TDOA Measurements Research Articles

Self UAV Localization Using Multiple Base Stations Based on TDoA Measurements

Self UAV Localization Using Multiple Base Stations Based on TDoA Measurements

Bayesian-Based Indoor Factory Positioning Using AOA, TDOA, and Hybrid Measurements

Bayesian-Based Indoor Factory Positioning Using AOA, TDOA, and Hybrid Measurements

Line-of-sight aware accurate collaborative localization based on joint TDoA and AoA measurements in UWB-MIMO environment

Line-of-sight aware accurate collaborative localization based on joint TDoA and AoA measurements in UWB-MIMO environment

Regularized Constrained Total Least Squares Source Localization Using TDOA and FDOA Measurements

Regularized Constrained Total Least Squares Source Localization Using TDOA and FDOA Measurements

Source Localization Based on Hybrid AOA, TDOA, and RSS Measurements

In this paper, a constrained weighted least squares (CWLS) problem with two quadratic constraints for hybrid AOA, TDOA, and RSS localization is formulated. The Lagrange multiplier method cannot be efficiently used in this situation, so we provide four methods to solve the CWLS problem: 1) weighted least squares (WLS); 2) iterative constrained weighted least squares (ICWLS); 3) Lagrange multiplier method combined with Newton’s method (LMM+NM); 4) semidefinite programming (SDP). Furthermore, in order to obtain a good balance between accuracy and computational burden, we develop a fixed point iteration (FPI)-based algorithm that is derived from an approximate maximum likelihood estimator (MLE). Simulation results show that the accuracy of the proposed FPI method is better than the other four methods; besides, its computational burden is one in ten of the SDP algorithm.

A Multiple Target Data Association Method for TDOA Passive Localization

In order to solve the multiple target data association problem in underwater acoustic passive localization system, a new algorithm focus on data association in Time Difference of Arriva l(TDOA) is studied. Firstly, the zero-sum condition is used to select TDOA measurements according to the continuous measurement values within a certain period of time. Then, the selected TDOA measurements are associated with the multiple targets and the correct correlation probability is measured by the correlation degree. The algorithm is used in sea trial. Processing results show that the method proposed in this paper can effectively solve the TDOA measurement association problem, and can locate multiple targets at the same time.

A Two-Stage Method for Short-Wave Target Localization Using DOA and TDOA Measurements

A Two-Stage Method for Short-Wave Target Localization Using DOA and TDOA Measurements

Geolocation a known‐altitude moving source by TDOA and FDOA measurements

Source altitude information, if known or can be measured by an altimeter, can greatly improve localisation performance. In this letter, a novel algebraic solution for known-altitude moving source geolocation using time difference of arrival and frequency difference of arrival measurements is developed. The localisation problem is solved via the successive unconstrained minimisation method. Simulation results demonstrate that the estimation accuracy of the source position and velocity can achieve the constrained Cramér–Rao lower bound at moderate noise levels.

A fast and accurate LEO satellite-based direct position determination assisted by TDOA measurements

This paper focuses on the trusted vessel position acquisition using passive localization based on the booming low-earth-orbit (LEO) satellites. As the high signal-to-noise ratio (SNR) reception cannot always be guaranteed at LEO satellites, the recently developed direct position determination (DPD) is adopted. For LEO satellite-based passive localization systems, an efficient DPD is challenging due to the excessive exhaustive search range leading from broad satellite coverage. In order to reduce the computational complexity, we propose a time difference of arrival-assisted DPD (TA-DPD) which minimizes the searching area by the time difference of arrival measurements and their variances. In this way, the size of the searching area is determined by both geometrical constraints and qualities of received signals, and signals with higher SNRs can be positioned more efficiently as their searching areas are generally smaller. Both two-dimensional and three-dimensional passive localization simulations using the proposed TA-DPD are provided to demonstrate its efficiency and validity. The superior accuracy performance of the proposed method, especially at low SNRs conditions, is also verified through the comparison to conventional two-step methods. Providing a larger margin in link budget for satellite-based vessel location acquisition, the TA-DPD can be a competitive candidate for trusted marine location service.

