Time Of Arrival Estimation Method Research Articles

Double sliding window variance detection-based time-of-arrival estimation in ultra-wideband ranging systems

<span lang="EN-US">Ultra-wideband (UWB) ranging via time-of-arrival (TOA) estimation method has gained a lot of research interests because it can take full advantage of UWB capabilities. Energy detection (ED) based TOA estimation technique is widely used in the area due to its low cost, low complexity and ease of implementation. However, many factors affect the ranging performance of the ED-based methods, especially, non-line-of-sight (NLOS) condition and the integration interval. In this context, a new TOA estimation method is developed in this paper. Firstly, the received signal is denoised using a five-level wavelet decomposition, next, a double sliding window algorithm is applied to detect the change in the variance information of the received signal, the first path (FP) TOA is then calculated according to the first variance sharp increase. The simulation results using the CM1 and CM2 IEEE 802.15.4a channel models, prove that our proposed approach works effectively compared with the conventional ED-based methods.</span>

A Mobile Phone Uplink CPDP-DTDOA Positioning Method Using UAVs for Search and Rescue

This article proposes a mobile phone passive positioning system using unmanned aerial vehicles (UAVs) to detect the uplink signals based on orthogonal frequency-division multiplexing (OFDM) for search and rescue. Reducing the influence of time synchronization error on time of arrival (TOA) estimation, the system sets up a reference node to broadcast reference signals at the subframe of uplink signals. The differential time difference of arrival (DTDOA) estimation method is adopted to achieve high-precision positioning. At the same time, an efficient TOA estimation method for DTDOA called cross power delay profile (CPDP) estimation is proposed, which can reduce the computational effort of TOA estimation by up to 50% compared to conventional DTDOA. The performance and Crámer–Rao lower bound of CPDP-DTDOA estimation are compared with conventional DTDOA estimation and TDOA estimation. The effects of signal-to-noise ratio (SNR) and sampling rate on the performance of CPDP-DTDOA are evaluated. The experiment and simulation demonstrate that CPDP-DTDOA can achieve time synchronization and obtain unbiased TOA estimation even at low sampling rates when the reference signal is under line-of-sight (LOS) and high SNR, satisfying the low-power design for UAV platforms.

Trajectory clustering for SVR-based Time of Arrival estimation

Accurate vessel Time of Arrival (ToA) estimation is important for port operation and resource management. In this paper, we propose a data-driven approach for estimating the ToA of ships based on Automatic Identification System (AIS) data. The proposed approach exploits a novel trajectory clustering approach to extract representative routes, from which training trajectories are grouped into clusters and ToA estimation models based on Support Vector Regressor (SVR) are trained for each cluster. The proposed ToA estimation approach adopts a short period of the latest AIS data as input and performs SVR model selection and ToA estimation in real-time. A historical AIS dataset provided by the Danish Maritime Authority is used to evaluate the proposed approach. Numerical results for tanker ships travelling to the port of Skagen demonstrate that the proposed approach can achieve ToA estimations that are 40% to 70% more accurate than state-of-the-art ToA estimation methods.

Carrier Phase Ranging for Indoor Positioning With 5G NR Signals

Indoor positioning is one of the core technologies of Internet of Things (IoT) and artificial intelligence (AI), and is expected to play a significant role in the upcoming era of AI. However, affected by the complexity of indoor environments, it is still highly challenging to achieve continuous and reliable indoor positioning. Currently, 5G cellular networks are being deployed worldwide, the new technologies of which have brought the approaches for improving the performance of wireless indoor positioning. In this paper, we investigate the indoor positioning under the 5G new radio (NR), which has been standardized and being commercially operated in massive markets. Specifically, a solution is proposed and a software defined receiver (SDR) is developed for indoor positioning. With our SDR indoor positioning system, the 5G NR signals are firstly sampled by universal software radio peripheral (USRP), and then, coarse synchronization is achieved via detecting the start of the synchronization signal block (SSB). Then, with the assistance of the pilots transmitted on the physical broadcasting channel (PBCH), multipath acquisition and delay tracking are sequentially carried out to estimate the time of arrival (ToA) of received signals. Furthermore, to improve the ToA ranging accuracy, the carrier phase of the first arrived path is estimated. Finally, to quantify the accuracy of our ToA estimation method, indoor field tests are carried out in an office environment, where a 5G NR base station (known as gNB) is installed for commercial use. Our test results show that, in the static test scenarios, the ToA accuracy measured by the 1-{\sigma} error interval is about 0.5 m, while in the pedestrian mobile environment, the probability of range accuracy within 0.8 m is 95%.

