Design of inertial navigation systems for marine craft with adaptive wave filtering aided by triple‐redundant sensor packages

Abstract

SUMMARYMarine craft feedback control systems typically require estimates of position, velocity and heading where the wave-induced motions should be suppressed. This paper presents a strapdown inertial navigation system with adaptive wave filtering. Wave filtering based on inertial navigation systems differ from previous vesselmodel-based designs which require knowledge of vessel parameters and mathematical models for estimation of thruster and wind forces and moments based on auxiliary sensors. The origin of the inertial navigation system error states is proven to be uniformly semiglobally exponentially stable (USGES). The wave-filtering scheme uses the estimated states of the inertial navigation system to separate the low-frequency motion of the craft from the wave-frequency motions. The observer structure also allows for estimation of the timevarying encounter frequency by using a signal-based frequency tracker or an adaptive observer. Finally, the structural properties of the triple-redundant sensors packages have been utilized to obtain optimal and robust sensor fusion with respect to sensor performance and faults.

Frequency tracking and mitigation method based on CPHD filter and adaptive multiple linear Kalman notch filter for multiple GNSS interference

“…Finally, in order to mitigate the interference signals, the frequencies obtained from the proposed CPHD filter are used to design the AMLKNF, which eliminates the multiple frequencies of GNSS interference in the received signal. The notch filter (especially, the second‐order infinite impulse response (IIR) notch filter) removes a specific frequency bandwidth and is widely used to cancel unnecessary frequencies in various fields . In order to improve tracking performance compared with the conventional notch filters, an interference frequency tracking and mitigation method using a linear Kalman notch filter (LKNF) is proposed to track and mitigate the GNSS interference signal.…”

Inertial Sensors for Risk-Based Redundancy in Dynamic Positioning

“…In addition, since specific force and angu- lar rate measurements are available, an INS can be sufficient as DP estimator, and vessel-model-based DP estimator is not necessary. This claim is supported by developments of INS-based wave filters [10], where wave filters are utilized to prevent the oscillatory wave-induced motions to be considered by the control system, [11].…”

“…While testifying the great effects and upsides the deployment of an INS may have, these references primarily suggest using one or two IMUs per position reference system for performance, and not fully integrate a redundant IMU solution in the DP system. [10] and [20] demonstrated the potential for using IMUs as a mean for fault detection and isolation in triple and dual position reference systems, and [21] for fault detection in the case of having a single position reference. Granted, INS based on MEMS might not be satisfactory as a separate position reference, as in the purported purpose of such systems.…”

Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network

“…Nonlinear observers that do not require knowledge of the vessel model have also been proposed for marine vessels operating in stationkeeping mode, often referred to as Dynamic Positioning (DP). Bryne, Fossen and Johansen performed wave filtering based on the Inertial Navigation System (INS) output [8], while Rogne et al used Inertial Measurement Unit (IMU) data for DR [9]. The difference being that the IMU provides the raw angular velocity and specific force measurements, while the INS integrates these measurements into a navigation solution in terms of a position, velocity and attitude.…”