Browsing by Author "Du, Shuang"
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- ItemOpen AccessIntegration of precise point positioning and low cost mems imu(2010) Du, Shuang; Gao, YangGlobal Positioning System (GPS) and low cost Inertial Navigation System (INS) integrated systems are expected to become more widespread as a result of the availability of low cost inertial Micro-Electro-Mechanical Sensors (MEMS). This integrated system has been widely and successfully applied in many applications, such as vehicle navigation and mobile mapping system. Currently most of the GPS/INS integrated systems are based on the differential GPS (DGPS) to ensure the navigation performance. However the requirement on a base station is usually problematic as it limits the operational range of the system and also increases the system cost and complexity. To tackle this issue, a method to integrate the data from a single GPS receiver and a low cost MEMS Inertial Measurement Unit (IMU) for autonomous positioning and attitude determination is developed in this thesis. The GPS and IMU data will be fused based on the Precise Point Positioning (PPP) technology, which is able to provide centimetre to decimetre positioning accuracy by using a single dual-frequency receiver and is therefore employed to ensure the navigation performance. Previous work has demonstrated that the integration of PPP GPS and tactical grade IMU is able to provide navigation solution with accuracy at centimetre to decimetre for position and centimetre per second for velocity. However, due to the expensive cost of the tactical grade IMU, it is not suitable for the commercial applications. The motivation of this research is to investigate the integration of PPP GPS and low cost MEMS IMU for precise positioning and attitude determination. Both loose and tight integration of PPP GPS and MEMS IMU are studied and loosely and tightly coupled Kalman filters are developed to derive the optimal navigation solutions. The primary observable used in PPP GPS is the carrier phase measurement, and it is well known that the undetected cycle slips deteriorate its high precision nature and eventually degrade the overall system performance. An algorithm of inertial aided cycle slip detection and identification is also investigated in this thesis. Two van tests are conducted to evaluate the performance of the developed integrated PPP GPS/MEMS IMU system. The performance analysis is carried out based the position, velocity and attitude errors. A loosely coupled DGPS/tactical grade IMU system is used to provide the reference solution.
- ItemOpen AccessRotary Inertial Navigation System with a Low-cost MEMS IMU and Its Integration with GNSS(2015-06-09) Du, Shuang; Gao, YangMicro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors, such as noises, biases, scale factors, and installation errors. Consequently, the navigation errors of a low-cost inertial system with the MEMS IMU will accumulate quickly over time in stand-alone mode. Methods that can effectively mitigate the navigation errors without a need for external aiding, will be of great value for many applications. This research proposed a rotary inertial navigation system (INS) to mitigate navigation errors caused by MEMS inertial sensor errors when external aiding information is not available. A rotary INS is an inertial navigator in which the IMU is installed on a rotation platform. Application of proper rotation schemes can effectively cancel and reduce sensor errors. For example, the rotation of an IMU with a constant angular rate can modulate the constant inertial bias into periodic signals, and an integration of the modulated inertial data over a complete rotation cycle can eliminate the effect of the bias on the navigation solutions. Improvement of current inertial system’s observability in the absence of system maneuvers is also highly desired in applications. It is well known that the position and velocity from external aiding are extensively used to estimate the INS errors, and the weak maneuvers result in poor system observability and eventually degrade the navigation performance due to inaccurate estimation of INS errors. As the rotation changes the position of the IMU, the system observability is significantly improved in a rotary inertial system. Although the rotary INS has been applied to inertial system with high-end IMUs, it has not been investigated for low-cost MEMS IMUs. Given the fact that the MEMS IMU features significant sensor errors, as well as large and fast error variations, there are many issues and challenges that need to be addressed for effective navigation error mitigation and applications by rotary INS with MEMS IMUs. The conducted turntable tests and kinematic field tests indicate that with proper data processing, the horizontal position errors can be reduced by about 2~5 times in an inertial system with a rotating low-cost MEMS IMU, compared to those errors in a non-rotating system. Moreover, the observability of the roll and pitch errors, the accelerometer biases in the horizontal axes, and the gyro bias in the vertical direction can be significantly improved by IMU rotations.