Both the code–phase combination and the Geometry-Free (GF) phase combination are widely employed to detect and repair cycle slips for BeiDou Navigation Satellite System (BDS) triple-frequency observations. However, the effect of residual ionospheric delay on Narrow-Lane (NL) or GF observations must be considered to avoid incorrect cycle–slip estimation. To improve the accuracy in repairing cycle slips, a corrective ionospheric delay value predicted from the previous ionosphere sequence is used to amend the NL or GF observations at the current epoch. The main purpose of the work reported here is to evaluate the efficacy of a three-step method proposed to detect and repair cycle slip using two extra-wide-lane code–phase and one GF phase combination observations. BDS triple-frequency data were processed in two stages: separate processing of geosynchronous Earth orbit satellites, and the division of inclined geosynchronous satellite orbit and medium Earth orbit satellites into two groups for processing at 30° elevation thresholds. Results revealed that using the prediction models to correct NL or GF observations could ensure a rounding success rate of cycle slip close to 100%, even under high ionospheric activity.

Cycle slip detection for single frequency Global Navigation Satellite System (GNSS) data is currently mainly based on measurement modelling or prediction, which cannot be effectively performed for kinematic applications and it is difficult to detect or repair small cycle slips such as half-cycle slips. In this paper, a new method that is based on the total differential of ambiguity and Least-Squares Adjustment (LSA) for cycle slip detection and repair is introduced and validated. This method utilises only carrier-phase observations to build an ambiguity function. LSA is then conducted for detecting and repairing cycle slips, where the coordinate and cycle slips are obtained successively. The performance of this method is assessed through processing short and long baselines in static and kinematic modes and the impact of linearization and atmospheric errors are analysed at the same time under a controlled variable method. The results indicate this method is very effective and reliable in detecting and repairing multiple cycle slips, especially small cycle slips.

The integration of Precise Point Positioning (PPP) with Inertial Navigation Systems (INS) has been very intensively developed and widely applied in multiple areas. The integrated navigation system is able to provide high accuracy position and attitude with a single receiver. However, the cycle slip caused by high dynamics, signal lock and low satellite elevation will decrease accuracy and degrade the system performance. In this paper, an inertial aided cycle slip detection and repair method is applied in PPP/INS tightly coupled navigation to obtain higher accuracy navigation information. The inertial information is introduced to the wide-lane combination observation to avoid the noise and multipath from pseudorange. Detail error analysis is given to determine the critical value of INS position accuracy which makes inertial aided wide-lane combination have better performance and a new decision variable is constructed. The inertial aided cycle slip detection and repair scheme that replaces the ambiguity re-initialisation is applied in PPP. An experiment was performed to validate the new algorithm. The results indicate that the inertial aided decision variable has higher accuracy than the traditional Melbourne-Wübbena decision variable. The inertial aided scheme can efficiently detect and repair the small cycle slip (from 1 to 6) and large cycle slip (from 10 to 20). The inertial-aided cycle slip detection method introduced in PPP resolution will remove the error by ambiguity re-initialisation.

This paper describes the verification of a real-time attitude determination algorithm during GPS attitude receiver hardware development. The GPS attitude receiver of 24 channels had been already developed in Surrey University. However 24 channels were not enough for practical usage. For this reason, a 48-channel attitude receiver with 12 channels for each antenna has been developed. To estimate attitude in real time, precise relative positions of the GPS antenna array have to be determined as rapidly as possible. However, the calculation load based on the conventional algorithm is too burdensome to perform using the RISC microprocessor. Therefore, in this paper, the cycle ambiguities of each base vector are resolved using SNUGLAD (Seoul Nat Univ GNSS Lab Attitude Determination), the design focus of which is to allow the receiver to estimate the 10 Hz onboard solutions. To keep precise solutions continuously, after ambiguity removal, cycle slip must be detected or isolated. Otherwise, the receiver would output erroneous solutions after a short signal blockage or fading of the GPS signal. To prevent this, we defined the cycle slip detection and repair scheme using a standard extended Kalman filter, which can detect and repair cycle slip within one cycle. As a result, this paper shows that time synchronized measurement with good quality and a reliable solution can be provided by the hardware developed with inexpensive chipsets and that this may be a possible cost efficient sensor for UAV or microsatellites.

To ensure high accuracy results from an integrated GPS/INS system, the carrier phase observables have to be used to update the filter's states. As a prerequisite the integer ambiguities must be resolved before using carrier phase measurements. However, a cycle slip that remains undetected (and uncorrected) will significantly degrade the filter's performance. In this paper, an algorithm that can effectively detect and identify any type of cycle slip is presented. The algorithm uses additional information provided by the INS, and applies a statistical technique known as the cumulative-sum (CUSUM) test. In this approach, cycle slip decision values can be computed from the INS-predicted position (due to the fact that its short-term accuracy is very high), and the CUSUM test used to detect cycle slips (as it is very sensitive to abrupt changes of mean values). Test results are presented to demonstrate the effectiveness of the proposed algorithm.