Cycle slip detection during high ionospheric activities based on combined triple-frequency GNSS signals

Dongsheng Zhao, Craig M. Hancock, Gethin Wyn Roberts, Shuanggen Jin

Research output: Journal PublicationArticlepeer-review

13 Citations (Scopus)
24 Downloads (Pure)

Abstract

The current cycle slip detection methods of Global Navigation Satellite System (GNSS) were mostly proposed on the basis of assuming the ionospheric delay varying smoothly over time. However, these methods can be invalid during active ionospheric periods, e.g., high Kp index value and scintillations, due to the significant increase of the ionospheric delay. In order to detect cycle slips during high ionospheric activities successfully, this paper proposes a method based on two modified Hatch–Melbourne–W¨ubbena combinations. The measurement noise in the Hatch–Melbourne–W¨ubbena combination is minimized by employing the optimally selected combined signals, while the ionospheric delay is detrended using a smoothing technique. The difference between the time-differenced ambiguity of the combined signal and this estimated ionospheric trend is adopted as the detection value, which can be free from ionospheric effect and hold the high precision of the combined signal. Five threshold determination methods are proposed and compared to decide the cycle slip from the magnitude aspect. This proposed method is tested with triple-frequency Global Navigation Satellite System observations collected under high ionospheric activities. Results show that the proposed method can correctly detect and fix cycle slips under disturbed ionosphere.
Original languageEnglish
Pages (from-to)250/1-250/20
JournalRemote Sensing
Volume11
Issue number3
DOIs
Publication statusPublished - 26 Jan 2019

Keywords

  • GNSS ionospheric bias mitigation
  • HMW combination
  • combined signals
  • cycle slip

Fingerprint

Dive into the research topics of 'Cycle slip detection during high ionospheric activities based on combined triple-frequency GNSS signals'. Together they form a unique fingerprint.

Cite this