Time Of Arrival Estimation Algorithm Research Articles

Time-of-Arrival Estimation for Integrated Satellite Navigation and Communication Signals

Global navigation satellite systems (GNSSs) are used in numerous fields, but their vulnerability is a global problem that has yet to be solved. A promising way to effectively address this problem is by integrating navigation into emerging dense nongeosynchronous orbit (NGSO) megaconstellations. To maximize the downlink efficiency for users, an integrated satellite navigation and communication (ISNAC) framework is proposed in this work, in which a necessary number of packetized bursty downlink satellite communication signals are used directly for navigation purposes. Then, the user terminal estimates the time of arrival (TOA) of these ISNAC signals regardless of their coding and modulation type. To this end, a TOA estimation algorithm is proposed. Specifically, the user terminal first constructs a template signal with demodulated data bits to replicate the transmitted ISNAC signal and then calculates the cross-correlation function (CCF) of the template and the received signal for TOA estimation, based on which the TOA is finally estimated. The performance bound of the proposed TOA estimation algorithm is analyzed. Simulations are conducted to corroborate the mathematical analysis and The results show that the proposed algorithm outperforms other TOA estimators for comparsion by approaching the Cramer-Rao lower bound (CRLB) with a much lower computational complexity.

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.

Time of arrival estimation for underwater acoustic signal using multi-feature fusion

Underwater target detection (UTD) is widely applied in ocean exploration. A key issue for the time-of-arrival (ToA)-based UTD algorithm is to localize the first direct path in an underwater multipath channel. However, the conventional Matched Filter (MF) suffers from a deterioration of the estimation accuracy when the direct arrival of the received signal is non-strongest. Therefore, this paper proposes a multi-feature fusion ToA estimation algorithm. First, a multi-decision strategy including the coarse ToA range estimation and the fine ToA estimation is proposed to realize a balance between computational complexity and estimation accuracy. Second, the coarse ToA range estimation is realized by multi-level spectrum analysis. Then, the coarse ToA range is used to localize the fine ToA utilizing the multi-feature fusion ToA estimation. Finally, the simulation and experimental results are provided to validate the proposed ToA estimation algorithm. It clearly shows that without training data, the proposed algorithm can not only deal with the multipath acoustic channel problem but also improve the accuracy of the ToA estimation compared to other algorithms.

Utilization of non-coherent accumulation for LTE TOA estimation in weak LOS signal environments

Ground localization systems based on cellular signals are vulnerable to the hazards of signal power attenuation and multipath propagation in urban environments. Non-coherent accumulation is an effective solution to this problem, but its application to cellular localization systems has not been properly discussed. In this paper, we propose two cellular time-of-arrival (TOA) estimation methods based on non-coherent accumulation: the “TOA estimation algorithm based on non-coherent accumulation of the channel impulse response” (nch-CIR) in the time domain and the “Super Resolution TOA Estimation Algorithm based on non-coherent accumulation of the covariance matrix” (nch-SRA) in the frequency domain. Among these two methods, the nch-CIR algorithm has a lower computational cost and better anti-noise performance, and the nch-SRA algorithm has better performance in terms of multipath delay estimation. Through theoretical analysis and extensive simulations, we also discuss the influence of mobility on these two methods. In addition, experiments are conducted to evaluate the performance of the proposed method using real collected cellular signals. The results show that both nch-CIR and nch-SRA can achieve a better performance compared with the conventional methods.

A novel singular value decomposition-based ultra wide band time-of-arrival estimation for multiple targets

It is widely <span>admitted that the estimation of ultra wide band (UWB) time-of-arrival (TOA) for multiple targets in indoor multipath channels is a very challenging task. The existing algorithms deal with a limited number of targets and require a complex exchange of several messages. In this paper, a novel TOA estimation algorithm for multiple targets is developed. The proposed algorithm estimates the first path (FP) TOA of a number of targets without exchanging messages or using collision avoidance techniques. As a first step, the singular value decomposition (SVD) is employed to extract the first path (FP) of each target and then a matched filter, followed by an iterative threshold crossing algorithm, is used to determine the number of targets and the corresponding FP TOAs. The simulation results with four targets, using the CM1 IEEE 802.15.4a channel model, showed that the proposed novel algorithm can effectively detect the FP of each target and estimate its corresponding TOA.</span>

High resolution time of arrival estimation algorithm for B5G indoor positioning

In beyond 5G (B5G) indoor positioning time of arrival (TOA) positioning method is an important one. Base stations measure reference signals sent by terminals to calculate the TOA. The accuracy of position calculation is highly dependent on the TOA estimation resolution. This paper proposes a high-resolution TOA estimation algorithm based on Sounding Reference Signal (SRS) of 5G communication system. The algorithm achieves high resolution estimation by two steps. The Least Mean Square (LMS) adaptive filtering method is used as the first step to obtain the integer part of TOA, which is a coarse estimation of TOA. In the second step, we use weighted Generalized Cross-Correlation (GCC) algorithm to obtain the fractional part of TOA in frequency domain to get a more precise TOA estimation. Moreover, the stability of the estimated results is improved by the threshold value setting. The proposed algorithm is simulated in both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. The simulation results show that the TOA error achieves 0.56 m in AWGN and 0.96 m in Rayleigh fading channels for 80% of test samples respectively.