Improved TOA Estimation Method for Acoustic Ranging in a Reverberant Environment

Indoor localization based on the time-of-arrival (TOA) measurements of acoustic signals has advantages of low cost, high accuracy and no electromagnetic interference compared with other location technologies such as Bluetooth and Wi-Fi. However, conventional TOA estimation approaches based on peak extraction or fixed thresholds have difficultly maintaining high ranging accuracy and robustness in reverberant indoor enclosed environments. To address this situation, this paper presents an improved TOA estimation method for acoustic ranging in a reverberant environment that is composed of two processes. One is an acoustic reverberant cancellation technique based on the signal power spectra, and the other is a first-extremum-based match filter. To verify the performance of the improved TOA estimation method, indoor experiments were conducted in an enclosed noisy and reverberant underground parking garage. The experimental results demonstrate that the proposed algorithm is superior to a traditional quadratic cross-correlation and match filter in terms of estimation accuracy and robustness.

Real-time and accurate pulsar time-of-arrival estimation using GA-optimized EMD-CS

For the estimation methods of the pulsar TOA (time-of-arrival) based on CS (compressed sensing), it is very important to construct the measurement matrix, which affects accuracy and computation load directly. Subjected to computational load, the matrix size is also an important performance indicator. To reduce the matrix size, we propose a pulsar TOA estimation method using GA (Genetic Algorithm)-optimized EMD (empirical mode decomposition)-CS. Firstly, the standard pulsar profile is decomposed by the EMD to get IMFs (Intrinsic Mode Function). After the decomposition and the phase shift, these IMFs are performed to obtain the set of IMFs with multiple phases. And then, we take the error of the pulsar TOA estimation as the optimization goal, and use the GA to select IMFs from this set. The IMFs selected by the GA forms the optimized measurement matrix. Finally, the CS with the GA-optimized measurement matrix is used to obtain the pulsar TOA estimation. Theoretical analysis and simulation results show that the GA-optimized EMD measurement matrix has unlimited dimensions and small size. The pulsar TOA estimation using GA-optimized EMD-CS has a high accuracy and small computational load.

Time‐of‐arrival estimation for smartphones based on built‐in microphone sensor

The time-of-arrival (TOA) estimation method is an important ranging and positioning technology for indoor localisation and navigation. In this Letter, a novel TOA estimation method for smartphones based on a built-in microphone sensor is proposed, which utilises the propagation delay between optical and acoustic signals to achieve distance estimation. Unlike other TOA estimation technologies based on multi-sensors, a single MEMS microphone of a smartphone is used as the receiving sensor for both optical and acoustic signals, which is beneficial for eliminating the synchronisation error and improving ranging precision. Experimental results demonstrate that the proposed TOA estimation method is effective and accurate with an average ranging error of <0.29 m under a signal-to-noise ratio (SNR) of 1.18 dB for the smartphones tested in this work.

Time of arrival estimation based on clustering for positioning in OFDM system

In positioning research based on the orthogonal frequency division multiplex (OFDM) system, the observed time difference of arrival positioning method is a widely studied direction. The terminal measures the reference signal sent by the base station to calculate the time of arrival (TOA). Using TOA information, the location of the terminal can be identified. So the accuracy of the positioning is highly dependent on the results of the TOA measurements. Terminals often have difficulty measuring accurate TOA due to multipath channels and occlusion of obstacles. This study proposes two clustering-based TOA estimation methods. The cluster-based Max-peak estimator is used to solve the problem that the energy of the first-path is not the strongest in the case of multipath. Moreover, a cluster-based adaptive threshold estimator is used to estimate TOA when the power of the direct path is low. The joint estimator of the two methods is designed to improve estimation accuracy. The proposed method is tested in the OFDM localisation environment, and the results demonstrate that the proposed method has better performance than the conventional way.

