Calibration-free TDOA self-localisation

Wendeberg, Johannes; Höflinger, Fabian; Schindelhauer, Christian; Reindl, L.

doi:10.1080/17489725.2013.796410

Cited by 17 publications

(12 citation statements)

References 17 publications

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“…The "Iterative Cone Alignment" algorithm [39,40] solves iteratively a nonlinear optimization problem of TDoA by a physical spring-mass simulation. The success rate of solving the calculation of the receiver positions was increased to 99.4% (with only six received signals and four receivers).…”

Section: Calibration Phasementioning

confidence: 99%

Acoustic Self-Calibrating System for Indoor Smart Phone Tracking

Ens

Höflinger

Wendeberg

et al. 2015

International Journal of Navigation and Observation

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This paper presents an acoustic indoor localization system for commercial smart phones that emit high pitched acoustic signals beyond the audible range. The acoustic signals with an identifier code modulated on the signal are detected by self-built receivers which are placed at the ceiling or on walls in a room. The receivers are connected in a Wi-Fi network, such that they synchronize their clocks and exchange the time differences of arrival (TDoA) of the received chirps. The location of the smart phone is calculated by TDoA multilateration. The precise time measuring of sound enables high precision localization in indoor areas. Our approach enables applications that require high accuracy, such as finding products in a supermarket or guiding blind people through complicated buildings. We have evaluated our system in real-world experiments using different algorithms for calibrationfree localization and different types of sound signals. The adaptive GOGO-CFAR threshold enables a detection of 48% of the chirp pulses even at a distance of 30 m. In addition, we have compared the trajectory of a pedestrian carrying a smart phone to reference positions of an optic system. Consequently, the localization error is observed to be less than 30 cm.

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Section: Calibration Phasementioning

confidence: 99%

Acoustic Self-Calibrating System for Indoor Smart Phone Tracking

Ens

Höflinger

Wendeberg

et al. 2015

International Journal of Navigation and Observation

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“…Different approximation strategies have been developed to reduce this risk. Wendeberg et al [5,6] used an iterative cone alignment algorithm for the iterative solving of a nonlinear TDOA optimization problem through a physical spring-mass simulation. In [7], this problem was re-formulated by a linear rank constraint on the matrix, and the unknown variables were estimated by minimizing the cost function using nuclear norm minimization.…”

Section: Related Workmentioning

confidence: 99%

Self-Calibration for the Time Difference of Arrival Positioning

Sidorenko

Schatz

Bulatov

et al. 2020

Sensors

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The time-difference-of-arrival (TDOA) self-calibration is an important topic for many applications, such as indoor navigation. One of the most common methods is to perform nonlinear optimization. Unfortunately, optimization often gets stuck in a local minimum. Here, we propose a method of dimension lifting by adding an additional variable into the l 2 norm of the objective function. Next to the usual numerical optimization, a partially-analytical method is suggested, which overdetermines the system of equations proportionally to the number of measurements. The effect of dimension lifting on the TDOA self-calibration is verified by experiments with synthetic and real measurements. In both cases, self-calibration is performed for two very common and often combined localization systems, the DecaWave Ultra-Wideband (UWB) and the Abatec Local Position Measurement (LPM) system. The results show that our approach significantly reduces the risk of becoming trapped in a local minimum.2 of 15 common and often combined systems are the DecaWave Ultra-Wideband (UWB) and the Abatec Local Position Measurement (LPM) system. The DecaWave UWB system is less affected by reflections, but is, due to regulations, limited in its transmitting power. The LPM system faces the opposite problem. However, here, the problem of self-localization becomes problematic, where neither the positions of the transmitters nor the receivers are known. This is analogous to the microphone-speaker problem, where systems of (sometimes redundant or self-contradicting) quadratic equations must be solved, sometimes resulting in zero and sometimes resulting in dozens of solutions for the minimum cases (see Chapter 10 in [2]). In the few related works outlined below, it is therefore commonplace to find overdetermined systems of equations. From a reliable solution and a suitable optimizer, these systems are developed to converge to the global minimum and thus successfully self-localize the sensors.The notations used in the text and in the equations are shown in Tables 1 and 2.

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“…This would lead to high positioning errors if the receiver moves at high velocity. Wendeberg et al [25] and Bordoy et al [26] show the feasibility of reference and calibration free localization systems with TDOA. As a result, the mobile receivers have no information about the positions of the beacons and themself.…”

Section: Related Workmentioning

confidence: 99%

“…Once the timestamps corresponding with the time when the receiver is standing are selected, we can extend the approach in [25] to unsynchronized senders. For simplicity and better understanding we assume that there are G selected signals from every sender.…”

Section: Calibration Phasementioning

confidence: 99%

Unsynchronized ultrasound system for TDOA localization

Ens

Reindl

Bordoy

et al. 2014

2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

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Indoor localization based on time difference of arrival (TDOA) has been recently a promising field of study. We consider the previously unsolved problem of locating a moving target receiver by using unsynchronized stationary beacons without requirement of manual calibration. Thus, the received signals and their time of arrival (TOA) have to be assigned to a beacon. Besides, in order to automatically calibrate the system it is required to estimate the time offsets between the senders, their positions and the initial receiver position.We present an approach to estimate all the variables of the scenario using the gradient descent and the Gauss-Newton method, two local optimization algorithms which use the derivative of a system of hyperbolic error equations. Besides, we present an ultrasound transmission system approach which fulfils the requirements of this scenario, being robust against multipath and estimating the reception time with high accuracy. In order to avoid interference by echoes the packet size is reduced by using two frequencies in Orthogonal Frequency Division Multiplex (OFDM). Further, the transmission system enables distinction of the beacons, as the ultrasound signals are used both for localization and for information transmission.The simulations show the local optimization algorithms are capable of estimating the positions of the beacons, receivers and offsets. They require only a rough knowledge of the sender positions. Further, real experiments show that the timestamps are measured with a standard deviation of only 1.19 μs for a SNR of 10 dB, which corresponds to standard deviation of about 0.4 mm for the distance measurement.

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Calibration-free TDOA self-localisation

Cited by 17 publications

References 17 publications

Acoustic Self-Calibrating System for Indoor Smart Phone Tracking

Acoustic Self-Calibrating System for Indoor Smart Phone Tracking

Self-Calibration for the Time Difference of Arrival Positioning

Unsynchronized ultrasound system for TDOA localization

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