Title: A Study on Cycle Slip Detection for Integrated Navigation of Single Frequency GNSS Receiver and Low Cost INS
Author(s): Younsil Kim, Junesol Song, Byungwoon Park, Changdon Kee
Published in: Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016)
September 12 - 16, 2016
Oregon Convention Center
Portland, Oregon
Pages: 1856 - 1884
Cite this article: Kim, Younsil, Song, Junesol, Park, Byungwoon, Kee, Changdon, "A Study on Cycle Slip Detection for Integrated Navigation of Single Frequency GNSS Receiver and Low Cost INS," Proceedings of the 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 1856-1884.
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Abstract: Cycle slip detection is one of the most important issues to be overcome when implementing a GNSS carrier phase positioning system, because cycle slip occurs very frequently whenever the carrier phase signal is weak. This results in the degradation of the vehicle's positioning accuracy. Cycle slip detection algorithms have been studied and developed for several decades. For a dual-frequency GNSS receiver, many researchers proposed cycle slip detection based on L1 and L2 carrier phase measurements. These algorithms were basically developed for dual frequencies, such that they can be applied only to a multiple-frequency receiver. Consequently, compared to a single-frequency receiver, the overall system cost would be high and therefore not cost effective. For a single-frequency GNSS receiver, the phase-code comparison, doppler integration, and differential phases of time methods can be used. However, because of the high noise level of the code measurement the phase-code comparison method can only safely handle a few cycle slips. To overcome these limitations, an inertial navigation system (INS) can be integrated with a GNSS to detect cycle slips. In this algorithm, the accuracy of the INS position estimation is the main contributor to the cycle slip detection. In turn, the accuracy of the inertial sensor is the most important contributor to the performance of an INS system. However, the accuracy of an inertial sensor is directly proportional to its cost, such that the most accurate devices are prohibitively expensive. Therefore, in this paper, we discuss how to improve the performance of the inertial-aided cycle slip detection algorithm, such that it can detect one-cycle slip, without having to increase the inertial sensor accuracy. The satellite-difference and time-difference residual between the predicted and measured carrier phases is defined as the value to be monitored for cycle slip detection. The INS position error mainly contributes to the residual and is projected to the range domain, multiplied by the satellite-difference line of sight vector. In general, the satellite having the highest elevation angle is chosen as the reference satellite for satellite-difference, with the same applying to all other satellites when obtaining satellite-difference. However, by selecting the satellite-difference satellite pair based on the satellite geometry, which minimizes the INS position error projection to the range domain, the cycle slip detection accuracy can be advanced with the same inertial sensor performance. In the proposed algorithm, the tightly coupled TDCP (Time Differenced Carrier Phase)/INS integrated navigation algorithm is used to estimate the user position. Before the TDCP measurement is updated, cycle slip detection and isolation is conducted by using the INS-predicted state variable. The cycle slip detection threshold is calculated by using the INS predicted covariance to maintain a consistent cycle slip false alarm probability. After cycle slip detection and isolation, the remaining carrier phase measurements are inserted as measurements of the TDCP/INS integrated navigation for the cycle slip detection for the next epoch. To verify the cycle slip detection performance for the proposed algorithm, a simulation and a vehicle-based experiment were conducted. Data was collected from the single-frequency GNSS receiver (GPS and GLONASS), microelectromechanical systems (MEMS) inertial measurement units (IMU) for post processing. We analyzed the cycle-slip detection performance by statistical analysis. As a result, the proposed satellite pair selection algorithm improves the cycle slip detection probability considerably.