High-accuracy Inertial Navigation System Research Articles

An autonomous and high-accuracy gravity disturbance compensation scheme for rotary inertial navigation system

Abstract With the increasing demands for long-endurance and high-accuracy inertial navigation system (INS), gravity disturbance has been identified as one of the major error sources with decisive effects on the performance of INS. To address the problem, this paper proposes an autonomous and high-accuracy gravity disturbance compensation scheme for rotary INS (RINS). The high-accuracy velocity measured by the laser Doppler velocimeter is fused with the angular velocity measured by the gyroscope to obtain navigation parameters, such as velocity, position and attitude, that are not affected by gravity disturbance. The navigation parameters independent of gravity disturbance are matched with the gravity disturbance-related navigation parameters output by RINS, and a measurement model containing gravity disturbance information is obtained. Besides, the intrinsic coupling relationship between gravity disturbance, gravity disturbance rate and gravity disturbance gradient is revealed, and a state-space model is established to accurately reflect the time-varying characteristics of gravity disturbance. Furthermore, the gravity disturbance is estimated and compensated in real-time through the optimal estimation algorithm. The results of vehicle experiments indicate that the gravity disturbance estimation precision of the proposed scheme is better than 2.15 mGal (1σ), and its horizontal position accuracy is better than 50 m at a driving distance of 80 km.

DESIGN AND EXPERIMENT OF A HIGH PAYLOAD FIXED WING VTOL UAV SYSTEM FOR EMERGENCY RESPONSE

Abstract. With the development of UAV technologies, the advantages of hybrid VTOL UAV have been realized and taken in emergency response. But, former hybrid VTOL UAV is lack of capacities on payload and endurance, which restrict the integration of multiple sensors. In this paper, a high payload fixed wing VTOL UAV, which has 20 kg payload and more than 3 hours endurance, is used to design a UAV system for emergency response. Multiple sensors including an optronics pod, PhaseOne IXM-100 camera, high accuracy inertial navigation system and three-axis stable head are integrated with it. Based on this, specific processing software is developed to process the video data and image which could meet the requirements of emergency response in different stages. Experiment results shown that the precision of mosaic image is about 10m and the precision of orthoimage is about 1m. This work could be reference for the design and practice of UAV system with multiple sensors.

An Improved Map-Drift Algorithm for Unmanned Aerial Vehicle SAR Imaging

Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) is usually sensitive to trajectory deviations that cause severe motion error in the recorded data. Because of the small size of the UAV, it is difficult to carry a high-accuracy inertial navigation system. Therefore, in order to obtain a precise SAR imagery, autofocus algorithms, such as phase gradient autofocus (PGA) method and map-drift (MD) algorithm, were proposed to compensate the motion error based on the received signal, but most of them worked on range-invariant motion error and abundant prominent scatterers. In this letter, an improved MD algorithm is proposed to compensate the range-variant motion error compared to the existed MD algorithm. In this context, in order to solve the outliers caused by homogeneous scenes or absent prominent scatterers, a random sample consensus (RANSAC) algorithm is employed to mitigate the influence resulting from the outliers, realizing robust performance for different cases. Finally, real SAR data are applied to demonstrate the effectiveness of the proposed method.

Inertial Navigation System of Pipeline Inspection Gauge

In this brief, a high-accuracy inertial navigation system (INS) for a pipeline inspection gauge (PIG) is proposed. Two mechanization approaches are investigated. First, a full INS dynamic model is used, and second, a 3-D reduced inertial sensor system (RISS) is utilized. The INS uses the full inertial measurement unit (IMU) data to calculate the navigation solution, whereas the RISS uses an encoder, one single-axis gyroscope, and two accelerometers. The RISS model is proposed in this brief for its better accuracy and less computational complexity. Due to the accumulated error in the INS or RISS solution, an extended Kalman filter is proposed to fuse the IMU data with PIG measurements. For the full INS model, these measurements are the encoder’s derived velocity constraint and the detected pipe length measurement. On the other hand, for the RISS model, it only refers to the detected pipe length measurement. An experimental setup, with a prototype of the in-pipe robot, is designed and built to test and validate our algorithms in a real pipe environment. Subsequently, the accuracy of the proposed algorithms is verified experimentally.

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.

Autofocus Correction of Residual RCM for VHR SAR Sensors With Light-Small Aircraft

Due to the light weight and small size, synthetic aperture radar (SAR) sensors with light-small aircraft are very sensitive to atmospheric turbulences, which cause serious trajectory deviations. Limited by the cost or payloads, light-small aircraft sometimes cannot carry high-accuracy inertial navigation systems (INS)/global positioning systems (GPS). For the very high resolution (VHR) case, residual range cell migration (RCM) often exceeds several range resolution cells during the course of the synthetic aperture, thus degrading the image quality substantially. In this paper, a robust scheme for the correction of residual RCM is presented. The scheme consists of three principle steps. First, the range-compressed data in the signal domain are divided into subapertures in azimuth. For each subaperture, a sliding window is used to select the subblock data with the highest signal-to-clutter ratio. Second, for each subaperture, residual RCM is estimated by using the selected subblock data based on a nonparametric entropy minimization technique. Third, the estimated residual RCM of all subapertures are filtered and coherently combined to perform the correction for the full-aperture data. Processing the results of VHR SAR raw data shows that the proposed scheme is effective for highly precise imaging with light-small aircraft equipped with only low-accuracy INS/GPS.

