In-flight Alignment Research Articles

Applied Quaternion Optimization Method in Transfer Alignment for Airborne AHRS Under Large Misalignment Angle

The airborne attitude and heading reference system (AHRS) is an inertial system that provides the aircraft with navigation parameters in real time. A new coarse transfer alignment method is proposed for low-accuracy AHRS with a large misalignment angle between AHRS and master inertial navigation system (MINS). The new coarse alignment method is derived from the quaternion-optimization-based in-flight alignment (IFA) method. By resolving the alignment problem in body frame, the proposed method makes full use of the navigation information of MINS and transforms the alignment problem into a quaternion optimization problem. Its accuracy is improved by presenting a two-step iterative algorithm. Compared with the quaternion-optimization-based IFA method, the proposed method is more robust and accurate by introducing the attitude information of MINS. The simulation and experiment results show that the proposed method is applicable to both large and small misalignment angles, and it serves as a nice coarse alignment that permits the implementation of linear error model in fine alignment process.

High-degree Cubature Kalman Filtering Approach for GPS Aided In-Flight Alignment of SDINS

High-degree Cubature Kalman Filtering Approach for GPS Aided In-Flight Alignment of SDINS

In-Flight Alignment of POS Based on State-Transition Matrix

Position and orientation system (POS) is an important part of airborne remote sensing system, it is used to measure and compensate the motion errors of airborne sensors in course of imaging. In-flight alignment is an effective way to improve the accuracy and robustness of POS in its operating cycles. In the traditional in-flight alignment methods, large initial alignment errors result in the fact that nonlinear error models and nonlinear filters must be used, which means much calculation load will accompany the system. To avoid the large initial alignment errors, in this paper, a new in-flight alignment method with fewer calculation loads is proposed. The error propagate characteristic of POS is analyzed first, and state transition matrix is used to record the initial alignment errors propagate process in every calculation step. After observability analysis of the new method, the in-flight alignment is carried out according to the navigation errors and the error state-transition matrix of POS. To validate the proposed in-flight alignment method, car-mounted experiment and flight test are carried out. Experiment results show that, the proposed in-flight alignment method can improve the accuracy and the robustness of POS with fewer calculation loads.

In-Flight Self-Alignment Method Aided by Geomagnetism for Moving Basement of Guided Munitions

Due to power-after-launch mode of guided munitions of high rolling speed, initial attitude of munitions cannot be determined accurately, and this makes it difficult for navigation and control system to work effectively and validly. An in-flight self-alignment method aided by geomagnetism that includes a fast in-flight coarse alignment method and an in-flight alignment model based on Kalman theory is proposed in this paper. Firstly a fast in-flight coarse alignment method is developed by using gyros, magnetic sensors, and trajectory angles. Then, an in-flight alignment model is derived by investigation of the measurement errors and attitude errors, which regards attitude errors as state variables and geomagnetic components in navigation frame as observed variables. Finally, fight data of a spinning projectile is used to verify the performance of the in-flight self-alignment method. The satisfying results show that (1) the precision of coarse alignment can attain below 5°; (2) the attitude errors by in-flight alignment model converge to 24′ at early of the latter half of the flight; (3) the in-flight alignment model based on Kalman theory has better adaptability, and show satisfying performance.

Carrier Aircraft Urgent Takeoff In-Flight Alignment Extended Set-Membership Estimation

This paper considers the nolinear system robust estimation problem with measurement time delay. The purpose is to provide algorithm for inertial navigation system nonlinear error model in transmittion delay case. Considering that innovation regroup method can treat the measurement delay problem better with no addition of system state dimension, and decrease the system computation, therefore, that algorithm is combined with extended set-membership estimation and deduce the distrete nonlinear system extended set-membership estimation algorithm with measurement delay, realize nonlinear system varying state estimation and the treatment of measurement delay. At last, apply the algorithm to carrier aircraft in-flight alignment and validate the effecitiveness.

