Abstract
The primary goal of this paper is to propose a new factor graph (FG) technique for the direction-of-arrival (DOA)-based three-dimensional (3D) multi-target geolocation. The proposed FG detector uses only the mean and the variance of the DOA measurement including both the azimuth and the elevation, assuming that they are suffering from errors following a Gaussian probability density function (PDF). Therefore, both the up-link (UL) transmission load and the detection complexity can be significantly reduced. The Cramer-Rao lower bound (CRLB) of the proposed DOA-based 3D geolocation system is mathematically derived. According to the root mean square error (RMSE) results obtained by simulations, the proposed FG algorithm is found to outperform the conventional linear least square (LS) approach, which achieves a very close performance to the derived CRLB. Moreover, we propose a sensor separation algorithm to solve the target-DOAs matching problem such that the DOAs, measured by each sensor, can be matched to their corresponding targets. With this technique, additional target identification is not needed, and the multi-target geolocation can be decomposed into multiple independent single-target detections.
Highlights
As one of the enabling technologies of building a smart city, wireless geolocation with densely distributed sensors is expected to play an important role in the future network functionalities [1]
The techniques described above may not be applicable for the generation geolocation system due to three reasons: (1) massively deployed sensors in the future network are expected to be cheap, where complicated hardwares may not be equiped; (2) targets may be anonymous, and conventioanl identification techniques used in wireless communications, e.g., the target-specific reference signal, may not be available; (3) multi-target DOA estimation can be conducted at every individual sensor, techniques for matching between the DOAs, measured by each sensor, and their corresponding targets are not yet known
It has been shown that the proposed technique outperforms the conventional least square (LS) approach in terms of the average root mean square error (RMSE)
Summary
As one of the enabling technologies of building a smart city, wireless geolocation with densely distributed sensors is expected to play an important role in the future network functionalities [1]. To satisfy such requirements in future networks, this paper proposes a new DOA-based FG technique for 3D anonymous multi-target geolocation Both the azimuth and the elevation measured at each sensor are taken into account in the proposed FG detector, where new factor nodes are introduced to connect the both angles to the position parameters in the standard 3D coordinate. The techniques described above may not be applicable for the generation geolocation system due to three reasons: (1) massively deployed sensors in the future network are expected to be cheap, where complicated hardwares may not be equiped; (2) targets may be anonymous, and conventioanl identification techniques used in wireless communications, e.g., the target-specific reference signal, may not be available; (3) multi-target DOA estimation can be conducted at every individual sensor, techniques for matching between the DOAs, measured by each sensor, and their corresponding targets are not yet known.
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