The diverse operating environments change GNSS measurement noise covariance in real time, and different GNSS techniques hold different measurement noise covariance as well. Mismodelling the covariance causes undependable filtering results and even degenerates the GNSS/INS Particle Filter (PF) process, due to the fact that INS error-state noise covariance is much smaller than that of GNSS measurement noise. It also makes the majority of existing methods for adaptively adjusting filter parameters incapable of performing well. In this paper, a feasible Digital Track Map-aided (DTM-aided) adaptive extended Kalman particle filter method is introduced in GNSS/INS integration in order to adjust GNSS measurement noise covariance in real time, and the GNSS down-direction offset is also estimated along with every sampling period through making full use of DTM information. The proposed approach is successfully examined in a railway environment, and the on-site experimental results reveal that the adaptive approach holds better positioning performance in comparison to the methods without adaptive adjustment. Improvements of 62.4% and 14.9% in positioning accuracy are obtained in contrast to Standard Point Positioning (SPP) and Precise Point Positioning (PPP), respectively. The proposed adaptive method takes advantage of DTM information and is able to automatically adapt to complex railway environments and different GNSS techniques.
To facilitate 5G-based positioning applications, Release 16 of the 3GPP 5G standard has defined the Positioning Reference Signal (PRS), which can be used to measure Time of Arrival (TOA) for downlink positioning. However, Orthogonal Frequency Division Multiplexing (OFDM) signals are sensitive and vulnerable to synchronization errors. Moreover, the highly configurable 5G PRS in Release 16 calls for a unique allocation pattern on the subcarriers. Existing timing recovery methods that have been employed for reference signals, which are evenly inserted in the subcarrier symbols, may not perform well. To solve the timing recovery issue of the OFDM signal through 5G standard-compliant PRS, we propose a three-stage timing recovery scheme. We use the 5G PRS as pilot symbols to estimate the path time delay and complete receiver sampling clock synchronization. We propose a generalized path time delay estimation method that can correct timing errors larger than one sample. In addition, we incorporate a delay-locked loop (DLL) that can track the PRS code-phase when the phase errors are within one sample, which showcases the precise positioning possible with a standard-compliant 5G New Radio (NR) signal.
IEC 61508-2010 puts special limits on the on-chip redundancy of one single chip, for example the safety integrity level (SIL) is limited up to SIL 3. About this, however, there are no specific explanations. Based on the safety-critical system of on-chip redundancy for a typical programmable logic device (FPGA), this paper proves that the highest SIL is 3; analyses the factors that may impact the safety integrity of redundancy system, and furthermore, provides reasonable solutions. The results show that the use of 1oo2 channel redundancy scheme can effectively improve the safety integrity level of the on-chip redundancy.
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