A New Real-Time Cycle Slip Detection and Repair Method under High Ionospheric Activity for a Triple-Frequency GPS/BDS Receiver

Abstract

Cycle slip detection and repair is a prerequisite for high-precision global navigation satellite system (GNSS)-based positioning. With the modernization and development of GNSS systems, more satellites are available to transmit triple-frequency signals, which allows the introduction of additional linear combinations and provides new opportunities for cycle slip detection and repair. In this paper, we present a new real-time cycle slip detection and repair method under high ionospheric activity for undifferenced Global Positioning System (GPS)/BeiDou Navigation Satellite System (BDS) triple-frequency observations collected with a single receiver. First, three optimal linearly independent geometry-free pseudorange minus phase combinations are selected to correctly and uniquely determine the cycle slips on the original triple-frequency carrier phase observations. Then, a second-order time-difference algorithm is employed for the pseudorange minus phase combinations to mitigate the impact of between-epoch ionospheric residuals on cycle slip detection, which is especially beneficial under high ionospheric activity. The performance of the approach is verified with static GPS/BDS triple-frequency observations that are collected with a 30 s sampling interval under active ionospheric conditions, and observations are manually inserted with simulated cycle slips. The results show that the method can correctly detect and repair cycle slips at a resolution as small as 1 cycle. Moreover, kinematic data collected from car-driven and airborne experiments are also processed to verify the performance of the method. The experimental results also demonstrate that the method is effective in processing kinematic data.

Real-Time Triple-Frequency Cycle Slip Detection and Repair Algorithm Based on the Optimal Fixing Probability

“…The active state of the ionosphere can be judged by Kp index [16]. We have analyzed the Kp index during recent years retrieved from http://omniweb.gstc.nasa.gov/form/dx1.html.…”

“…This means that our algorithm performs well during the entire observation time. Figure 8 shows the comparison of our algorithm and that of Liu et al (2018). G01 observed from JFNG on March 17, 2013 are analyzed.…”

“…These five stations are all in low latitude regions which may undergo more severe ionospheric disturbance. In addition, observations from station JFNG on March 17, 2013, which are the same as in Liu et al (2018)[16], are also analyzed here to compare the performance of our algorithm with (Liu et al)'s algorithm. The elevation mask angle is set as 10 degrees.…”

Cycle Slip Detection during High Ionospheric Activities Based on Combined Triple-Frequency GNSS Signals

“…When the data epoch interval is larger than 5 s, second-order ionospheric variations estimated from the previous 10 epochs should be applied by a linear fitting model [26]. Liu et al [27] also applied the second-order ionospheric variation to predict the ionospheric delay but using less consecutive epochs. The ionospheric bias mainly affects the determination of the threshold; however, all of the previous studies did not pay attention to the determination of the threshold.…”

“…where k denotes epoch k, while the subscript (i, j, k) indicting the combined signals is omitted for the sake of simplicity. The reason for adopting Ṅ as the detection value is that the ionospheric residuals amplified by the combined signals can affect the detection of the outliers using the time-differenced ambiguities directly [27]. Although Ṅ can amplify the measurement noise, it is still precise enough to detect the outliers.…”