Joint Time Of Arrival Research Articles

Low-Complexity Joint Angle of Arrival and Time of Arrival Estimation of Multipath Signal in UWB System.

In an ultra-wideband (UWB) system, the two-dimensional (2D) multiple signal classification (MUSIC) algorithms based on high-precision 2D spectral peak search can jointly estimate the time of arrival (TOA) and angle of arrival (AOA). However, the computational complexity of 2D-MUSIC is very high, and the corresponding data model is only based on the dual antennas. To solve these problems, a low-complexity algorithm for joint AOA and TOA estimation of the multipath ultra-wideband signal is proposed. Firstly, the dual antenna sensing data model is extended to the antenna array case. Then, based on the array-sensing data model, the proposed algorithm transforms the 2D spectral peak search of 2D-MUSIC into a secondary optimization problem to extract the estimation of AOA via only 1D search. Finally, the acquired AOA estimations are brought back, and the TOA estimations are also obtained through a 1D search. Moreover, in the case of an unknown transmitted signal waveform, the proposed method can still distinguish the main path signal based on the time difference of arrival of different paths, which shows wider applications. The simulation results show that the proposed algorithm outperforms the Root-MUSIC algorithm and the estimation of signal parameters using the rotational invariance techniques (ESPRIT) algorithm, and keeps the same estimation accuracy but with greatly reduced computational complexity compared to the 2D-MUSIC algorithm.

A Single-Site Vehicle Positioning Method in the Rectangular Tunnel Environment

Due to the satellite signals are blocked, it is difficult to obtain the vehicle position in the tunnels. We propose a single-site vehicle localization scheme for the rectangular tunnel environment, where most satellite-based positioning methods can not provide the required localization accuracy. In the non-line-of-sight (NLOS) scenarios, we make use of the reflection paths as assistants for vehicle positioning. Specifically, first, the virtual stations are established based on the actual geometrical structure of the tunnel. Second, we use the direction-of-arrival (DOA) and time-of-arrival (TOA) information of reflection paths from two tunnel walls to achieve vehicle positioning. Especially, the Cramer-Rao lower bound (CRLB) of the joint TOA and DOA localization for NLOS propagations in a two-dimensional (2D) space is derived. In addition, based on the localization algorithms with and without filters, we assess the localization performance. In the line-of-sight (LOS) scenarios, we use the LOS path and two reflection paths from the tunnel walls to estimate the vehicle location. First, virtual base stations are established. Second, based on the obtained TOA information, different positioning algorithms are used to estimate the vehicle location. Simulation results illustrate that the proposed positioning approach can provide a small root mean square error. The localization algorithms using filters improve the localization accuracy, compared with the positioning algorithm without using filters, namely, the two-stage weighted least squares (TSWLS) algorithm. Moreover, the Unscented Particle Filter (UPF) algorithm achieves better positioning accuracy than other methods (i.e., Unscented Kalman Filter (UKF), Extended Kalman Filter (EKF), TSWLS algorithms).

Joint TOA and DOA Estimation for UWB Systems with Antenna Array via Doubled Frequency Sample Points and Extended Number of Clusters

The ultra-wideband (UWB) system, which transmits information using nanosecond or even sub-nanosecond pulses, has been widely applied in precise positioning. In this paper, we investigate the problem of the time of arrival (TOA) estimation and the direction of arrival (DOA) estimation in the UWB systems with antenna array and propose a joint TOA and DOA estimation algorithm with doubled frequency sample points and extended number of clusters. Specifically, the proposed algorithm uses two antennas to receive impinging signals and utilizes the conjugate symmetry characteristic of the delay matrices to extend the sample points as well as the number of clusters. Moreover, in order to obtain TOA estimates with low computational complexity, the proposed algorithm transforms the two-dimensional (2D) spectral search to one-dimensional (1D) searches. The DOA estimates can then be achieved by using the TOA estimation results and the geometric information. Simulation results are given to testify the performance of the proposed algorithm.