큰 초기 자세 오차를 가진 관성항법장치의 운항중 정렬을 위한 비선형 필터 연구

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

In-Flight Alignment UsingH∞Filter for Strapdown INS on Aircraft

In-flight alignment is an effective way to improve the accuracy and speed of initial alignment for strapdown inertial navigation system (INS). During the aircraft flight, strapdown INS alignment was disturbed by lineal and angular movements of the aircraft. To deal with the disturbances in dynamic initial alignment, a novel alignment method for SINS is investigated in this paper. In this method, an initial alignment error model of SINS in the inertial frame is established. The observability of the system is discussed by piece-wise constant system (PWCS) theory and observable degree is computed by the singular value decomposition (SVD) theory. It is demonstrated that the system is completely observable, and all the system state parameters can be estimated by optimal filter. Then a H ∞ filter was designed to resolve the uncertainty of measurement noise. The simulation results demonstrate that the proposed algorithm can reach a better accuracy under the dynamic disturbance condition.

Adaptive Redundant Inertial Measurement Unit/Global Positioning System Integration Filter Structure for Fault Tolerant Navigation

This paper proposes a new adaptive filter structure containing two subfilters, a fault detection and isolation (FDI) filter, and a main-filter for redundant inertial measurement unit (RIMU)/global positioning system (GPS) integrated navigation system tolerant toward faults of inertial sensors. The purpose of subfilters is compensation of sensor level bias (SLB) of the RIMU during in-flight alignment for successful FDI processing. Also, that of the main-filter is providing of error compensated navigation solution based on the good FDI result. To achieve these purposes, two coordinate frames, sub-body frame (SBF) and master-body frame (MBF), are defined first. Then, two different error models for the RIMU are formulated in the SBF for sensor level compensation and in the MBF for module level compensation, respectively. Based on the formulated error models, an adaptive filter structure is designed. Some numerical simulations are performed to validate the performance of the proposed adaptive filter structure.

In-flight alignment of the optical-electronic system of a spacecraft

The problem of refining the parameters of the mutual attitude of the onboard camera and the star tracker installed on a spacecraft is considered. A distinctive feature of the problem statement and solution is that the refinement is based on observations of landmarks that are not geodetically referenced.

An In-Flight Emergency Alignment Scheme for Aircraft MINS with Assistant of Airborne SAR

The alignment of a strapdown inertial navagation system (SDINS) is the process whereby the orientation of body frame is determined with respect to the navigation frame [. In a broad sense, alignment of SDINS can be classified as initial alignment and in-flight alignment (IFA). The IFA is performed with IMU and external sensors during the vehicle flight [2,, in which the primary assistant sources are satellite system, radar, or other airborne equipment, offering reference signals like position, velocity, or attitude to assist the alignment process [4,. However, these sources have disadvantages in redundancy, independence, and stability, which will be incipient faults in emergency take-off or warfare. So it is necessary for us to analyse the subsidiary airborne equipments and design new in-flight alignment scheme.

In-flight alignment of a strapdown inertial navigation system of an unmanned aerial vehicle

The alignment system of a strapdown inertial navigation system for an unmanned aerial vehicle installed on a carrier aircraft is studied. The aim is to develop alignment techniques for the strapdown inertial navigation system that improve the accuracy of alignment and reduce the alignment time. A technique for constructing the initial alignment system for a strapdown inertial navigation system of an unmanned aerial vehicle is proposed.

Quaternion-Optimization-Based In-Flight Alignment Approach for Airborne POS

Position and Orientation System (POS) is a key technology that provides motion compensation information for imaging sensor in airborne remote sensing. In-flight alignment (IFA) is an important alignment method that can improve reaction speed and accuracy of measurement for airborne POS. The traditional IFA methods based on the Kalman filter and the adaptive extended Kalman filter (AEKF) are severely affected by flight maneuver; severe maneuver may result in alignment accuracy degeneration or failure. On the basis of optimization-based alignment method for static base alignment, a novel IFA method based on quaternion optimization is devised in this paper, aiming to boost up the robustness and the accuracy of IFA, which extends the range of the application of optimization-based alignment method from static base alignment to IFA. The proposed algorithm has the advantage that it can avoid the affection from severe maneuver. The real-time implementation is given. Flight experiment demonstrates that, compared with the IFA method based on AEKF, the proposed algorithm is better in converging speed and robusticity with the same alignment accuracy.

