Time Of Arrival Estimation Research Articles

Potential of Low-Frequency Automated Vehicle Location Data for Monitoring and Control of Bus Performance

The potential of low-frequency bus localization data for the monitoring and control of bus system performance is investigated in this paper. It is shown that data with a sampling rate as low as 1 min, when processed appropriately, can provide ample information. Accurate estimates of stop arrival and departure times are obtained; these estimates in turn allow the analysis of headways and travel times. A three-parameter gamma family of distributions is fitted for headways at the stops along a bus line. The evolution of the parameters demonstrates critical points on the line where bus bunching is significantly increased. Moreover, this analysis allows differentiating problems associated with varying passenger demand from uncertainties associated with traffic conditions. Furthermore it is shown that expected travel time and travel time variability can be calculated from low-frequency localization data. Finally, the way in which the results can be used to calibrate a simulation model that can test bus control strategies is presented. The methods are applied and validated to data obtained from Bus Route Number 1 in Boston, Massachusetts.

A new automatic S-onset detection technique: Application in local earthquake data

Algorithms that deal with the automatic [Formula: see text]-onset time identification problem are a topic of ongoing research. Modern dense seismic networks used for earthquake location, seismic tomography investigations, source studies, early warning, etc., demand accurate automatic S-wave picking. Most of the techniques that have been proposed up to now are mainly based on the polarization features of the seismic waves. We propose a new time domain method for the automatic determination of the [Formula: see text]-phase arrival onsets, and present its implementation on local earthquake data. Eigenvalue analysis takes place over small time intervals, and the maximum eigenvalue which is obtained on each step is retained for further processing. In this way, a time series of maximum eigenvalues is formed, which serves as a characteristic function. We obtain a first [Formula: see text]-phase arrival time estimation by applying the kurtosis criterion on the derived characteristic function. Furthermore, a multiwindow approach combined with an energy-based weighting scheme is also applied, to reduce the algorithm’s dependence on the moving window’s length and provide a weighted [Formula: see text]-phase onset. Automatic picks were compared against manual reference picks, resulting in mean residual time of 0.051 s. Moreover, the proposed technique was subjected to a noise robustness test and sustained a good performance. The mean residual time remained lower than 0.1 s, for noise levels between [Formula: see text] up to 8 dB. The proposed method is easy to implement, because it is almost parameter free and demands low computational resources.

A Comparative Study of Amplitude and Timing Estimation in Experimental Particle Physics using Monte Carlo Simulation

Optimal detection of liquid ionization calorimeter signal in experimental particle physics is considered. A few linear and nonlinear approaches for amplitude and arrival time estimation based on the χ2 function are compared in simulation considering the noise sample correlation introduced by the analog pulse shaper. The estimation bias of the first-order approximation, a.k.a linear optimal filtering, is studied and contrasted to those of the second-order as well as the exhaustive search. A gradient-descent technique is presented as an alternative to the exhaustive search with significantly reduced search time and computation complexity. Results from various pulse shapers including the CR-RC2, CR-RC3, and CR2-RC2 are also compared.

Time of arrival and power delay profile estimation for IR-UWB systems

In time of arrival (TOA) estimation of received ultra-wideband (UWB) pulses, traditional maximum likelihood (ML) and generalized likelihood estimators become impractical because they require sampling at the Nyquist rate. Sub-Nyquist ML-based TOA estimation currently assumes a priori knowledge of the UWB channels in the form of the average power delay profile (APDP). In this paper, instead of assuming a known APDP, we propose and investigate a joint estimator of the TOA and the APDP. We assume a multi-cluster parametric APDP model and estimate its parameters via a least-squares approach; the estimated APDP is then used in connection with a ML criterion to obtain the TOA estimate. The proposed method has a low sampling rate requirement and is well-suited for real-time implementation. Simulation results show that it can achieve improved accuracy in practical UWB TOA estimation scenarios, when compared to other competing approaches.

High Resolution Cognitive Radio-Based Concatenated Spectrum Time-of-Arrival Estimation

This paper proposes high-precision, time-of-arrival (TOA) estimation by concatenating non-contiguous and non-equal white spaces in the spectrum. White spaces are identified and allocated by the capabilities of cognitive radios (CR). A simple radio system that enables sequential concatenation of non-contiguous bands is introduced. The paper aims to design signal-processing techniques for the proposed radio that maintain a TOA performance comparable to that of utilizing a bandwidth equivalent to the addition of all white spaces. This work also investigates two potential high resolutions, TOA estimation architectures that are applicable to CR-based systems. The first approach estimates TOA over each sub-band and then optimally fuses the estimated TOAs. In the second technique, channels estimated over sub-bands are concatenated and a TOA-estimation method is applied to the whole available spectrum. The Cramer–Rao bound (CRB) of the TOA estimation for both approaches is computed. Minimum mean square estimation (MMSE) algorithm is applied to evaluate the performance of the proposed system. Simulations are concluded to study the performance in terms of the variance of error. Moreover, the complexity of the proposed concatenation method is evaluated.

