DOA) estimates in the time domain. Generally, the matched filter that detects the arrivals at the hydrophone is used with beamforming. However, when the ocean noise smears the arrivals, ambiguities appear in the beamforming results, degrading the DOA estimation. In this work, compressive sensing (CS) is applied to accurately evaluate the arrivals by suppressing the noise, which enables the correct detection of arrivals. For this purpose, CS is used in two steps. First, the candidate time delays for the actual arrivals are calculated in the continuous time domain using a grid-free CS. Then, the dominant arrivals constituting the received signal are selected by a conventional CS using the time delays in the discrete time domain. Basically, the compressive TDE is used with a single measurement. To further reduce the noise, common arrivals over multiple measurements, which are obtained using the extended compressive TDE, are exploited. The delay-and-sum beamforming technique using refined arrival estimates provides more pronounced DOAs. The proposed scheme is applied to shallow-water acoustic variability experiment 15 (SAVEX15) measurement data to demonstrate its validity.

scholarly journals Methods for broadband signals mutual time delays estimating enhancement

2019 ◽  
Vol 30 ◽  
pp. 03012
Author(s):  
Ilya Grin ◽  
Oleg Morozov
Keyword(s):  
Time Delay ◽  
Computational Efficiency ◽  
Radiation Source ◽  
Time Delays ◽  
Time Delay Estimation ◽  
Ambiguity Function ◽  
Delay Estimation ◽  
Reliability Criterion ◽  
Optimal Processing ◽  
Narrowband Channels

This paper considers methods for estimating the mutual time delay of broadband signals recorded by satellites based multi-position systems for determining the location of a radiation source. All methods considered are based on modified algorithms for calculating the ambiguity function. The presented algorithms are based on the extraction of narrowband channels from the studied signals and their further optimal processing. The reliability criterion for mutual time delay estimation by the presented methods was evaluated. Based on the results and analysis of computational efficiency, viability of methods considered and their modifications was determined.

scholarly journals Evaluation of Three Different Approaches for Automated Time Delay Estimation for Distributed Sensor Systems of Electric Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 351 ◽  
Author(s):  
Jakob Pfeiffer ◽  
Xuyi Wu ◽  
Ahmed Ayadi
Keyword(s):  
Time Delay ◽  
Electronic Control Unit ◽  
Measurement Data ◽  
Control Unit ◽  
Real Data ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Distributed Sensor ◽  
Automotive Electronic ◽  
Interesting Approach

Deviations between High Voltage (HV) current measurements and the corresponding real values provoke serious problems in the power trains of Electric Vehicle (EVs). Examples for these problems have inaccurate performance coordinations and unnecessary power limitations during driving or charging. The main reason for the deviations are time delays. By correcting these delays with accurate Time Delay Estimation (TDE), our data shows that we can reduce the measurement deviations from 25% of the maximum current to below 5%. In this paper, we present three different approaches for TDE. We evaluate all approaches with real data from power trains of EVs. To enable an execution on automotive Electronic Control Unit (ECUs), the focus of our evaluation lies not only on the accuracy of the TDE, but also on the computational efficiency. The proposed Linear Regression (LR) approach suffers even from small noise and offsets in the measurement data and is unsuited for our purpose. A better alternative is the Variance Minimization (VM) approach. It is not only more noise-resistant but also very efficient after the first execution. Another interesting approach are Adaptive Filter (AFs), introduced by Emadzadeh et al. Unfortunately, AFs do not reach the accuracy and efficiency of VM in our experiments. Thus, we recommend VM for TDE of HV current signals in the power train of EVs and present an additional optimization to enable its execution on ECUs.

Root-Cause Analysis Based on Time Delay Estimation for Alarm Systems in Power Grids

2011 ◽  
Vol 354-355 ◽  
pp. 943-946
Author(s):  
Yi Shu Zhao ◽  
Xi Nong Li ◽  
Ke Jun Li
Keyword(s):  
Time Delay ◽  
Time Delays ◽  
Estimation Method ◽  
Root Cause Analysis ◽  
Time Delay Estimation ◽  
Power Grids ◽  
Delay Estimation ◽  
Consistency Check ◽  
Cause Analysis ◽  
Root Cause

This paper studies the root-cause analysis based on the time delays among various signals, for reducing nuisance alarms in modern industrial systems including power grids. Time delays are estimated via the revised nearest neighbor imputation method, and are validated via the subsequent consistency check. Numerical examples including the IEEE 5-node system as a prototype power grid are provided to demonstrate the effectiveness of the proposed time delay estimation method and the subsequent consistency check.

Under-ice target echo time delay estimation using ℓp-norm based matched filter

2022 ◽  
Vol 185 ◽  
pp. 108391
Author(s):  
Hang Dong ◽  
Siyuan Cang ◽  
Xueli Sheng ◽  
Jingwei Yin ◽  
Longxiang Guo
Keyword(s):  
Time Delay ◽  
Matched Filter ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Echo Time

scholarly journals A discrete time domain approach on time delay estimation

ACTA IMEKO ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 77
Author(s):  
Jorma Kekalainen
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Time Domain ◽  
Estimation Method ◽  
Extreme Value ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Criterion Function ◽  
Delay Distribution ◽  
Criterion Functions

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>

Parameter identification of nonlinear multirate time-delay system with uncertain output delays

2017 ◽  
Vol 40 (12) ◽  
pp. 3498-3506 ◽  
Author(s):  
Xianqiang Yang ◽  
Weili Xiong ◽  
Zeyuan Wang ◽  
Xin Liu
Keyword(s):  
Time Delay ◽  
Time Delays ◽  
Finite Impulse Response ◽  
Delay System ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Model Parameters ◽  
Delay Model ◽  
Process Data ◽  
Time Delay System

The joint parameter and time-delay estimation problems for a class of nonlinear multirate time-delay system with uncertain output delays are addressed in this paper. The practical process typically has time-delay properties and the process data are often multirate, sampled with output data inevitably corrupted by uncertain delays. The linear parameter varying (LPV) finite impulse response (FIR) multirate time-delay model is initially built to describe the considered system. The problems of over-parameterization and the existence of both continuous model parameters and discrete time-delays have made the conventional maximum likelihood difficult to solve the considered problems. In order to handle these problems, the joint parameter and time-delay estimation for the LPV FIR multirate time-delay model are formulated in the expectation-maximization scheme, and the algorithm to estimate the model parameters and time-delays is derived, simultaneously based on multirate process data. The efficacy of the proposed method is verified through a numerical simulation and a practical chemical plant.

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