In-Flight Alignment Algorithm Based on ADD2 for Airborne POS

The Position and Orientation System (POS) is a special Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS) integrated system, widely employed in airborne remote sensing. In-Flight Alignment (IFA) is an effective way to improve the accuracy and speed of initial alignment for an airborne POS. IFA is normally accomplished with references from the position and velocity of GPS for SINS, so that unstable GPS measurements will result in poor alignment accuracy. To improve alignment accuracy under unstable GPS conditions, an adaptive filtering algorithm of the Second-order Divided Difference filter (DD2) based on adaptive innovation estimation is proposed, which introduces calculated innovation covariance directly into computation of the filter gain matrix. Then, the adaptive DD2 algorithm is used for the IFA of the POS with a large initial heading error. To validate the proposed algorithm, simulations are undertaken, followed by IFA experiments for the prototype of the airborne POS (TX-F30) under a turning manoeuvre in a car-mounted experiment, and under an “8” manoeuvre in-flight. The simulations and experimental results show that the proposed algorithm can reach better alignment accuracy under unknown statistical characteristic of GPS measurement noises.

Velocity/Position Integration Formula Part I: Application to In-Flight Coarse Alignment

The in-flight alignment is a critical stage for airborne INS/GPS applications. The alignment task is usually carried out by the Kalman filtering technique that necessitates a good initial attitude to obtain satisfying performance. Due to the airborne dynamics, the in-flight alignment is much difficult than alignment on the ground. This paper proposes an optimization-based coarse alignment approach using GPS position/velocity as input, founded on the newly-derived velocity/position integration formulae. Simulation and flight test results show that, with the GPS lever arm well handled, it is potentially able to yield the initial heading up to one degree accuracy in ten seconds. It can serve as a nice coarse in-flight alignment without any prior attitude information for the subsequent fine Kalman alignment. The approach can also be applied to other applications that require aligning the INS on the run.

Study on Innovation Adaptive EKF for In-Flight Alignment of Airborne POS

The Position and Orientation measurement System (POS) is a dedicated Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS) integrated system for airborne remote sensing. In-flight alignment (IFA) is an effective way to improve the accuracy and speed of initial alignment for an airborne POS. During IFA, the GPS provides the position and velocity references for the SINS, so the alignment accuracy will be degraded by unstable GPS measurements. To improve the alignment accuracy under unstable GPS measurement, an adaptive filtering algorithm of an extended Kalman filter (EKF) combined with innovation-based adaptive estimation is proposed, which introduces the calculated innovation covariance into the computation of the filter gain matrix directly. Then, this innovation adaptive EKF algorithm is used for the IFA of the POS with a large initial heading error. Moreover, it is optimized by blocked matrix multiplication to reduce the computational burden and improve the real-time performance. To validate the proposed algorithm, the car-mounted IFA experiment is carried out for the prototype of the airborne POS (TX-D10) under a turning maneuver, taking Applanix's POS/AV510 as a reference and changing the GPS measurement artificially. The experiment results demonstrate that the proposed algorithm can reach a better alignment accuracy than the EKF under unknown GPS measurement noises.

Non-symmetric unscented transformation with application to in-flight alignment

To overcome the extended Kalman Filter (EKF) limitation, the unscented transformation (UT) was developed as a method to propagate mean and covariance information through nonlinear transformation. However, the ordinary UT has both local and global sampling problems. In this paper, non-symmetric unscented transformation (NSUT) is proposed to solve these problems. The sigma point sets of the NSUT are non-symmetrically located with respect to the zeroth sigma point set which is equal to the prior mean. Then, the weights of the sigma points are derived by using some conditions for mean and covariance. The non-symmetric unscented Kalman filter (NSUKF) based on the sigma points and weights of the NSUT are applied to the in-flight alignment (IFA) with a large heading error. With a low cost MEMS IMU, the simulations are carried out at an S-type trajectory to analyze the performance of the proposed method.

A Localization and In-flight Alignment Protocol for Airborne SINS Based on Flight-vehicle Wireless Sensor Networks

The necessity recurrently comes to align a strapdown inertial navigation system (SINS) in a moving vehicle to guarantee the accuracy and efficiency in the long run-off of the inertial system after a take-off or launch command is issued. This in-flight alignment is therefore achieved by integrating SINS data with some external aiding source inlcluding airborne navigation equipments and networking sensors. In this paper, a localization architecture and alignment scheme is presented for aircraft in a three-demensional fleet network, which is based on wireless sensor network. Firstly, a 3D node localization scheme is designed based on weighed-multidimensional scaling, which adopt spherical locating in the initial stage, and adaptively choose source nodes with high relative reliability to achieve position update. Then a robust filter algorithm is applied to compensate time-varying delay error and large azimuth uncertainty in alignment. Extensive simulation shows that the DMDG-3D localization scheme can provide highly accurate and relatively reliable navigation information in real time, and filter algorithm can accelerate convergence and give better estimation of the navigation parameters. ∞ − l l2