Corrections to “Outlier-Robust Student's-t-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements” [Jun 20 1646-1658

Corrections to “Outlier-Robust Student's-t-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements” [Jun 20 1646-1658

Outlier-Robust Student's-$t$-Based IMM-VB Localization for Manned Aircraft Using TDOA Measurements

This article proposes a novel outlier-robust localization algorithm that is based on time difference of arrival measurements at an airport for multilateration surveillance. An outlier-robust filtering scheme is derived based on Student's- $t$ -distribution, where the state, a scale matrix, and a degree of freedom parameter are estimated simultaneously using variational Bayesian (VB) inference. An interacting multiple model (IMM) filter with different system models is implemented to handle the multimodal dynamics of the aircraft, yielding the IMM-VB algorithm. Specifically, the likelihood function is newly derived using VB inference for the combination procedure in the proposed IMM-VB algorithm. The experimental results obtained from a flight test using a commercial aircraft at an airport demonstrate that the proposed IMM-VB algorithm has better localization accuracy and robustness to outlier measurements than the existing state-of-the-art approaches.

Phase tracking approach for TDOA measurements in critical lunar spaceflights

Phase tracking approach for TDOA measurements in critical lunar spaceflights

Target localisation in multistatic radar using BR, TDOA, and AOA measurements

This study investigates the target localisation problem by using the hybrid bistatic range (BR), time difference of arrival, and angle of arrival (AOA) measurements in multistatic passive radar. An explicit algebraic solution is developed by linearising the non-linear measurement equations through introducing multiple nuisance parameters in the first stage and estimating the localisation error of the first stage solution to refine the final target position estimate in the second stage. The closed-form resulting estimator has attractive computational complexity. Theoretical analysis of the proposed method is presented, and it is shown to be able to reach the Cramer–Rao lower bound at low noise levels. Simulations are included to validate the performance of the proposed estimator.

Wireless Sensor Network-Based Localization Method Using TDOA Measurements in MPR

Localization is perhaps one of the most interesting research subjects in signal processing. Traditional localization methods rely on the prior information whether the source is located in the near-field or far-field. Since the prior knowledge is hard to obtain in practice, neither positioning nor bearing may not be able to provide reliable performance for both cases. The modified polar representation (MPR) is proposed to solve this contradictory problem in a uniform framework and eliminate the thresholding effect as the source range increases. The maximum likelihood estimator (MLE) in the state-of-art research realizes excellent performance reaching the Cramer-Rao lower bound (CRLB) but it is computation-complex and time-consuming. Besides, it has the possible divergence problem if the initial value is not close enough to the true value. This paper focuses on the localization problem using time difference of arrival measurements in MPR. Formulating it in a new form, we develop a two-step least squares (LS) estimator for the MPR model. The weighted total LS is applied in the first step and the weighted LS for the final solution, where the second step is based on the natural constraint of the unknowns. The proposed method is closed-form and able to reach CRLB in low noise power situation irrespective of the source range. The covariance is analyzed and proved to provide CRLB accuracy for Gaussian noise theoretically. Simulation supports our theoretical results and verifies the advocated performance that is comparable with MLE but simpler and computationally more efficient. It outperforms the classical closed-form solution.

Adaptive Filtration of Radio Source Movement Parameters Based on Sensor Network TDOA Measurements in Presence of Anomalous Measurements

The methods based on TDOA measurements find wide application for localization of radio sources using wireless sensor networks. The need of taking into account the presence of anomalous measurement results often occurs in real conditions. Their appearance means a significant malfunction of sensor network components that results in divergence of traditional algorithms of Kalman filtration of radio source movement parameters. Based on the mathematical tools of mixed Markov processes in discrete time domain, the optimal and quasioptimal algorithms of adaptive filtration of radio source movement parameters were synthesized on the basis of TDOA measurements of sensor network in the presence of anomalous measurements. The optimal algorithm describes the evolution of joint a posteriori probability density of the vector of movement parameters and switching variables determining the type of measurement errors of network sensors. The quasioptimal algorithm obtained by linearization of the measurement equation involves the implementation of sequential technique of incoming data processing and performance of the Gaussian approximation of a posteriori probability density of radio source movement parameters. For the case considered in this paper using the statistical simulation, the developed quasioptimal algorithm makes it possible to recognize the appearance of anomalous errors of measurements with probability close to unity and eliminate their impact on the accuracy of determining the radio source movement parameters.

