Dynamic dual-target VLBI correlator technology

Abstract

The dynamic dual-target very long baseline interferometry (VLBI) processing technology applied to the CVNScorr software processor is introduced. Chang’e 5 (CE-5) has achieved China’s first sample return mission from an extraterrestrial body. The characteristics of VLBI are that there are several target probes and the telemetry tracking and command (TT&C) technical requirements are high in CE-5. In the rendezvous and docking process, a real-time in-beam VLBI technology is required to perform the high-precision orbit measurement of two dynamic targets, the orbiter and the ascender. In addition, the VLBI correlator (CVNScorr) should tackle two-phase centers from two probes simultaneously. In the special power flight phases such as rendezvous and docking, near-moon braking, powered descending, and lunar takeoff, the VLBI high-precision delay model cannot be derived owing to the low accuracy of the predicted orbit. If the conventional data processing method is adopted, the VLBI fringe cannot be obtained. Therefore, the VLBI correlator should have the function of real-time dual-target fringe search and delay model reconstruction. CVNscorr adopts the principle of FX-type software correlation and has the function of dual-target correlation module, multibeacon fringe search, and delay model reconstruction. By taking advantage of the characteristics of TT&C signals from different probes, multiple beacons fringes are automatically searched and the delay values of the two targets are obtained simultaneously to reconstruct the high-precision delay models. CVNScorr uses MPI, GPU, and other technologies to realize parallel computing, and it is run on a CPU+GPU parallel cluster platform. In the CE-5 mission, the real-time processing capability is up to four stations of the Chinese VLBI Network and the postprocessing capability is up to six stations. The real-time data rate reaches 128 Mbps per station, the VLBI delay accuracy reaches 0.4 ns, and the real-time performance is better than 25 s.