Distributed Spatio-Temporal Information Based Cooperative 3D Positioning in GNSS-Denied Environments

Abstract

A distributed spatio-temporal information based cooperative positioning (STICP) algorithm is proposed for wireless networks that require three-dimensional (3D) coordinates and operate in the global navigation satellite system (GNSS) denied environments. Our algorithm supports any type of ranging measurements that can determine the distance between nodes. We first utilize a finite symmetric sampling based scaled unscented transform (SUT) method for approximating the nonlinear terms of the messages passing on the associated factor graph (FG) with high precision, despite relying on a small number of samples. Then, we propose an enhanced anchor upgrading mechanism to avoid any redundant iterations. Our simulation results and analysis show that the proposed STICP has a lower computational complexity than the state-of-the-art belief propagation based localizer, despite achieving an even more competitive positioning performance.

Factor Graph Weight Particles aided Distributed Underwater Cooperative Positioning Algorithm

“…Different from GNSS-based CP methods, the range-based CP methods estimate the inter-node ranges by using radio ranging techniques such as time-of arrival (TOA) [16], angle of arrival (AOA) [17], receiver signal strength (RSS) [18] and round-trip time (RTT) [19]. The range-based CP methods are more suitable for the scenarios where the availability of GNSS is limited [20]. Additional radio ranging measurements could help to improve the positioning availability and decrease the positioning errors.…”