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.

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.

Time of Arrival and Angle of Arrival Estimation Algorithm in Dense Multipath

Accurate position determination of a wireless device by time-of-arrival (TOA) and angle-of-arrival (AOA) estimation of the line-of-sight (LOS) path with an array of collocated antennas, is important in various applications. In an indoor environment, there can be many multipath reflections, from different angles of arrivals; and, when the signal bandwidth is relatively narrow, the received signal from the LOS path is often obscured by the overlapping received multipath signals. In this case, accurate estimation of the LOS TOA and AOA is challenging. In this paper, we present a novel estimator for the LOS TOA and AOA in multipath conditions, by obtaining an approximate distribution for the received signals of all the antennas. We approximate as Gaussian the distribution of the received signals given the LOS TOA and AOA, as well as additional clusters’ mean AOAs; and subsequently derive a maximum likelihood estimator for the LOS TOA and AOA. We also further derive an estimation algorithm with reduced complexity. The performance of the LOS TOA and AOA estimation algorithm in challenging multipath conditions is evaluated. The results show, that the proposed estimator achieves a performance advantage compared to reference methods for sufficiently high SNR.

Super-Resolution Time of Arrival Estimation for a Symbiotic FM Radio Data System

A symbiotic FM radio data system (SRDS) refers to a kind of digital broadcasting whose signal co-exists with the FM in channel. The SRDS signal has a symmetrical split spectrum in the band of the host FM signal spectrum. Like the FM signal, this kind of broadcasting signal also has a wide range of ground coverage. When used as an alternative to the positioning, navigation and timing (PNT), it will be meaningful for intelligent artifacts in safety-of-life applications. However, SRDS signals not only have much narrower bandwidth than GNSS signals, but also multiple peaks of auto-correlation function, which poses a serious challenge to the time of arrival (ToA) estimation. In this paper, we propose a super-resolution ToA estimation algorithm for the SRDS signals. Specifically, the properties of the auto-correlation function of SRDS signal are deduced concretely, and a two-step ToA estimation algorithm for the SRDS signal is proposed accordingly. Simulations are conducted with different configurations of quantization bits, SNR, oversampling rates and multi-path. The results show that the meter-level ranging performance can be obtained in the single-path Gaussian channel, and the ranging performance degrades from tens of meters to a hundred meters in multi-path environments.

A time-of-arrival estimation algorithm for OFDM signals in indoor multipath environments

Time-of-arrival (TOA) estimation of OFDM signals in multipath channels is challenging, especially when the signal bandwidth is limited, such as is the case of WIFI. In this paper, a novel low complexity TOA estimation algorithm is developed for OFDM signals that is robust to various multipath environments. We approximate the received signal as Gaussian with an autocorrelation that can be predetermined by the environment characteristics, and then derive the Maximum Likelihood estimator with an efficient implementation algorithm. The estimator performance was tested with a measurement system that was developed based on off-the-shelf WIFI 802.11g routers. The measurement system enabled the evaluation of the estimator performance in real-life indoor environments, and with real-life OFDM transmitter and receiver imperfections. The results show that the novel TOA estimator outperforms other known reference methods over various indoor 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.

High-Resolution Time of Arrival Estimation With Small Samples Considering Time-Varying Channel Fading Coefficient Correlation in OFDM

This paper proposes a new method using orthogonal frequency division multiplexing (OFDM) signals for time-of-arrival (TOA) estimation in complex environments, such as electromagnetic interference and short burst received signals. Under that circumstance, sometimes only a short period of signals that were seriously interfered [i.e., low signal-to-noise ratio (SNR) and small samples] can be received for estimation. However, the traditional algorithm would be faced with a decrease in estimation accuracy under that conditions. Due to the fact that the sparse reconstruction method can recover the original signal from a small number of observations with high probability, this paper proposes an OFDM TOA estimation algorithm based on it. The algorithm not only considers the correlation of the channel complex fading coefficients in the samples at adjacent moments but also considers the off-grid effect. Under the Bayesian learning framework, this correlation and off-grid parameter are introduced into the estimation process, which effectively improves the estimation accuracy under small samples and low SNR conditions. The proposed algorithm first constructs a sparse representation model based on the channel frequency response estimated by the OFDM signal physical layer protocol data unit and then introduce the correlation characterization matrix and the off-grid parameter and make probability assumptions for the noise vector, the off-grid parameter, and the sparse coefficient vector in the model. Finally, according to Bayesian inference, the expectation-maximization algorithm is used to solve the hyperparameters to achieve high-resolution estimation of TOA. The simulation results show that the proposed algorithm has a better estimation performance than the traditional algorithms and existing sparse reconstruction algorithms. In addition, its performance curve is closer to the Cramer-Rao bound at low SNR. At the same time, based on the universal software radio peripheral, the effectiveness of the proposed algorithm is verified by the actual OFDM signal.