Particle filtering for arrival time tracking in space and source localization

Locating and tracking a source in an ocean environment and estimating environmental parameters of a sound propagation medium are critical tasks in ocean acoustics. Many approaches for both are based on full field calculations which are computationally intensive and sensitive to assumptions on the structure of the environment. Alternative methods that use only select features of the acoustic field for localization and environmental parameter estimation have been proposed. The focus of this paper is the development of a method that extracts arrival times and amplitudes of distinct paths from measured acoustic time-series using sequential Bayesian filtering, namely, particle filtering. These quantities, along with complete posterior probability density functions, also extracted by filtering, are employed in source localization and bathymetry estimation. Aspects of the filtering methodology are presented and studied in terms of their impact on the uncertainty in the arrival time estimates. Using the posterior probability densities of arrival times, source localization and water depth estimation are performed for the Haro Strait Primer experiment; the results are compared to those of conventional methods. The comparison demonstrates a significant advantage in the proposed approach.

Compression functions used in the algorithms for the estimation of signal arrival time under high-precision event timing

The possibilities are studied for improving the accuracy of the interpolation method for measuring the event occurrence time based on the digital processing of signals associated with the events. The problem of estimating the time of the analog signal arrival is formulated and solved as a problem of finding a fixed point of some contraction mapping. The compression function is constructed on the basis of spectral coefficients of a trigonometric series that approximates the shape of the analog signal. The accuracy potential of the interpolation measurement technique is illustrated by the results of computer simulation.

Performance Evaluation of a Low-Complexity Receiver Concept for TOA-Based Ultrawideband Ranging

In this paper, a novel low-complexity time-of-arrival (TOA) estimation strategy and a conceptual receiver setup for ultrawideband (UWB) signals is proposed, and its performance is evaluated. The receiver consists of an analog peak detector followed by two RC filters with different time constants. From two exponentially decaying signals, the TOA of the first peak of the received signal is reconstructed. This solution requires simple signal processing and sampling rates on the order of only a few tens of megahertz. At the same time, the achieved range error is at centimeter level since the large signal bandwidth used is fully exploited. To allow for performance flexibility, a statistical framework is proposed in which results of multiple initial TOA estimates are combined into a final estimate. Impairments due to narrowband interference are investigated, and a coarse acquisition scheme based on maximum energy detection is described. This last step is required for proper operation of the TOA receiver. A link budget analysis, which is based on the FCC power limitations for UWB signals, shows that reliable ranging is feasible up to 300 m in line-of-sight situations and up to 60 m in non-line-of-sight cases. The presented solution avoids the main technological challenges, namely extremely high sampling rates and complex processing at the receiver, which currently limit practical implementations of high-precision UWB positioning systems.

A Space–Time Extended MUSIC Estimation Algorithm for Wide Band Signals

The direction of arrival (DOA) estimation and the time of arrival (TOA) estimation using an antennas array are two key problems in signal processing. Recently, joint estimation of DOA and TOA has attracted considerable attentions for several applications, such as for telecommunications, military and medical. In this paper, a new method is proposed for wide band signals localization. This algorithm is presented with high-resolution localization capabilities, based on the Extended MUSIC algorithm. The capacities of the proposed approach are compared with high resolution algorithms. The new method showed interesting performance in terms of resolution and precision. In addition, the algorithm will show a good ability to estimate a number of sources that exceed the number of sensors in the antennas array which is a constraint in other algorithms.

Indoor Positioning Using UWB-IR Signals in the Presence of Dense Multipath with Path Overlapping

This paper presents a method for positioning using ultra-wideband impulse radio (UWB-IR) signals that is robust in indoor environments characterized by dense multipath channel with path overlapping. Path overlapping effects arising from multipath in dense cluttered environments decrease the direct path resolution in time domain, and hence induce time-of-arrival (TOA) and angle-of-arrival (AOA) based positioning inaccuracy. To mitigate this problem, system design that is capable of resolving the closely-spaced multipath at low cost is of value. Our method yields the least-squares estimation of joint TOA and AOA with low computational cost. It is based on the spectral observation of beam forming, in which the path overlapping effect is mitigated using multipath-aided acquisition. The computational cost is reduced using in-band power spectrum and accurate initial estimations. The performance is verified both in IEEE 802.15.4a CM3 channel model and in a real environment. Simulation results in CM3 channel model show that the TOA and AOA estimation improvements on average are 2.4cm and 13.1° in the dense multipath scenario. Measurement in an indoor open hall environment shows that the AOA error decreases from 10.6° to 7.2°, and the TOA error decreases from 2.1cm to 1.9cm when the path overlapping effects are mitigated in the range of 21m.

