When sensing Earth's ionosphere using multiple Global Navigation Satellite Systems (GNSSs), special care needs to be taken with the receiver differential code bias (DCB) contributions to the error budget. We propose a method that is able to time-wisely retrieve the Between-Receiver DCBs (BR-DCBs) from code measurements collected by a zero-baseline setup, thereby eliminating most common error sources. We base our investigations on dual-frequency GPS (L1 + L2), BeiDou (B1 + B2), and Galileo (E1 + E5a) measurements collected in 2013 with a 30 second sampling rate by four multi-GNSS receivers of three types connected to one common antenna. For each receiver-pair, we determine the time-wise estimates of GPS/GEO/IGSO/MEO/Galileo BR-DCBs from the corresponding code measurements. We confirm that (1) the time-wise estimates of BR-DCBs for all tested receiver-pairs exhibit good intra-day stability and (2) the daily weighted average (DWA) estimates of GEO/IGSO/MEO BR-DCBs are inconsistent for receiver-pairs of mixed type, due to the presence of BeiDou code inter-satellite-type biases (ISTBs). We also identify likely factors accounting for variability in DWA estimates of BR-DCBs over a one-year interval.

An ongoing research to represent the human body with mathematical models in different methods is described. 3D anthropometric data systems can be used in the product design process and other applications. Neural networks can be used to approximate functions which were proved by rigid mathematical theory. It was analyzed that neural networks can be used to research 3D scanned human body surface.