A Joint TOA and DOA Acquisition and Tracking Approach for Positioning With LTE Signals

A receiver structure is proposed to jointly estimate the time-of-arrival (TOA) and azimuth and elevation angles of direction-of-arrival (DOA) from received cellular long-term evolution (LTE) signals. In the proposed receiver, a matrix pencil (MP) algorithm is used in the acquisition stage to obtain a coarse estimate of the TOA and DOA. Then, a tracking loop is proposed to refine the estimates and jointly track the TOA and DOA changes. The performance of the acquisition and tracking stages are evaluated in the presence of noise and multipath. Simulation results are provided to validate the analytical results. The Cramér-Rao lower bounds (CRLBs) of the TOA and DOA estimates are derived to compare the performance of the proposed acquisition and tracking approaches with the best-case performance. It is shown that the proposed approach has lower complexity compared to the MP algorithm. Finally, experimental results are provided with real LTE signals, showing a reduction of 93%, 57%, and 31% in the standard deviation of TOA, azimuth, and elevation angles' estimation errors, respectively, using the proposed receiver compared to the MP algorithm.

TOA and DOA Estimation for IR‐UWB Signals: An Efficient Algorithm by Improved Root‐MUSIC

The automatically paired time of arrival (TOA) and direction of arrival (DOA) can be jointly estimated via a high‐precision multidimensional spectral peak search‐ (SPS‐) based multiple signal classification (MUSIC) algorithm in the impulse radio ultrawideband (IR‐UWB) positioning system, while heavy computational burden is required. To tackle this issue, we propose an improved root‐MUSIC algorithm for joint TOA and DOA estimation. After modelling the frequency domain form of the received signal, the algorithm first uses the signal subspace to establish the relationship between the two antennas. Then, the MUSIC spatial spectrum function is reconstructed with this relation, which enables it to offer a spectrum function in regard to the one‐dimensional (1D) parameter of time delay. For further reducing the complexity, the TOA estimates of one antenna are obtained via 1D polynomial root finding instead of SPS, and the TOA estimates of the other antenna can be calculated by the established relationship. Finally, the DOA estimation can be achieved with the estimated TOAs. Due to the relationship between two antennas with signal subspace, the parameters estimated by the proposed algorithm are autopaired. Numerical simulations substantiate the superiority of the proposed algorithm.

Novel 3-D Irregular-Shaped Model for Massive MIMO V2V Channels in Street Scattering Environments

In this letter, we develop a three-dimensional (3-D) irregular-shaped semi-ellipsoid channel model for massive multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communication in street scattering environments. The geometric model is irregular-shaped due to the scattering environments cut by vertical structures along the roadside. With employing a uniform planar array (UPA), we first characterize the geometrical relationships between transmitter and receiver constrained by different boundaries of scattering regions in detail. Then we derive the closed-form expressions for the probability density functions (PDFs) of the angle of departure (AoD) and joint time of arrival (ToA)/AoD in azimuth and elevation planes. Moreover, we discuss the impacts of the street width and large-scale antenna array on channel statistical properties. Numerical results show that our proposed model can capture characteristics of massive MIMO V2V channels while in close agreement with the prior reported results, thereby demonstrating the efficiency of the proposed model that can provide guidance for system design and performance evaluation of massive MIMO V2V communication in street scattering environments.

Joint Time-of-Arrival Estimation for Coherent UWB Ranging in Multipath Environment With Multi-User Interference

Time-of-Arrival (ToA) estimation becomes extremely challenging for ultra-wideband ranging systems in dense multipath environment with multiuser interference. In this paper, we propose a high accuracy joint ToA estimation (JToAE) algorithm, which can provide dominantly better performance than existing techniques. Based on the requirement of time synchronization among base stations, our proposed JToAE algorithm jointly exploits spatial information of each base station and the ToA of each multipath component of each received signal in ToA estimation. Our scheme is insensitive to the selection of the threshold, and does not require any additional information such as channel, noise power, preamble, or synchronization between transmitters and receivers. We also propose how to effectively distinguish the ToA of the first path of the desired user from the interfering signals in multi-user case without generating error propagation. The proposed JToAE is verified by extensive Monto Carlo simulation that is based on IEEE 802.15.4a channel models, and the simulation results indicate that even in low signal-to-noise ratio and multi-user case, our proposed technique can achieve significantly higher ranging accuracy compared to those in the literature in recent decades.