A Novel Hybrid RSS and TOA Positioning Algorithm for Multi-Objective Cooperative Wireless Sensor Networks

Due to the significance of positioning in complicated electromagnetic environment of its variety of applications, wireless localization techniques have attracted significant research interests with the trends moving toward boosting the capabilities of multi-objective cooperative networks. This paper addresses the problem of locating multiple targets in 3-D cooperative wireless sensor network. A novel hybrid received signal strength (RSS) and time-of-arrival (TOA) positioning scheme is proposed. Employing RSS and TOA measurements, four valuable expressions are drawn. The TOA and RSS technologies are combined with path loss difference variable being introduced. Based on the weighted least squares criterion, the rough solutions of multiple targets positions are derived. Finally, the locations of obtained targets are optimized by cooperative wireless communication between the target and another target. The location accuracy of the proposed estimation algorithm is analyzed and compared with the conventional RSS and TOA estimation algorithms through simulation experiments. The simulation result demonstrates that the proposed hybrid RSS and TOA localization algorithm for multi-objective cooperative wireless networks outperforms traditional approaches.

A novel time of arrival estimation algorithm using an energy detector receiver in MMW systems

This paper presents a new time of arrival (TOA) estimation technique using an improved energy detection (ED) receiver based on the empirical mode decomposition (EMD) in an impulse radio (IR) 60 GHz millimeter wave (MMW) system. A threshold is employed via analyzing the characteristics of the received energy values with an extreme learning machine (ELM). The effect of the channel and integration period on the TOA estimation is evaluated. Several well-known ED-based TOA algorithms are used to compare with the proposed technique. It is shown that this ELM-based technique has lower TOA estimation error compared to other approaches and provides robust performance with the IEEE 802.15.3c channel models.

TOA Analysis Based on Energy for 60 GHz Signals

In the field of sensor networks, impulse radio 60 GHz signals are even much more practical for accurate localization which is low cost, low complexity with high time and multipath resolution. Typically, accurate Time of Arrival (TOA) estimation is very important for localization. In order to improve precision of TOA estimation, a new TOA estimation algorithm based on energy detector (ED) is proposed which is based on a joint metric of skewness, standard deviation and kurtosis after ED. The best threshold based on signal-to-noise ratio (SNR) is investigated and effects of integration period and channel model are examined. Simulation results are presented which show for IEEE802.15.3c channel models CM1.1 and CM2.1, the proposed algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

A Novel Time of Arrival Estimation Algorithm based on Skewness and Kurtosis

A Novel Time of Arrival Estimation Algorithm based on Skewness and Kurtosis

IEEE 802.15.4 ZigBee-Based Time-of-Arrival Estimation for Wireless Sensor Networks.

Precise time-of-arrival (TOA) estimation is one of the most important techniques in RF-based positioning systems that use wireless sensor networks (WSNs). Because the accuracy of TOA estimation is proportional to the RF signal bandwidth, using broad bandwidth is the most fundamental approach for achieving higher accuracy. Hence, ultra-wide-band (UWB) systems with a bandwidth of 500 MHz are commonly used. However, wireless systems with broad bandwidth suffer from the disadvantages of high complexity and high power consumption. Therefore, it is difficult to employ such systems in various WSN applications. In this paper, we present a precise time-of-arrival (TOA) estimation algorithm using an IEEE 802.15.4 ZigBee system with a narrow bandwidth of 2 MHz. In order to overcome the lack of bandwidth, the proposed algorithm estimates the fractional TOA within the sampling interval. Simulation results show that the proposed TOA estimation algorithm provides an accuracy of 0.5 m at a signal-to-noise ratio (SNR) of 8 dB and achieves an SNR gain of 5 dB as compared with the existing algorithm. In addition, experimental results indicate that the proposed algorithm provides accurate TOA estimation in a real indoor environment.

A Novel Time of Arrival Estimation Algorithm based on Energy Detector

Accurate localization has gained significant interest in the field of sensor networks, impulse radio60GHz signals which is low cost, low complexity are even much more practical for ranging, localization and tracking systems because of the high time and multipath resolution and so on. Typically, accurate Time of Arrival (TOA) estimation of the 60GHz signals is very important. In order to improve the precision of the TOA estimation, a new TOA estimation algorithm based on Energy Detector is proposed which is based on a joint metric of the Skewness, Kurtosis, Maximum Slope and Standard Deviation after Energy Detection. 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 theIEEE802.15.3c channel models CM1.1 and CM2.1, the proposed algorithm provides better precision and robustness in both high and low SNR environments than other ED-based algorithms.

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.