Abstract
<p>While global navigation satellite system (GNSS)technologies have always been the go-to solution for localizationproblems, they may not be the best choice for some Internet-of-Things (IoT) applications due to the incurred power consumptionand cost. In this paper, we present an alternative satellite-basedlocalization method exploiting the signature of Doppler shifts andangle of arrival measurements as seen by a receiving satellite.We first derive the joint likelihood function of the measurements,which is represented as a combination of three Gaussian distri-butions. Then, we show that the maximum likelihood problemreduces to a more-efficient mean squared error minimizationin the Gaussian case as inferred from real measurements wecollected from low-earth-orbit satellite using a tracking groundstation. Thus, we propose utilizing a stochastic optimizer tosearch for the global minimum of the mean squared error whichrepresents the location of the ground IoT device as estimated bythe satellite platform. The emulated results show that the IoTdevice localization, under such realistic model, can be performedwith sufficient accuracy for IoT applications.</p>
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Cited by
1 articles.
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