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In this study, the authors investigate the problem of source localisation based on the time difference of arrival (TDOA) in a group of sensors. Aiming to minimise the squared range-difference errors, the problem leads to a quadratically constrained quadratic programme. It is well known that this approach results in a non-convex optimisation problem. By proposing a relaxation technique, they show that the optimisation problem would be transformed to a convex one which can be solved by semi-definite programming (SDP) and Lagrange multiplier methods. Moreover, these methods offer the exact solution of the original problem and the affirmation of its uniqueness. In contrast to other complicated... 

This paper examines the problem of determining optimal sensors trajectories for localization of a moving radio source based on Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) measurements in situations in which sensors are constrained both in their movements and regions of operation. By considering the movement of the source and constrained movement of the sensors, a constraint problem is formed which is solved to determine optimal trajectories of the sensors for source tracking. The validity of the proposed algorithm is assessed by two different simulation scenarios and the results verify its proper operation with estimation error decreasing in consecutive steps... 

This paper presents a new approach to sensor placement strategy in emitter localization problem which is based on Time Difference of Arrival (TDOA) measurements. The advantage of this method is its flexibility and capability of positioning sensors in constrained or non-stationary situations in which the positions of the sensors are restricted to certain portions of the space and/or needed to be changed repeatedly. The validity of the proposed algorithm is assessed by three different simulation scenarios and the results verify its proper operation  

In this paper, a sparsity-aware target localization method in multiple-input-multiple-output (MIMO) radars by utilizing time difference of arrival (TDOA) measurements is proposed. This method provides a maximum likelihood (ML) estimator for target position by employing compressive sensing techniques. Also, for fast convergence and mitigating the mismatch problem due to grid discretization, we address a block-based search coupled with an adaptive dictionary learning technique. The Cramer-Rao lower bound for this model is derived as a benchmark. Simulations results are included to verify the localization performance  

The Cramer-Rao lower bound for source localization based on Time Difference of Arrival and Frequency Difference of Arrival is investigated in this paper. The result is used for theoretical analysis of optimality in sensor placement. An optimal sensor-target geometry including sensors locations and velocities is presented and its properties is studied  

This paper focuses on localizing acoustic source using fuzzy logic. For this purpose, an array of microphones are used as sensors. The Time Delay Estimation (TDE) is performed by correlation between received signals from each pair of microphones. In this paper, instead of assuming a crisp value as a TDOA, we introduce fuzzy number of TDOA in which the absolute value of the cross correlation function is normalized and then assumed as TDOA membership function for each pair of microphones. Truth value of presenting acoustic source is computed in region of interest based on achieved TDOA membership functions. Computing this truth value is represented in this paper based on fuzzy logic. The... 

In some well-known passive localization methods, when the number of equations equals the number of unknown object coordinates, there arise finite number of possible solutions. A localization disambiguation technique is required to identify the correct solution in these cases. As an example, the exact solution of time-difference-of-arrival (TDOA) based equations for four receiver sites, leads to a couple of solutions with only one of them being the true target position. This ambiguity, conventionally is resolved by using angle-of-arrival (AOA) measurements or using an additional receiver site which increase the cost and complexity of the system. In this paper a localization disambiguation... 

This study presents a new approach to sensor placement strategy in emitter localisation problems based on time difference of arrival measurements. The method addresses a flexible procedure which is capable of positioning the sensors in constrained environments or non-stationary situations where the positions of the sensors are restricted to certain parts of the space and/or need to be changed repeatedly. This method is sequential and has lower computation burden compared to other methods. The validity of the proposed algorithm is assessed by many different numerical scenarios and the results verify its proper operation. © The Institution of Engineering and Technology 2017  

In this letter, the problem of source localization using time difference of arrival (TDOA) is investigated. Then, a closedform two-stage solution is proposed based on estimation of the range nuisance parameter in the first stage and refinement of initial solution in the next stage. The proposed solution is shown analytically and verified by simulations to be an efficient estimate, which can attain the CRLB performance under mild Gaussian noise assumption. This method is able to locate the source with the minimum number of sensors required for N-dimensional localization. Numerical simulations demonstrate significant performance improvement of the proposed method compared with the... 

Several target position finding methods are proposed in various papers mainly regarding sensor networks. However, the problem of position finding in passive radar systems is somewhat different from the general case of sensor networks. Generally, in a passive radar system, there are few receivers located at short distances when compared with the it distance from the target. In this case, a problem known as geometric dilution of precision (GDP) occurs, which considerably increases the error of many proposed methods. This phenomenon can even make the position finding equations non-solvable. Regarding this fact, we have developed a least mean square error (LMSE) based method, which uses both the... 

In some well-known passive localization methods, when the number of equations equals the number of unknown object coordinates, there arise finite number of possible solutions. A localization disambiguation technique is required to identify the correct solution in these cases. As an example, the exact solution of time-difference-of-arrival (TDOA) based equations for four receiver sites, leads to a couple of solutions with only one of them being the true target position. This ambiguity conventionally is resolved by using angle-of-arrival measurements or using an additional receiver site, which increase the cost and complexity of the system. In this paper, a localization disambiguation... 

The sensor-source geometry has a significant effect on accuracy of source localization problems. In a sensor placement problem, one attempts to optimally place the sensors in the surveillance area so as to optimize a performance criterion. Sensor placement methods mainly solve the associated problems without taking any specific constraint on permissible location of sensors into account. In practical applications, however, possible location for deployment of the sensors are subject to such limitations as environmental, industrial, and communication constraints, which affects the optimal sensor-source geometry. In this article, we consider the problem of optimal sensor placement, based on time... 

Localization of radio-frequency (RF) transmitters using time difference of arrival (TDOA)-based methods is one of the conventional passive techniques that admits noncooperative source position finding, but suffers from challenging requirements such as precise intersensor synchronization and high-throughput transmission data links. A tradeoff governing the TDOA systems is in the sensor placement configuration. The more distance the sensors are placed, the more accurate localization is carried out, while the cost for the synchronization and data link increases, at the same time. In this work, a novel reconfigurable intelligent surface (RIS)-aided localization system is proposed that enjoys...