Improved Algebraic Solution for Source Localization From TDOA and FDOA Measurements

In this letter, an improved version of the popular two-stage weighted least squares (WLS) algorithm is presented to determine the position and velocity of a moving source using time difference of arrival and frequency difference of arrival measurements in a wireless sensor network. A closed-form solution is obtained from the minimization of the WLS criterion in each stage. The estimator accuracy is shown analytically to attain the Cramer–Rao lower bound under the small Gaussian noise assumption. Numerical simulations are included to support and corroborate the theoretical developments.

Iterative Constrained Weighted Least Squares Source Localization Using TDOA and FDOA Measurements

This paper investigates the constrained weighted least squares (CWLS) source localization problem by using time difference of arrival and frequency difference of arrival measurements. The problem can be formulated as a quadratic programming with two indefinite quadratic equality constraints, which is nonconvex and NP-hard. Moreover, the weighting matrix is coupled with the unknown source position and velocity. We propose an iterative CWLS method that can efficiently solve this problem. It iteratively performs a linearization procedure on the quadratic equality constraints to obtain an approximate programming with linear constraints, which can be analytically solved, and the weighting matrix is updated in each iteration. Theoretical analysis reveals that the proposed method, if converges, can lead to the global optimal solution of the formulated problem that reaches the CRLB accuracy under mild assumptions on the measurement noises. The Monte Carlo simulation results indicate that the percentage of convergence within $\mathbf 20$ iterations is more than $\mathbf 96\%$ , and the localization accuracy is significantly improved over the previous methods with less computation time requirement. Moreover, it is found from simulations that the iterative CWLS method retains acceptable performance even under the ill-conditioned situation when the sensor geometry is not desirable.

Detection of PUE Attack in CRN with Reduced Error in Location Estimation Using Novel Bat Algorithm

Cognitive Radio Network Technology makes the efficient utilization of scarce spectrum resources by allowing the unlicensed users to opportunistically use the licensed spectrum. Cognitive Radio Network due to its flexible and open nature is vulnerable to a number of security attacks. This paper is mainly concerned with one of the physical layer attack called Primary User Emulation Attack and its detection. This paper solves the problem of PUE attack by localization technique based on TDOA measurements with reduced error in location estimation using a Novel Bat Algorithm (NBA). A number of cooperative secondary users are used for detecting the PUEA by comparing its estimated position with the known position of incumbent. The main goal of NBA is to minimize two fitness functions namely non-linear least square and the maximum likelihood in order to optimize the estimation error. After evaluation, simulation results clearly demonstrates that NBA results in reduced estimation error as compared to Taylor Series Estimation and Particle Swarm Optimization.

Estimating geo-position and depth of echo-locating beaked whales using an array of drifting recorders

An array of 8 drifting recorders were deployed in the Catalina Basin off Southern California to localize beaked whales. The drifting recorders with hydrophone pairs at 90-135 m were deployed along two parallel lines with ~1 km separation between recorders. The array was re-deployed daily at approximately the same location to maintain this array spacing. Cuvier’s beaked whales (Ziphius cavirostris) were detected on 26 occasions from their distinctive echo-location clicks. On 8 of these occasions, direct-path and surface-reflected signals were received on four or more drifting recorders, which allowed us to estimate location and depth of the whales. Average array tilt during these events was less than 0.2°, and always less than 0.6°. The same echolocation clicks were seldom received on more than two recorders, so we could not use methods that require TDOA measurements between recorders. We develop a novel method of 3-D localization using the vertical bearing angles estimated from the direct- and surface-reflected signals and use optimization methods to find the unique location and depth at which these angles converged. Detection ranges varied from 1.0 to 3.7 km (mean = 2.0, sd = 0.65), and depths of vocalizing animals varied from 696-1150 m (mean = 948, sd = 152).

Optimal Sensor Velocity Configuration for TDOA-FDOA Geolocation

This paper establishes the velocity orientation requirements for dual or multiple mobile sensors to achieve optimal localization of a stationary emitter, based on TDOA and FDOA measurements. In one approach, optimal velocities are obtained by maximizing the determinant of the Fisher Information Matrix (FIM). The other approach calls for minimizing the trace of the FIM inverse. The paper shows that for a given source-sensor position geometry, two opposite optimal sensor velocity configurations are possible. One way to apply the results of this paper is to deploy sensors onboard highly maneuvering platforms, which are able to rapidly align the platform velocities with those computed by one of the optimization approaches. This usually brings a significant increase in emitter localization accuracy even if the initial sensor-source position geometry is poor. A number of computer simulations are given in the paper, which confirms the paper's theoretical findings.