WHY THE HORIZON IS IMPORTANT FOR AIRBORNE SENSE AND AVOID APPLICATIONS

Abstract. The utility of the horizon for airborne sense-and-avoid (ABSAA) applications is explored in this work. The horizon is a feature boundary across which an airborne scene can be separated into surface and sky and serves as a salient, heading-independent feature that may be mapped into an electro-optical sensor. The virtual horizon as established in this paper represents the horizon that would be seen assuming a featureless earth model and infinite visibility and is distinct from the apparent horizon in an imaging sensor or the pilot’s eye. For level flight, non-maneuvering collision course trajectories, it is expected that targets of interest will appear in close proximity to this virtual horizon. This paper presents a model for establishing the virtual horizon and its projection into a camera reference plane as part of the sensing element in an ABSAA system. Evaluation of the model was performed on a benchmark dataset of airborne collision geometries flown at the National Research Council (NRC) using the Cerberus camera array. The model was compared against ground truth flight test data collected using high accuracy inertial navigation systems aboard aircraft on several ’near-miss’ intercepts. The paper establishes the concept of ’virtual horizon proximity’ (VHP), the minimum distance from a detected target and the virtual horizon, and investigates the utility of using this metric as a means of rejecting false positive detections, and increasing range at first detection through the use of a region of interest (ROI) mask centred on the virtual horizon. The use of this horizon-centred ROI was shown to increase the range at first detection by an average factor of two, and was shown to reduce false positives for six popular feature detector algorithms applied across the suite of flight test imagery.

High-order attitude compensation in coning and rotation coexisting environment

With the development of high-accuracy inertial navigation system inertial sensors, such as ring laser gyroscopes and atomic spin gyroscopes, it is increasingly important to improve the strapdown inertial navigation algorithms to match such high-accuracy inertial sensors. For example, the existing inertial navigation algorithms have not taken into account the triple-cross-product term of noncommutativity error. However, theoretical analysis demonstrates that the ignored triple-cross-product term is nonignorable under coning motion with constant angular rate precession environments. In this paper, a new high-accuracy rotation vector algorithm is proposed for strapdown inertial navigation. The Taylor series about time is used for error analysis and optimization of the new algorithm. General maneuvers and coning motion with constant angular rate precession environments are considered in establishing the coefficient equations in the proposed algorithm. Error drift equations are given after the error compensation. Normalized quaternion under coning motion with constant angular rate precession environments and Savage’s severe integrated angular-rate profiles are used to numerically verify the new algorithm. The results indicate that the new high-order attitude updating algorithm can improve inertial navigation accuracy.

SAR Imaging and Interferometry Using Parameters Estimated from Raw Data

Due to the costs, sensitivity, and export policies of many governments, universities, and research institutions, particularly in developing countries, the ability to purchase, install and maintain high-accuracy inertial navigation system (INS) and global positioning system (GPS) is restricted. This paper presents a new method for SAR imaging and interferometry using parameters estimated from raw data. First, methods for determining the order of real and imaginary parts within the raw data images, and for determining chirp rate polarity are proposed. Second, a selection of parameters, including the forward effective velocities of the sensor, the near range distance, and the squint angle, are extracted using the Doppler centroid and Doppler rate. Finally, we create single look complex (SLC) images, coherence maps, digital elevation models (DEMs), and dual-pass differential unwrapped phase maps. The level of accuracy shown in this comparative study suggests that the proposed method is acceptable for creating the featured SAR products and is suitable for real world applications. This method and result is particularly relevant for systems which suffer from a lack of high-accuracy positional metadata.

Fiber-optic gyroscopes: from design to production [Invited

Fiber-optic gyroscopes (FOGs) represent an important development in the field of inertial sensors and are now considered an alternative technology to mechanical and ring laser gyroscopes for inertial navigation and control applications. The past 30 years of research and development around the world have established the FOG as a critical sensor for high-accuracy inertial navigation systems. In this paper, specifications, system configurations, and error and sensitivity analysis for different types of FOGs, including critical technology, are presented. This paper addresses the design and production of a different FOG that fulfills requirements such as small size, low production cost, low power consumption, and a broad spectrum of applications.

Gravity-model errors in mobile inertial-navigation systems

A high-accuracy inertial-navigation system (INS) is to be used to navigate a land-mobile Vehicle travelling at about 30 knots, Over time periods of 2-4 h or less. Important sources of navigation error are the errors in modeling the anomalous gravity forces acting on the vehicle. To obtain acceptable performance, the INS must be accurately compensated in real time for the anomalous gravity. A significant reduction in the growth of navigation errors can be obtained by stopping the vehicle periodically and processing zero-velocity updates in an on-board navigation filter. The land-navigation system design considerations that affect the growth of navigation error due to the gravity-model errors are examined here. These include the grid-spacing of the data base used to derive the real-time gravity compensation, the use of odometer and zero-sideslip measurement data for in-transit INS updating, and the frequency and accuracy of the at-rest zero-velocity updates which are the key to high-accuracy land navigation.