Fast Joint Estimation of Time of Arrival and Angle of Arrival in Complex Multipath Environment Using OFDM

Joint time of arrival (TOA) and angle of arrival (AOA) estimation based on a uniform circle array (UCA) involves problems, including high computational complexity in the multi-dimensional spectral search method and lack of applicability in coherent multipath environments. In this paper, we introduce a fast estimation algorithm based on the orthogonal frequency-division multiplexing system that uses space–frequency characteristics to reconstruct the virtual array and extend the array aperture. First, we combine the array structure with the signal frequency features to construct the extended virtual array. We then calculate the channel frequency response covariance matrix via frequency-domain smoothing preprocessing and determine a closed-form solution of AOA using UCA estimating signal parameters via rotational invariance techniques. Finally, using the estimated angle values, we perform a 1-D spectral search to determine the TOA values. The simulation results indicate that the proposed method provides an accurate estimation under the low signal-to-noise ratio conditions in coherent, independent, or mixed multipath environments, and provides a better performance than the multi-dimensional spectral peak search method, in terms of both computational complexity and estimation accuracy.

Joint estimation of DOA and TOA for MB‐OFDM UWB signals based on frequency‐domain processing

This study proposes a new joint direction of arrival (DOA) and time of arrival (TOA) estimation (JDTE) scheme for multi-band orthogonal frequency-division multiplexing (MB-OFDM) ultra-wideband systems with a two-antenna receiver based on frequency-domain processing. Prior joint TOA and DOA estimation (JTDE) schemes first measure the TOAs from the received waveforms at all antennas and then obtain the DOA from the TOA measurements. The proposed JDTE method estimates parameters directly from the waveforms received at all antennas, where the channel frequency response associated with the two antenna elements can be considered as a 2D (frequency and space) ‘virtual array’. The DOA is estimated by exploiting the spatial dimension of the virtual array first, and then the TOA is estimated by exploiting the frequency dimension of the virtual array. The use of the virtual array enables the number of resolvable paths to exceed the number of antennas. More importantly, the Cramer–Rao bound (CRB) of DOA estimation that is derived from the received waveforms is significantly lower than that obtained from the TOA metric, and the CRB of the estimated TOA is also slightly lower than that obtained using the JTDE scheme. Numerical simulations verify the superiority of the proposed method.

Joint Frequency and Time Estimation Algorithms

In this paper, we present six subspace decomposition based methods for joint time of arrival (TOA) and frequency of arrival (FOA) estimation of multiple incident sources. These are LU-TLS, QR-TLS, direct TSQR-TLS, direct TSLU-TLS, parallel TSQR-TLS, and parallel TSLU-TLS. The direct and parallel TSQR/TSLU-TLS are recently developed methods in subspace decomposition and are employed in this work for time and frequency estimation. The proposed methods employ a pair of spatially separated sensors to receive multiple incident source signals. A data matrix is constructed in the form of a Hankel matrix from multiple snapshots of the received signal. The information of both TOA and FOA of multiple incident sources is extracted from the data matrix by applying LU/QR techniques (in the first set of the methods) and a tall skinny TSLU/TSQR factorization in the second set. The estimates of the TOA and FOA are obtained from the signal subspace by applying the total least squares (TLS) method. Simulation results are presented to assess the performance of the proposed methods. The effect of parametric variations on the performance has also been analyzed for all the proposed methods. Further, the computational times and complexities of the proposed methods are also computed and compared with each other.

Joint estimation of TOA and DOA in IR-UWB system using a successive propagator method

Impulse radio ultra-wideband (IR-UWB) ranging and positioning require accurate estimation of time-of-arrival (TOA) and direction-of-arrival (DOA). With receiver of two antennas, both of the TOA and DOA parameters can be estimated via two-dimensional (2D) propagator method (PM), in which the 2D spectral peak searching, however, renders much higher computational complexity. This paper proposes a successive PM algorithm for joint TOA and DOA estimation in IR-UWB system to avoid 2D spectral peak searching. The proposed algorithm firstly gets the initial TOA estimates in the two antennas from the propagation matrix, then utilises successively one-dimensional (1D) local searches to achieve the estimation of TOAs in the two antennas, and finally obtains the DOA estimates via the difference in the TOAs between the two antennas. The proposed algorithm, which only requires 1D local searches, can avoid the high computational cost in 2D-PM algorithm. Furthermore, the proposed algorithm can obtain automatically paired parameters and has better joint TOA and DOA estimation performance than conventional PM algorithm, estimation of signal parameters via rotational invariance techniques algorithm and matrix pencil algorithm. Meanwhile, it has very close parameter estimation to that of 2D-PM algorithm. We have also derived the mean square error of TOA and DOA estimation of the proposed algorithm and the Cramer-Rao bound of TOA and DOA estimation in this paper. The simulation results verify the usefulness of the proposed algorithm.