Time‐of‐arrival estimation algorithm for positioning in NB‐IoT physical layer

In this study, the authors propose a new time-of-arrival (ToA) algorithm for positioning in the physical layer of narrowband Internet-of-Things (NB-IoT) technology. This algorithm estimates the ToA of transmitted narrowband positioning reference signals (NPRSs) by detecting the first valid tap of estimated power delay profile (PDP). They estimate the PDP as well as the noise power in the time domain via inverse Fast Fourier transformation of received frequency-domain NPRSs. The accuracy of the estimated noise power is crucial in the ToA estimation since the SNR is extremely low in typical NB-IoT scenarios. The simulations show that the proposed ToA estimation method outperforms the conventional method and performs well in various scenarios.

Quantized Compressed Sensing Based TOA Estimation of IR-UWB System in the Presence of Overload Noise

In this paper, the problem of the overload noise during quantization step applied to the compressed sensing (CS) measurements is tackled for Impulse Radio (IR) Ultra-Wide Band (UWB) ranging signal under indoor residential environment. The dynamic-threshold (DT) fitting method used for the high precision of the time of arrival (TOA) estimation is leveraged in the case of the bounded non sparse noises like thermal noise and quantization noise. However, the inevitable presence of the overload noise in the practical application decreases significantly the ranging accuracy with the dynamic-threshold method whose parameters are established without considering the saturation effect of the measurements. The fact that the overload noise is sparseness motivates us to focus on this special characteristic. Hence, the proposed approach aims to reduce the overload noise effect on the reconstruction of the channel impulse response (CIR) through justice pursuit de-noising (JPDN) model and allows the use of the dynamic-threshold method for TOA estimation. The paper exploits the innovative basis pursuit de-noising (iBPDN) strategy to reduce computational load. The performances of the proposed approach are verified through numerical simulations.

Virtual Antenna Array and Fractional Fourier Transform-Based TOA Estimation for Wireless Positioning.

In this paper, a novel virtual antenna array and fractional Fourier transform (FRFT)-based 2-dimension super-resolution time-of-arrival (TOA) estimation algorithm for OFDM WLAN systems has been proposed. The proposed algorithm employs channel frequency responses (CFRs) at the equi-spaced positions on a line or quasi-line moving trajectory, i.e., the CFRs of a virtual antenna array, to extract multipaths’ TOA information. Meanwhile, a new chirp-like quadratic function is used to approximate the channel multipaths’ phase variation across the space dimension, which is more reasonable than the traditional linear function, especially for relatively big virtual antenna array sizes. By exploiting the property of chirp-like multipaths’ energy concentration in the FRFT domain, the FRFT can be first used to separate chirp-like multipath components, then the existing TOA estimation methods in frequency domain can be further employed on the separated multipath components to obtain the multipaths’ TOA estimates. Therefore, the proposed algorithm can make more use of the multipaths’ characteristics in the space dimension, thus it can efficiently enhance the multipath resolution and achieve better multipaths’ TOA estimation performance without requiring a real antenna array. Simulation results demonstrate the effectiveness of the proposed algorithm.

Method to Improve the Positioning Accuracy of Vehicular Nodes Using IEEE 802.11p Protocol

Currently, vehicle incidence remains high, but the related research is mainly focused on single-vehicle collision warning, which is unable to notice the following multiple endangered vehicles in emergency. The main technical challenge of chain collision warning is accurate and seamless ranging or positioning of the neighboring multiple vehicles. Because of the non-line of sight (NLOS) environments, the traditional ultrasonic or laser method does not work. At the same time, the accuracy of global navigation satellite system (GNSS) is over 10 m, such as global positioning system (GPS) or BeiDou satellite positioning system (BDS), which is not efficient for the cooperative collision avoidance (CCA) system. Moreover, GNSS fails to operate in NLOS tunnels or downtown areas where blockage of satellite signals is frequent. Thus, in this paper, a seamless and high accuracy positioning method based-on three kind of multi-source information fusion is proposed, i.e., the high accuracy local positioning information is provided by IEEE 802.11p protocol, the dual-mode wide area differential positioning information provided by the fusion of BDS and GPS, the positioning information of dead reckoning provided by the fusion of on-board diagnostic (OBD) and micro-electro-mechanical system-inertial navigation system. In vehicle positioning system, the accurate time of arrival (TOA) estimation is very important, so in this paper, a two steps method for TOA estimation using the IEEE 802.11p short preamble is proposed. Simulations show that in both the international telecommunication union vehicular multipath channel and the additive white Gaussian noise channel, the proposed method provides better accuracy and is less time complex than some well-known methods. The estimated TOA fused with the GNSS and OBD information can be used for seamless and high accuracy positioning in the CCA system to avoid traffic accident.

