A TDOA Technique with Super-Resolution Based on the Volume Cross-Correlation Function

Shi, Hailong; Zhang, Hao; Wang, Xiqin

doi:10.1109/tsp.2016.2548988

Cited by 26 publications

(7 citation statements)

References 49 publications

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“…Usually, cross-correlating BS signal Y i ( t ) ( i = 1, 2, 3 … N ) with BS 0 signal Y 0 ( t ) can get N cross-correlation functions R i 0 ( τ ) ( i = 1, 2, 3, …, N ). After detecting peaks on R i 0 ( τ ) and eliminating the interference from ambiguous peaks with prior information [ 20 ], the signal time difference of arrival measurements τ i 0 ( i = 1, 2, 3 … N ) between BSi to BS 0 is found.…”

Section: Algorithm and Processmentioning

confidence: 99%

Robust Time-Difference-of-Arrival (TDOA) Localization Using Weighted Least Squares with Cone Tangent Plane Constraint

Jin

Zhang

2018

Sensors

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Finding the position of a radiative source based on time-difference-of-arrival (TDOA) measurements from spatially separated receivers has been widely applied in sonar, radar, mobile communications and sensor networks. For the nonlinear model in the process of positioning, Taylor series and other novel methods are proposed. The idea of cone constraint provides a new way of solving this problem. However, these approaches do not always perform well and are away from the Cramer-Rao-Lower-Bound (CRLB) in the situations when the source is set at the array edge, the noise in measurement is loud, or the initial position is biased. This paper presents a weighted-least-squares (WLS) algorithm with the cone tangent plane constraint for hyperbolic positioning. The method adds the range between the source and the reference sensor as a dimension. So, the space-range frame is established. Different from other cone theories, this paper sets the reference sensor as the apex and finds the optimal source estimation on the cone. WLS is used for the optimal result from the measurement plane equations, a vertical constraint and a cone constraint. The cone constraint equation is linearized by a tangent plane. This method iterates through loops and updates the tangent plane, which approximates the truth-value on the cone. The proposed algorithm was simulated and verified under various conditions of different source positions and noises. Besides, some state-of-the-art algorithms were compared in these simulations. The results show that this algorithm is accurate and robust under poor external environment.

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Section: Algorithm and Processmentioning

confidence: 99%

Robust Time-Difference-of-Arrival (TDOA) Localization Using Weighted Least Squares with Cone Tangent Plane Constraint

Jin

Zhang

2018

Sensors

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“…where is the carrier frequency of the signal in MHz and is the 3-D Euclidean distance between the aircraft and the i-th GRS obtain using Eq. (9).…”

Section: Signal Attenuation Based On Fspl Propagation Modelmentioning

confidence: 99%

“…Several approaches to TDOA estimations have been reported in literatures [6][7][8][9] but the most commonly used approach is the cross-correlation (CC) method [8,9]. The CC method is used particularly in the case of constant delay, stationary process and long observation intervals [9]. In practical applications, signals are corrupted with noise will leads to TDOA estimation error.…”

Section: Introductionmentioning

confidence: 99%

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Effect of Path Loss Propagation Model on the Position Estimation Accuracy of a 3-Dimensional Minimum Configuration Multilateration System

Yaro

Sha’ameri

2018

IJIE

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The 3-Dimensional (3-D) position estimation (PE) accuracy of a multilateration (MLAT) system depends on several factors one of which is the accuracy at which the time difference of arrival (TDOA) measurements are obtained. In this paper, signal attenuation is considered to be the major contributor to the TDOA estimation error and its effect based on path loss propagation model on the PE accuracy of the MLAT system is determined. The two path loss propagation models considered are: Okumura-Hata and the free space path loss (FSPL) model. The transmitter and receiver parameters used for the analysis are based on actual system used in the civil aviation surveillance. Monte Carlo simulation result based on square ground receiving station (GRS) configuration and at some randomly selected aircraft positions show that the MLAT system with the Okumura-Hata model has the highest PE error. The horizontal coordinate and altitude errors obtained considering the Okumura-Hata are 2.5 km and 0.6 km respectively higher than that obtained with the FSPL model.

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“…Wang et al [ 28 ] used a two-dimensional MUSIC algorithm to estimate TOA and AOA in a IR-UWB system, and the simulation results showed that the performance is better than RootMUSIC and matrix pencil algorithm. Hailong et al [ 29 ] proposed a novel TDOA algorithm with super resolution based on a multi-dimensional cross-correlation function, namely the volume cross-correlation function (VCC). Numerical simulations showed an excellent time resolution capability of the algorithm in multipath environment.…”

Section: Introductionmentioning

confidence: 99%

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

Deng

Zheng

Wang

et al. 2020

Sensors

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Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.

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A TDOA Technique with Super-Resolution Based on the Volume Cross-Correlation Function

Cited by 26 publications

References 49 publications

Robust Time-Difference-of-Arrival (TDOA) Localization Using Weighted Least Squares with Cone Tangent Plane Constraint

Robust Time-Difference-of-Arrival (TDOA) Localization Using Weighted Least Squares with Cone Tangent Plane Constraint

Effect of Path Loss Propagation Model on the Position Estimation Accuracy of a 3-Dimensional Minimum Configuration Multilateration System

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments

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