Feedforward ins aiding: an investigation of maneuvers for in-flight alignment

Navigation in autonomous vehicles involves integrating measurements from on-board inertial sensors and external data collected by various sensors. In this paper, the computer-frame velocity error model is augmented with a random constant model of accelerometer bias and rate-gyro drift for use in a Kalman filter-based fusion of a low-cost rotating inertial navigation system (INS) with external position and velocity measurements. The impact of model mismatch and maneuvers on the estimation of misalignment and inertial measurement unit (IMU) error is investigated. Previously, the literature focused on analyzing the stripped observability matrix that results from applying piece-wise constant acceleration segments to a stabilized, gimbaled INS to determine the accuracy of misalignment, accelerometer bias, and rate-gyro drift estimation. However, its validation via covariance analysis neglected model mismatch. Here, a vertically undamped, three channel INS with a rotating IMU with respect to the host vehicle is simulated. Such IMU rotation does not require the accurate mechanism of a gimbaled INS (GINS) and obviates the need to maneuver away from the desired trajectory during in-flight alignment (IFA) with a strapdown IMU. In comparison with a stationary GINS at a known location, IMU rotation enhances estimation of accelerometer bias, and partially improves estimation of rate-gyro drift and misalignment. Finally, combining IMU rotation with distinct acceleration segments yields full observability, thus significantly enhancing estimation of rate-gyro drift and misalignment.

SUNRISE: High resolution UV/VIS observations of the sun from the stratosphere

SUNRISE is an international project for the development, construction and operation of a balloon-borne solar telescope with an aperture of 1 m, working in the UV/VIS spectral domain. The main scientific goal of SUNRISE is to understand the structure and dynamics of the magnetic field in the atmosphere of the Sun. SUNRISE will provide near diffraction-limited images of the photosphere and chromosphere with an unprecedented resolution down to 35 km on the solar surface at wavelengths around 220 nm. Active in-flight alignment and image stabilization techniques are used. The focal-plane instrumentation consists of a polarization sensitive spectrograph, a Fabry–Perot filter magnetograph and a phase-diverse filter imager working in the near UV. The first stratospheric long-duration balloon flight of SUNRISE is planned in summer 2009 from the Swedish ESRANGE station. SUNRISE is a joint project of the German Max-Planck-Institut für Sonnensystemforschung (MPS), Katlenburg-Lindau, with the Kiepenheuer-Institut für Sonnenphysik (KIS), Freiburg, Germany, the High-Altitude Observatory (HAO), Boulder, USA, the Lockheed-Martin Solar and Astrophysics Laboratory (LMSAL), Palo Alto, USA, and the Spanish IMaX consortium. This paper will give an overview about the mission and a description of its scientific and technological aspects.

GPS 반송파 위상변화율을 이용한 SDINS/GPS 복합항법 필터 구성

SDINS 운항중 정렬에 적용 가능한 GPS 반송파 위상변화율 측정 모델을 유도하여 새로운 SDINS/GPS 복합항법 시스템 구성 방법을 제안한다. 제안된 SDINS/GPS 복합항법 필터의 성능 분석을 공분산 해석기법을 이용하여 수행하고 이의 결과를 실제 차량 실험을 통하여 검증한다. 제안된 결합기법은 2개 이상의 안테나를 갖는 SDINS/GPS 결합시스템에 적용가능하며 기수각 추정에 직접적으로 연계된 GPS 측정치를 생성함으로써 빠른 SDINS의 기수각 추정을 가능하게 함으로써 SDINS/GPS의 항법 성능을 향상시키게 된다. As an application of SDINS/GPS integration for its synergistic results, the SDINS alignments utilizing GPS carrier phase rate measurements. A measurement model of GPS carrier phase rate is derived in order to be used with SDINS alignment process. For in-flight alignment, the performance of the suggested SDINS/GPS integration method is analyzed using the covariance analysis and its results are confirmed by those of van test. Consequently, it is shown that all states of the SDINS integrated system by utilizing GPS carrier phase rate measurements can be estimated more efficiently than a general SDINS/GPS during in-flight alignment.