Threshold selection method for UWB TOA estimation based on wavelet decomposition and kurtosis analysis

In wireless sensor networks, ranging or positioning via ultra-wideband (UWB) has caused widespread research interests where the non-coherent energy detection (ED) method with low sampling rate and low complexity is widely studied. However, the traditional energy detection methods only analyze the signal energy in the time domain, so their error is relatively large. In this paper, the simulation results show that most of the signal energy concentrates in the low-frequency band, so a novel threshold selection method for time of arrival (TOA) estimation is proposed that analyzes the signals in both time domain and frequency domain. In this method, the received signal is decomposed by “db6” wavelet and the kurtosis of energy blocks of the low-frequency wavelet coefficients (Kc) is analyzed. At last, the mapping relationship between Kc and the normalized threshold for TOA estimation is created using polynomial fitting with degree 3. The simulation results show that the TOA estimation error of the proposed method is significantly less than the method without wavelet decomposition.

TOA Estimation for Positioning With DVB-T Signals in Outdoor Static Tests

Digital television signal is a promising signal of opportunity for wireless positioning. This paper studies the time of arrival (TOA) estimation on the European standard DVB-T signals in the context of positioning. Theoretical analysis on the autocorrelation of the pilot signal and multipath error envelop suggests that DVB-T has the appropriate characteristics for positioning. A software defined radio-based DVB-T receiver is developed for field testing, in which the radio frequency DVB-T signals are first sampled by universal software radio peripheral, and then algorithms of the coarse symbol synchronization, the pilot detection, the first path acquisition, and the delay tracking are sequentially performed to obtain the TOA estimation. To quantify the TOA tracking results on real DVB-T signals, field testing campaigns are carried out in five cities in Southern France. Test results showed that, in the high signal-noise ratio condition, the 2- $\sigma$ error interval is within 1 m. By taking into account all the field tests, the interval of 95% accuracy is within 4 m and the corresponding ${C/N_{0}}$ varies from 48 to 62 dB-Hz. In addition, with the developed TOA estimation method, the synchronization of the emitters with global positioning system time is evaluated and the distance difference of the multiple emitters within single frequency networks are also measured during the tests.

Wavelet packet transform‐based time of arrival estimation method for orthogonal frequency division multiplexing ultra‐wideband signal

This study discusses the estimation of time of arrival (TOA) used for ranging and positioning applications in orthogonal frequency division multiplexing ultra-wideband- (OFDM-UWB) based system. The correlation-based method applied for impulse radio-UWB (IR-UWB) is not suitable for OFDM-UWB because OFDM-UWB signal is much longer than IR-UWB in time domain. This study proposes a new method for TOA estimation of OFDM-UWB signal based on wavelet packet transform (WPT). The author's method estimates TOA of OFDM-UWB signal through the time information of the frequency band of UWB, which is one of the branches of WPT decomposition of the oversampled received baseband signal. It does not need the whole OFDM signal to estimate TOA of UWB signal because every segment of OFDM-UWB signal in time domain contains all information of UWB frequency band; therefore the resolution of TOA is improved. Signal-to-noise ratio can also be improved because WPT decomposes the power of additive white Gaussian noise equally in all wavelet packet branches, and false alarm rate can be controlled. The author's method is robust in that it can counter narrow band noise and impulse noise effectively. Numerical results show our method is effective for accurate estimation of TOA for OFDM-UWB signal.

