Abstract:

When performing very long baseline interferometry using weak signals in deep space exploration or high-dynamic arcs of detectors, a high-precision interferometry time delay model is required. A theoretical analysis of the impact of the time delay rate model on correlation processing was conducted, whose results showed that the longer the integration period, the higher the accuracy requirement for the time delay rate model. Based on the initial time delay model, a high-precision time delay rate model refinement method based on multi-integration period cross-spectral phase least squares processing was proposed. The least squares calculation was performed on the cross-spectral phases of multiple integration periods to obtain the residual time delay rate and correct the initial time delay rate model; further, an evaluation method for the accuracy of the time delay rate model was presented. Monte Carlo simulations and measured data from China deep space Network were used to process and verify both radio source signals and detector signals. The results show that after the correction of the time delay rate model, the accuracy of time delay rate model is better than 0.2 ps/s, the residual delay estimation accuracy of the radio source is improved by up to approximately 56%, and the residual time delay accuracy is improved by nearly two orders of magnitude in scenarios where the detector's predicted ephemeris is inaccurate.The proposed method is conducive to improving the interferometric measurement accuracy of weak signals in deep space exploration and high-dynamic arcs of detectors, and has certain reference significance for subsequent data processing of deep space exploration.

Key words: deep space interferometry, weak signal, delay rate model, distributed variance, optimal integration period