Accuracy studies for TDOA and TOA localization
Regina Kaune
Abstract
Regina Kaune
Abstract
In sensor networks, passive localization can be performed by exploiting the received signals of unknown emitters. In this paper, the Time of Arrival (TOA) measurements are investigated. Often, the unknown time of emission is eliminated by calculating the difference between two TOA measurements where Time Difference of Arrival (TDOA) measurements are obtained. In TOA processing, additionally, the unknown time of emission is to be estimated. Therefore, the target state is extended by the unknown time of emission. A comparison is performed investigating the attainable accuracies for localization based on TDOA and TOA measurements given by the Crame?r-Rao Lower Bound (CRLB). Using the Maximum Likelihood estimator, some characteristic features of the cost functions are investigated indicating a better performance of the TOA approach. But counterintuitive, Monte Carlo simulations do not support this indication, but show the comparability of TDOA and TOA localization.
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In sensor networks, passive localization can be performed by exploiting the received signals of unknown emitters. In this paper, the Time of Arrival (TOA) measurements are investigated. Often, the unknown time of emission is eliminated by calculating the difference between two TOA measurements where Time Difference of Arrival (TDOA) measurements are obtained. In TOA processing, additionally, the unknown time of emission is to be estimated. Therefore, the target state is extended by the unknown time of emission. A comparison is performed investigating the attainable accuracies for localization based on TDOA and TOA measurements given by the Crame?r-Rao Lower Bound (CRLB). Using the Maximum Likelihood estimator, some characteristic features of the cost functions are investigated indicating a better performance of the TOA approach. But counterintuitive, Monte Carlo simulations do not support this indication, but show the comparability of TDOA and TOA localization.
Key concepts: Multilateration, Time of arrival, Cramér–Rao bound, Estimator, Computer science, FDOA, Algorithm, Monte Carlo method