A New In-Flight Alignment Method with an Application to the Low-Cost SINS/GPS Integrated Navigation System

Abstract

The optimization-based alignment (OBA) methods, which are implemented by the optimal attitude estimation using vector observations—also called double-vectors—have proven to be effective at solving the in-flight alignment (IFA) problem. However, the traditional OBA methods are not applicable for the low-cost strap-down inertial navigation system (SINS) since the error of double-vectors will be accumulated over time due to the substantial drift of micro-electronic- mechanical system (MEMS) gyroscope. Moreover, the existing optimal estimation method is subject to a large computation burden, which results in a low alignment speed. To address these issues, in this article we propose a new fast IFA method based on modified double-vectors construction and the gradient descent method. To be specific, the modified construction method is implemented by reducing the integration interval and identifying the gyroscope bias during the construction procedure, which improves the accuracy of double-vectors and IFA; the gradient descent scheme is adopted to estimate the optimal attitude of alignment without complex matrix operation, which results in the improvement of alignment speed. The effect of different sizes of mini-batch on the performance of the gradient descent method is also discussed. Extensive simulations and vehicle experiments demonstrate that the proposed method has better accuracy and faster alignment speed than the related traditional methods for the low-cost SINS/global positioning system (GPS) integrated navigation system

Phased Array Radio Navigation System on UAVs: GNSS-based Calibration in the Field

“…The Kalman filer (KF) is widely used in the initial alignment [13] with the information from an external sensor device such as GNSS [14], odometer [15] and Doppler velocity log (DVL) [16]. Optimisation-based initial alignment is also suggested as obtaining a roughly known initial estimate required for KF is hard for an inmotion vehicle [17], [18]. However, as we are aiming to run the calibration algorithm online in parallel the system operation, and the PARS ground radio antenna orientation can be roughly estimated using a compass [6], and with more practical treatment of noise, Kalman filter is suitable for the antenna orientation calibration.…”

High-Altitude Balloon-Based Sensor System Design and Implementation

“…The inertial navigation sensor (INS) designed in this paper can provide both orientation and navigation data, which includes an IMU and runs an onboard enhanced Extended Kalman Filter (EKF). The use of Global Navigation Satellite System(GNSS) data or other aiding equipment such as odometer or internal barometric sensor can be used to provide accurate navigation data, but also to improve orientation accuracy [12]. The design block of the INS system, is shown in Figure 2; it includes IMU, data fusion unit and data formatting and output unit.…”

Bionic Integrated Positioning Mechanism Based on Bioinspired Polarization Compass and Inertial Navigation System

“…Real-time autonomous positioning is essential for long endurance vehicles, especially in unknown and complex environments [ 1 ]. Currently, the global navigation satellite system (GNSS), visual navigation system (VNS), and inertial navigation system (INS) are the commonly used positioning methods [ 2 , 3 ]. However, the GNSS positioning performance could deteriorate when GNSS signals suffer from electromagnetic interference.…”