Inertial navigation system

About: Inertial navigation system is a research topic. Over the lifetime, 14582 publications have been published within this topic receiving 190618 citations. The topic is also known as: intertial guidance system & inertial reference platform.

Daytime stellar imager

Abstract: An automatic celestial navigation system for navigating both night and day by observation of K-band or H-band infrared light from multiple stars. In a first set of preferred embodiments three relatively large aperture telescopes are rigidly mounted on a movable platform such as a ship or airplane with each telescope being directed at a substantially different portion of sky. Embodiments in this first set tend to be relatively large and heavy, such as about one cubic meter and about 60 pounds. In a second set of preferred embodiments one or more smaller aperture telescopes are pivotably mounted on a movable platform such as a ship, airplane or missile so that the telescope or telescopes can be pivoted to point toward specific regions of the sky. Embodiments of this second set are mechanically more complicated than those of the first set, but are much smaller and lighter and are especially useful for guidance of aircraft and missiles. Telescope optics focus (on to a pixel array of a sensor) H-band or K-band light from one or more stars in the field of view of each telescope. Each system also includes an inclinometer, an accurate timing device and a computer processor having access to catalogued infrared star charts. The processor for each system is programmed with special algorithms to use image data from the infrared sensors, inclination information from the inclinometer, time information from the timing device and the catalogued star charts information to determine positions of the platform. Direction information from two stars is needed for locating the platform with respect to the celestial sphere. The computer is also preferably programmed to use this celestial position information to calculate latitude and longitude which may be displayed on a display device such as a monitor or used by a guidance control system. These embodiments are jam proof and insensitive to radio frequency interference. These systems provide efficient alternatives to GPS when GPS is unavailable and can be used for periodic augmentation of inertial navigation systems.

INS/GPS integration using neural networks for land vehicular navigation applications

Abstract: Most of the present navigation sensor integration techniques are based on Kalman filtering estimation procedures. Although Kalman filtering represents one of the best solutions for multi-sensor integration, it has some drawbacks in terms of stability, computation load, immunity to noise effects and observability. Furthermore, Kalman filters perform adequately only under certain predefined dynamic models. Neuron computing, a technology of Artificial Neural Network (ANN), is a powerful tool for solving nonlinear problems that involve mapping input data to output data without having any prior knowledge about the mathematical process involved. This article suggests a multi-sensor integration approach for fusing data from an Inertial Navigation system (INS) and Differential Global Positioning System (DGPS) utilizing multi-layer feed-forward neural networks with a back propagation learning algorithm. The performance of the proposed architecture was tested using two different INS systems(tactical grade IMU and navigation grade IMU) in a land vehicle.

Integrated Navigation and Guidance Systems

Abstract: Principles of Navigation and the Concept of an Integrated Navigation System Newton's Laws Applied to Navigation (Geodesics, Basic Reference Frames, Simplified Aerospace Vehicle Equation) Inertial Navigation Systems (INS) and Global Positioning System (GPS) Uncertainty in Navigation, INS Error Propagation, Probabilities, Autocorrelation and the Method of Least Squares Kalman Filters and Their Key Role in the Integration of Aircraft Avionics Systems GPS Theory and its Application to Navigation (Including System Accuracy) GPS Application to Precision Approach and Landing, Attitude Control and Air Traffic Control Flight Testing of Navigation Systems Computer Exercises.

Visual–Inertial Navigation Systems for Aerial Robotics: Sensor Fusion and Technology

Abstract: In this paper, we comprehensively discuss the current progress of visual–inertial (VI) navigation systems and sensor fusion research with a particular focus on small unmanned aerial vehicles, known as microaerial vehicles (MAVs). Such fusion has become very topical due to the complementary characteristics of the two sensing modalities. We discuss the pros and cons of the most widely implemented VI systems against the navigational and maneuvering capabilities of MAVs. Considering the issue of optimum data fusion from multiple heterogeneous sensors, we examine the potential of the most widely used advanced state estimation techniques (both linear and nonlinear as well as Bayesian and non-Bayesian) against various MAV design considerations. Finally, we highlight several research opportunities and potential challenges associated with each technique.

Tight coupling of GPS, laser scanner, and inertial measurements for navigation in urban environments

Abstract: Many applications can be envisioned for accurate, robust, and reliable navigation solution in challenging urban environments. Examples of existing and prospective applications include, but are not limited to, navigation, guidance, and control of autonomous vehicles (including both ground and aerial vehicles) for urban surveillance and reconnaissance; collection of geographical information system (GIS) data in cities; monitoring of urban infrastructure for situational awareness; and, precise automotive applications such as automated lane keeping. If used by themselves, none of the existing navigation technologies have the potential to fully satisfy the requirements for reliable and accurate navigation in urban environments. Hence, this paper develops a multi-sensor integrated solution that combines the complementary features of the Global Positioning System (GPS), laser scanner feature-based navigation, and inertial navigation for urban scenarios. GPS and laser scanner-based navigation ideally complement each other for urban navigation. The laser scanner-based navigation relies on the availability of structures (lines and surfaces) within the scan range (80 m, typically). Features (such as lines) are first extracted from laser scan images and then used for position and attitude determination. In urban areas, if there exists a building wall that blocks GPS signals, this wall creates a feature in the laser scan image. On the other hand, for open streets with limited features, the GPS signal is generally unobstructed. Thus, GPS and laser data can be combined into integrated solution architecture. The system architecture developed also exploits INS navigation states for improved solution robustness: e.g., for robust feature association between scan images and for coasting through instances where sufficient number of combined GPS/laser measurements is unavailable. A tightly coupled GPS/laser scanner/INS mechanization is developed and applied for centimeter- accurate trajectory reconstruction. The paper uses live urban data to demonstrate that combined GPS and laser scanner data generally support the observability of navigation states at any part of the urban trajectory; and, for those limited cases where insufficient GPS/laser measurements are available, the INS coasting option can be efficiently utilized. Test results presented also show that the developed tightly coupled GPS/laser scanner/INS solution provides accurate trajectory reconstruction capabilities (one sigma error residuals are at a cm-level) in challenging urban environments.