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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.

The resilience of indoor localization systems is a main concern of their industrial application. A combination of different techniques can enhance the overall robustness of such systems. In this work, we present fusion possibilities of coarse Bluetooth Low Energy localization based on the received signal strength indicator and the finer ultrasound time difference of arrival (TDOA) technique.This approach offers the advantage to robustify the high-accuracy ultrasonic localization in areas with non-optimal coverage. Moreover, the data fusion enables to enhance the overall localization area in a cost effective manner. This contribution proposes and evaluates (i) novel methods of how the ultrasonic system can be extended to a constrained area and (ii) a novel possibility to incorporate available Bluetooth signal strength information in the TDOA algorithm to improve accuracy.

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