Real-time Cycle-slip Detection and Correction for Land Vehicle Navigation using Inertial Aiding

Abstract

Processing GPS carrier-phase measurements can provide high positioning accuracy for several navigation applications. However, if not detected, cycle slips in the measured phase can strongly deteriorate the positioning accuracy. Cycle slips frequently occur in areas surrounded by trees, buildings, and other obstacles. The dynamics experienced by the GPS receiver in kinematic mode of navigation also increases the possibility of cycle slips. Detection and correction of these cycle-slips is essential for reliable navigation. One way of detecting and correcting for cycle slips is to use another system to be integrated with GPS. Inertial Navigation Systems (INS), using three-axis accelerometers and three-axis gyroscopes, is integrated with GPS to provide more reliable navigation solution. Moreover, INS was utilized in the past for GPS cycle slip detection and correction. For low cost applications, Micro-Electro-Mechanical-Systems (MEMS) accelerometers and gyroscopes are used inside INS. For land navigation, reduced inertial sensor system (RISS) utilizing two accelerometers, one gyroscope, and the vehicle odometer was suggested. MEMS-based RISS has the advantage of using less number of MEMS-based gyroscopes and accelerometers thus reducing the overall cost and avoiding the complex error characteristics associated with MEMS sensors. In this thesis, we investigate the use of MEMS – based RISS to aid GPS and detect and correct for cycle slips. The Kalman filter was employed in centralized fashion to integrate the measurements from both GPS and RISS. This thesis research also offers a new threshold selection criterion resulting in a more robust cycle slip detection and correction. The proposed method was tested in different scenarios of road tests in land vehicle. Results show accuracy iii improvement over the conventional double differenced pseudoranges-based integrated system. Moreover, the adaptive selection criterion of the detection threshold proposed in this thesis improves the detection rate, especially in the case of small-sized cycle slips.