Decentralized GNSS PPP-RTK

PPP-RTK, known as integer ambiguity resolution-enabled precise point positioning, requires precise satellite-related products and atmospheric corrections estimated in a global navigation satellite system (GNSS) network. In generating these products, one commonly sends all network data to a computation center and conducts a centralized processing scheme. However, this centralized PPP-RTK faces considerable challenges in computational efficiency and model formulation with the increasing number of receivers. This work proposes a decentralized PPP-RTK processing strategy that generates products in three steps: subnetwork processing, satellite-related product integration, and atmospheric correction update. The first step divides the whole network into several subnetworks where we can impose ionosphere-weighted constraints to improve the precision of estimates. The second step integrates subnetwork-dependent satellite clocks and biases and aligns the underlying datum. The final step updates the atmospheric delays by considering the covariances between satellite-related products and atmospheric estimates. This three-step decentralized PPP-RTK processing strategy can improve computational efficiency and ensure the high precision of all products. For numerical evaluation, we collected one-week dual-frequency global positioning system (GPS) data from 82 stations, in which 44 stations were divided into four groups for product generation and 38 stations were considered users for positioning experiments. The results show, on the network side, that the decentralized PPP-RTK generates products with the same precision as that of centralized PPP-RTK and reduces the computation time by about 50%. On the user side, the decentralized PPP-RTK products perform as well as their centralized counterparts, and the time-to-first-fix (TTFF) and three-dimensional root-mean-square (RMS) are less than 3 epochs and 1.59 cm on average, respectively. Moreover, the results verify that the decentralized PPP-RTK ensures continuous positioning when users move across subnetworks.