Adaptive robust ultra‐tightly coupled global navigation satellite system/inertial navigation system based on global positioning system/BeiDou vector tracking loops

Abstract

With the development of global navigation satellite system (GNSS), the GNSS/inertial navigation system (INS) integrated system offers the users better positioning or navigation performance. This paper proposes an adaptive robust ultratightly coupled GNSS/INS system based on a novel vector tracking strategy for combining both global positioning system (GPS) L1 and BeiDou B1 signals' tracking together. The inherent mechanism of the vector tracking approach has been analysed to describe the relationship between the replica signals and user's dynamic state. Then, an adaptive robust filter is used to gain the accurate estimates of vehicle states when the vehicle is under a weak-signal or large manoeuvring environment. Finally, the experimental platform is set up using a GPS/BeiDou signal simulator and an inertial measurement unit simulator and the test results show that the proposed ultra-tightly coupled system can keep the tracking loops from the high dynamic perturbations, which saves the cost time of signal reacquisition. Moreover, the presented adaptive robust ultratightly coupled system can obtain a higher accuracy than Kalman filtering in a simultaneous weak-signal and large manoeuvring environment.

Fault Identification Ability of a Robust Deeply Integrated GNSS/INS System Assisted by Convolutional Neural Networks

“…It is derived by applying the maximum likelihood estimation to resist the outlier effect of measurement vector, and its function is realized by adjusting the covariance matrix of measurement noise with expansion factors [19]. The Huber weight function that is commonly used outputs the reciprocal of normalized residual as an expansion factor when the residual value is larger than the preset threshold [20,21]. However, its performance is restricted by fixed parameter value and limited parameter range.…”

Efficient BeiDou DBZP‐based weak signal acquisition scheme for software‐defined receiver

“…The information can include those from reference station, sensors such as IMU and so on [10, 11]. However, the aided approach increases the complexity, weight, cost and power consumption of the user system [12]. The unaided approach is to detect the weak signal without any external equipment or assisted information and completes the acquisition with receiver algorithm like coherent or non‐coherent integration, which makes the acquisition more autonomous and independent.…”

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