Dual Shift Invariant TOA Estimation Algorithm for Multi-Band Signals

This letter proposes a dual shift invariant TOA estimation method for multi-band signals. Although conventional shift invariant TOA estimation methods have been proposed to exploit a single shift invariant structure of the transformed signals, the proposed method is developed to make use of the dual shift invariant structure of the transformed multi-band signals. The performance of the proposed method is compared with that of the Cramer-Rao lower bound (CRLB) and conventional algorithms such as MUSIC, matrix pencil, TLS-ESPRIT in additive white Gaussian noise (AWGN) and multipath channel.

An Incoherent Two-Step TOA Estimation Algorithm based on Train of IR-UWB Pulses

An Incoherent Two-Step TOA Estimation Algorithm based on Train of IR-UWB Pulses

Using sonic anemometer temperature to measure sensible heat flux in strong winds

Abstract. Sonic anemometers simultaneously measure the turbulent fluctuations of vertical wind (w') and sonic temperature (Ts'), and are commonly used to measure sensible heat flux (H). Our study examines 30-min heat fluxes measured with a Campbell Scientific CSAT3 sonic anemometer above a subalpine forest. We compared H calculated with Ts to H calculated with a co-located thermocouple and found that, for horizontal wind speed (U) less than 8 m s−1, the agreement was around ±30 W m−2. However, for U ≈ 8 m s−1, the CSAT H had a generally positive deviation from H calculated with the thermocouple, reaching a maximum difference of ≈250 W m−2 at U ≈ 18 m s−1. With version 4 of the CSAT firmware, we found significant underestimation of the speed of sound and thus Ts in high winds (due to a delayed detection of the sonic pulse), which resulted in the large CSAT heat flux errors. Although this Ts error is qualitatively similar to the well-known fundamental correction for the crosswind component, it is quantitatively different and directly related to the firmware estimation of the pulse arrival time. For a CSAT running version 3 of the firmware, there does not appear to be a significant underestimation of Ts; however, a Ts error similar to that of version 4 may occur if the CSAT is sufficiently out of calibration. An empirical correction to the CSAT heat flux that is consistent with our conceptual understanding of the Ts error is presented. Within a broader context, the surface energy balance is used to evaluate the heat flux measurements, and the usefulness of side-by-side instrument comparisons is discussed.

Threshold Selection for Ultra-Wideband TOA Estimation based on Neural Networks

Because of the good penetration into many common materials and inherent fine resolution, Ultra-Wideband (UWB) signals are widely used in remote ranging and positioning applications. On the other hand, because of the high sampling rate, coherent Time of Arrival (TOA) estimation algorithms are not practical for low cost, low complexity UWB systems. In order to improve the precision of TOA estimation, an Energy Detection (ED) based non-coherent TOA estimation algorithm using Artificial Neural Networks (ANN) is presented which is based on the skewness after energy detection. The expected values of skewness and kurtosis with respect to the Signal to Noise Ratio (SNR) are investigated. It is shown that the skewness is more suitable for TOA estimation. The best threshold values for different SNRs are investigated and the effects of integration period and channel modes are examined. Comparisons with other ED based algorithms show that in CM1 and CM2 channels, the proposed algorithm provides higher precision and robustness in both high and low SNR environments.

Sound speed estimation and source localization with particle filtering and a linearization approach

In previous work, a particle filtering method was developed that provided estimates of multipath arrival times from short-range data and, subsequently, employed them in geometry, bathymetry, and sound speed inversion. The particle filter provided probability density functions of arrival times, that were then “propagated” backwards through a sound propagation model for inversion. That implies that every particle from the probability density is employed in the inversion scheme, creating a potentially computationally cumbersome process. In this work, we develop a new method for such parameter estimation which relies on linearization. The novel aspect is that the Jacobian matrix now includes derivatives with respect to Empirical Orthogonal Function coefficients. The approach, requiring only a few iterations to converge, is particularly efficient. Results from the application of this technique to synthetic and real (SW06) data are presented and compared to full-field inversion estimates. [Work supported by ONR and the NSF CSUMS program.]