Joint for time of arrival and direction of arrival estimation algorithm based on the subspace of extended hadamard product

In the joint estimation for time of arrival (TOA) and direction of arrival (DOA) in the narrow-band orthogonal frequency division multiplexing (OFDM) system with antenna arrays, the estimation accuracy is not high in the situation of few numbers of arrays. Especially, DOA cannot be estimated if the number of multiple paths is more than that of the arrays. For these problems, a joint estimation algorithm for TOA and DOA based on the subspace of the extended hadamard product is proposed. First of all, the algorithm constructs an extended channel response in frequency domain via channel estimation for each array in the frequency domain. Then, auto-correlation matrix of extended channel response in the frequency domain is estimated by sampling many times. This estimation method of channel response in the frequency domain can use the fast Fourier transform algorithm. And the hadamard product in the extended noise subspace is obtained by eigenvalue decomposition. Finally, the pseudo-spectral function is constructed and used to search for spectrum peaks, so as to realize the joint estimation of TOA and DOA. The proposed algorithm requires no parameter paring but needs a two-dimensional searching. Monte Carlo algorithm can be used to reduce computational complexity. Simulation results show that the root mean square error of the joint TOA and DOA estimation which can be matched automatically is closer to the Cramer-Rao bound than that using present algorithms. And the proposed algorithm can be still applied when the number of multiple paths is more than number of arrays.

Joint DFT-ESPRIT Estimation for TOA and DOA in Vehicle FMCW Radars

This letter proposes a joint discrete Fourier transform (DFT)—estimation of signal parameters via rotational invariance techniques (ESPRIT) estimator for time-of-arrival (TOA) and direction-of-arrival (DOA) in vehicle frequency-modulated continuous-wave (FMCW) radars. Since the vehicle FMCW radar should recognize vehicles in the side/rear area when the driver initiates a lane change, the estimation of the joint TOA/DOA between the radar and targets is an important issue for solving complicated location tasks. However, conventional joint estimation methods such as 2D-ESPRIT and 2D-multiple signal classification (MUSIC) cannot be adopted for real-time implementation due to their high computational loads. To satisfy the required accuracy specifications and reduce complexity compared with the conventional estimator, we propose a low-complexity joint TOA and DOA estimator that uses the combined DFT-ESPRIT algorithm for FMCW radars. The performance of the proposed estimation in multitarget environments was derived and compared with the Monte Carlo simulation results. The root-mean-square error (RMSE) of the proposed method was compared with that of 2D-ESPRIT with various parameters. To verify the performance of the proposed combination method, we implemented the FMCW radar and verified its performance in an anechoic chamber environment.

A ML-Based Framework for Joint TOA/AOA Estimation of UWB Pulses in Dense Multipath Environments

We present a joint estimator of the time of arrival (TOA) and angle of arrival (AOA) for impulse radio ultrawideband (UWB) systems in which an antenna array is employed at the receiver. The proposed method consists of two steps: 1) preliminary estimation of the TOA and the average power delay profile (APDP) using energy-based threshold crossing and log-domain least-squares fitting, respectively; and 2) joint TOA refinement and AOA estimation by local 2-D maximization of a log-likelihood function (LLF) that employs the preliminary estimates from the first step. The derivation of the LLF relies on an original formulation in which the superposition of images from secondary paths is modeled as a Gaussian random process, whose second-order statistical properties are characterized by a wideband space-time correlation function. In addition to the APDP, this function incorporates a special gating mechanism to represent the onset of the secondary paths, thereby leading to a novel form of the LLF. Closed-form expressions for the Cramer-Rao bound on the variance of the TOA and AOA estimators are also derived, which formally take into account pulse overlap through this gating mechanism. In simulation experiments based on multipath UWB channel models featuring both diffuse and directional image fields, our approach exhibits superior performance to that of a competing scheme from the recent literature.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

Joint TOA and DOA Localization in Indoor Environment Using Virtual Stations

This letter presents a geometrical localization approach that is able to locate a mobile station in non-line-of-sight (NLOS) and multipath conditions using time-of-arrival (TOA) and direction-of-arrival (DOA) estimates. The novelty of our work resides in converting the NLOS problem into a line-of-sight problem with virtual stations, even if the signal undergoes multiple-bound scattering, which has not been resolved in previous works. We also develop a two-step weighted least squares (TSWLS) positioning estimator using the hybrid TOA and DOA values. Simulation results demonstrate the effectiveness of the proposed method.

