Benefits of motion constraining for robust, low-cost, dual-frequency GNSS PPP + MEMS IMU navigation

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Low-cost sensor navigation is growing in demand for next-generation, mass-market applications such as low-cost automation, smartphones, UAVs and others. Precise Point Positioning (PPP) is a Global Navigation Satellite System (GNSS) measurement processing technique in which wide-area-based satellite corrections are applied without the need for local infrastructure to attain kinematic accuracies at the dm- to cm-level. The most significant advantage of the PPP technique is that it does not require a local reference station for GNSS error calibration. GNSS PPP and inertial measurement unit (IMU) integration work is a relatively recent advancement in the area of precision navigation. In the past, high-precision GNSS receivers augmented with PPP processing were integrated with highperformance micro-electromechanical system (MEMS) IMUs. Later, single-frequency (SF) GNSS PPP + MEMS IMUs were explored. Recently, there has been the emergence of mass-market, low-cost, dual-frequency (DF) GNSS receivers. Integrating a low-cost DF GNSS receiver with low-cost MEMS IMU performs with decimetre-level accuracy even in an obstructed environment when there are only three or four satellites available. In this research work, the performance of tightly-coupled DF GNSS PPP and MEMS IMU is assessed when constraints are applied. Past research work in this area that examined constraining in detail did not involve PPP augmentation and the work that involved PPP augmentation does not explain and quantify impact constraining makes on the accuracy or continuity of the estimation/solution explicitly. In this work, vehicle constraints including zero velocity update (ZVU), zero angular rate update (ZARU), and height constraining are applied to assess any improvements they offer to the solution when GNSS-PPP is integrated with a low-cost MEMS IMU. Calibrating an IMU in a timely manner is required because of the nature of an IMU to drift with time in the absence of GNSS signals for calibration. When ZVU, ZARU, and height constraints are applied, the algorithm performs at the decimetre-level accuracy, as opposed to metre level accuracy with no constraining using the low-cost hardware during a partial GNSS signal outage. The research contribution through this work is the quantitative analysis of benefits attained from a unique combination of low-cost DF GNSS PPP and IMU integrated algorithm with dynamic constraints, which has not been analysed/quantified in previous works. The constraints make a significant positive impact on the algorithm in the absence of GNSS signals by improving the position and velocity solution by 85-90%. Next-generation applications such as low-cost robotics, low-cost autonomous vehicles, etc. that demand decimetre-level accuracy continuously can be potentially satisfied by a DF GNSS PPP + MEMS IMU solution once constraining is imposed.