Integration of precise point positioning and low cost mems imu

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Abstract

Global 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.

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