Joint Estimation of TOA and DOA in IR-UWB System Using a Successive MUSIC Algorithm

Time-of-arrival (TOA) and direction-of-arrival (DOA) are key parameters in the impulse radio ultra wideband (IR-UWB) positioning system with a two-antennas receiver. A two-dimensional (2D) multiple signal classification (MUSIC) algorithm, which requires the 2D spectral peak search, can be used to estimate the parameters, but it has much higher computational complexity. This paper proposes a successive MUSIC algorithm for joint TOA and DOA estimation in IR-UWB system to avoid 2D spectral peak search. The proposed algorithm obtains the initial estimate of TOA corresponding to the first antenna via Root-MUSIC, and simplifies the 2D global search into successive one-dimensional searches to achieve the estimation of TOAs in the two antennas. It then estimates the DOA parameters via the difference of the TOAs between the two antennas. The proposed algorithm can get the parameters paired automatically, and has a much lower complexity than 2D-MUSIC algorithm. In addition, we have derived the mean square error of TOA and DOA estimation of the proposed algorithm and the Cramer---Rao bound of TOA and DOA estimation in the paper. The simulation results show that the parameter estimation performance of the proposed algorithm is better than that of Root-MUSIC, and is almost the same as that of 2D-MUSIC algorithm. Moreover, it has much better performance than matrix pencil algorithm, propagator method and estimation of signal parameters via rotational invariance techniques algorithm.

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.

Statistical NLOS Identification Based on AOA, TOA, and Signal Strength

Nonline-of-sight (NLOS) propagation is one of the challenges in radio positioning. Significant attention has been drawn to the mitigation of the NLOS effect in recent years. This paper focuses on the identification of NLOS conditions by employing the statistical decision theory. A Neyman-Pearson (NP) test method is first derived for scenarios where either 1-D or 2-D angular measurements are provided. A time-of-arrival (TOA) based method is then developed under idealized conditions to provide a performance reference. In the presence of both TOA and received signal strength (RSS) measurements, a joint identification method is derived to efficiently exploit the TOA and RSS measurements. Analytical expressions of the probability of detection (POD) and the probability of false alarm (PFA) are derived for all the scenarios considered. Two theorems and one corollary regarding the line-of-sight (LOS) conditions based on the angle of arrival (AOA) are also presented, and the proofs are provided. Simulation results demonstrate that the proposed methods perform well, and the joint TOA- and RSS-based method considerably outperforms the TOA-based methods. The proposed methods are robust to the model errors, as demonstrated through simulations. It is also shown that the analytical results agree well with the simulated ones.

Ultra-Wideband Indoor Double-Directional Channel Estimation Using Transformation between Frequency and Time Domain Signals

This paper proposes an ultra-wideband double-directional spatio-temporal channel sounding technique using transformation between frequency- and time-domain (FD and TD) signals. Virtual antenna arrays, composed of omnidirectional antennas and scanners, are used for transmission and reception in the FD. After Fourier transforming the received FD signals to TD ones, time of arrival (TOA) is estimated using a peak search over the TD signals, and then angle of arrivals (AOA) and angle of departure (AOD) are estimated using a weighted angle histogram with a multiple signal classification (MUSIC) algorithm applied to the FD signals, inverse-Fourier transformed from the TD signals divided into subregions. Indoor channel sounding results validated that an appropriate weighting reduced a spurious level in the angle histogram by a factor of 0.1 to 0.2 in comparison with that of non-weighting. The proposed technique successfully resolved dominant multipath components, including a direct path, a single reflection, and a single diffraction, in line-of-sight (LOS) and non-LOS environments. Joint TOA and AOA/AOD spectra were also derived from the sounding signals. The spectra illustrated the dominant multipath components (agreed with the prediction by ray tracing) as clusters.