Remotely-sensed TOA interpretation of synthetic UWB based on neural networks

Because of the good penetration into many common materials and inherent fine resolution, Ultra-Wideband (UWB) signals are widely used in remote sensing applications. Typically, accurate Time of Arrival (TOA) estimation of the UWB signals is very important. In order to improve the precision of the TOA estimation, a new threshold selection algorithm using Artificial Neural Networks (ANN) is proposed which is based on a joint metric of the skewness and maximum slope after Energy Detection (ED). The best threshold based on the signal-to-noise ratio (SNR) is investigated and the effects of the integration period and channel model are examined. Simulation results are presented which show that for the IEEE802.15.4a channel models CM1 and CM2, the proposed ANN algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

Semi-coherent time of arrival estimation using regression

Time of arrival (ToA) estimation is essential for many types of remote sensing applications including radar, sonar, and underground exploration. The standard method for ToA estimation employs a matched filter for computing the maximum likelihood estimator (MLE) for ToA. The accuracy of the MLE decreases rapidly whenever the amount of noise in a received signal rises above a certain threshold. This well-known threshold effect is unavoidable in several important applications due to various limitations on the power and the spectrum of a narrowband source pulse. A measurement performed in the presence of the threshold effect employs a receiver which operates in the semi-coherent state. Therefore, the conventional methods assuming a coherent state receiver should be adapted to the semi-coherent case. In this paper, a biosonar-inspired method for the semi-coherent ToA estimation is described. The method abandons the exploration of an echo signal by a single matched filter in favor of the analysis by multiple phase-shifted unmatched filters. Each phase-shifted unmatched filter gives rise to a biased ToA estimator. The described method uses regression for combining these estimators into a single unbiased ToA estimator that outperform the MLE in the presence of the threshold effect.

Parameters affecting the resolution and accuracy of 2-D quantitative shear wave images

Time-of-flight methods allow quantitative measurement of shear wave speed (SWS) from ultrasonically tracked displacements following impulsive acoustic radiation force excitation in tissue. In heterogeneous materials, reflections at boundaries can distort the wave shape and confound determination of the wave arrival time. The magnitude of these effects depends on the shear wavelength of the excitation, the kernel size used to calculate the SWS, and the method used to determine the wave arrival time. In this study, we perform a parametric analysis of these factors using finite element modeling of the tissue response and simulated ultrasonic tracking. Two geometries are used, a stiff vertical layer and a stiff spherical inclusion, each in a uniform background. Wave arrival times are estimated using the peak displacement, peak slope of the leading edge, and cross-correlation methods. Results are evaluated in terms of reconstruction accuracy, resolution, contrast, and contrast-to-noise ratio of reconstructed SWS images. Superior results are obtained using narrower excitation widths and arrival time estimators which identify the leading edge of the propagating wave. The optimal kernel size is determined by a tradeoff between improved accuracy for larger kernels at the expense of spatial resolution.

Threshold Selection for TOA Estimation based on Skewness and Slope in Ultra-wideband Sensor Networks

Accurate localization has gained significant interest within sensor networks but because of the high sampling rate, Matched Filter (MF) based coherent Time of Arrival (TOA) estimation algorithms are not practical for low cost, low complexity Ultra-wideband (UWB) ranging, positioning and tracking systems. In this paper, an Energy Detection (ED) based non-coherent TOA estimation algorithm is presented where the TOA is estimated via Threshold Crossing (TC). The expected values of skewness, maximum slope, kurtosis and standard deviation with respect to the Signal to Noise Ratio (SNR) are investigated using the IEEE 802.15.4a Channel Models (CM). It is shown that the skewness and maximum slope are more sensitive to the SNR and thus more suitable for TOA estimation. To improve the precision of ED based TOA estimation, especially in low SNR environments, a new threshold selection algorithm is proposed which is based on a joint metric of the skewness and maximum slope. The best threshold values for different SNRs are investigated and the effects of integration period and channel models are examined. Comparisons with other ED based algorithms show that in both the CM1 and CM2 channels, the joint metric provides higher precision and robustness in both high and low SNR environments.

A New Diversity Combining Scheme Based on Interleaving Method for Time-of-arrival Estimation of Chirp Signal

A new diversity combining scheme is proposed for time-of-arrival (TOA) estimation of chirp signal in dense multipath channel. In the multipath channel, the performance of TOA estimation using conventional correlation matrix-based diversity combining scheme is degraded due to the lack of de-correlation effect. To increase the de-correlation effect, the proposed diversity scheme employs interleaving method based on the property of de-chirped signal. As a result, the proposed scheme increases de-correlation effect and also reduces the noise of TOA estimation. Finally, the diversity achieved from the proposed scheme improves TOA estimation performance. The de-correlation effect is analyzed mathematically. The estimation accuracy of the proposed diversity scheme is superior to that of conventional diversity scheme in multipath channel.