Fast non‐linearly constrained least square joint estimation of position and velocity for X‐ray pulsar‐based navigation

Considering the limited computational capacity of on-board computer, a fast non-linearly constrained least square joint estimation of position and velocity is proposed for X-ray pulsar-based navigation (XNAV). The authors found that besides the distortion of the pulse profile, the Doppler caused by the spacecraft velocity alters the pulse time-of-arrival (TOA). The relationship model between the pulse TOA and the spacecraft velocity is built. Based on this, they can estimate the spacecraft velocity according to the variation of TOAs instead of the pulse profile distortion. In the proposed estimation method, the total observation interval is divided into several equal observation sub-intervals. Then a set of TOAs for sub-intervals can be obtained by the Fourier transform-based TOA estimation method. Finally, the non-linearly constrained least square estimation method is developed to estimate the spacecraft position and velocity. The simulation results have demonstrated that the proposed method is far faster than the maximum-likelihood estimation method, in which the spacecraft velocity is estimated via detecting the distortion of the folded pulse profile. The accuracy of the proposed method is robust to the initial errors and the elements of orbit.

High-Resolution Low-Complexity Cognitive-Radio-Based Multiband Range Estimation: Concatenated Spectrum vs. Fusion-Based

This paper, incorporating the principles of cognitive radios and utilizing the available bandwidth, proposes an active range estimation method with the properties of high precision and low complexity in wireless environments. Here, the cognitive radio concatenates the available narrow-band white spaces to increase the precision of a range estimation system. Two scenarios are investigated. First, signals are transmitted over an available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. To improve the range estimation performance, two new high-resolution time-of-arrival (TOA) estimation algorithms that are applicable to multiband scenarios are investigated. The first algorithm estimates the TOA over each subband and then optimally fuses the estimated TOAs. In the second technique, channels estimated over subbands are concatenated and a TOA estimation method is applied to the whole available spectrum. The TOA estimation error Cramer-Rao bounds of both approaches are computed. The performances of the proposed algorithm are investigated via simulations. The complexities of the introduced techniques are compared.

First Path Detection Using Rank Test in IR UWB Ranging with Energy Detection Receiver under Harsh Environments

To estimate time of arrival (TOA) in impulse radio (IR) ultra wideband (UWB) ranging under harsh environments, the rank test is adopted in the study to detect the first path (FP) in dense multipath with energy detection (ED) receiver. Most TOA estimation methods work well in the additive white Gaussian noise (AWGN). Actually, the background noise could be non-Gaussian. Moreover, the received signal could be polluted by outliers. In these cases, traditional threshold based methods perform badly, as there may be extraordinary large samples in the output of the receiver. These samples will interfere with the detection of the sample containing the FP. A novel and practical method based on the rank test is proposed to deal with these problems. The FP detection is based on the ranks of the received data samples instead of the samples. Simulations are carried out to demonstrate its effectiveness in the IEEE 802.15.4a channels.

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.

Linear quadrature optimisation-based non-coherent time of arrival estimation scheme for impulse radio ultra-wideband systems

Owing to the extremely high-time resolution of impulse radio ultra-wideband (IR-UWB), time of arrival (TOA) estimation has been an important and tempting issue of this technology ever since its emergence. Conventional TOA estimation (TOAE) schemes require prohibitively high sampling rate and a priori knowledge of the received signal, and hence render a practical implementation rigorous or even infeasible. To tackle these drawbacks, this paper proposes a low-complexity energy detection-based non-coherent TOAE scheme, which is composed of two processing stages: initial signal acquisition (ISA) and fine timing estimation (FTE). In the ISA stage, a linear quadrature optimisation (LQO)-based weighting scheme is proposed to coarsely capture the arrival of the IR-UWB signals. Capitalising on the acquisition of the IR-UWB signal in a relatively short time range, the authors then develop in the FTE stage, a double-threshold test (DTT) tailored for locating the leading edge of the IR-UWB signal. Simulations illustrate that the LQO algorithm yields a considerably increased probability of seizing the arrival of the IR-UWB signals in a blind manner, and the DTT strategy significantly ameliorates the TOAE accuracy in terms of mean absolute error, compared with the conventional energy detection-based TOAE methods.