Showing papers on "Inertial measurement unit published in 1972"

In-Flight Alignment and Calibration of Inertial Measurement Units - Part I: General Formulation

Abstract: This is the first part of a two-part paper which summarizes work pursued by the author in 1966 [1]. The paper describes the application of minimum-variance estimation techniques for in-flight alignment and calibration of an inertial measurement unit (IMU) relative to another IMU and/or some other reference. The first part formulates the problem, and the second part [2] reports numerical results and analyses. The approach taken is to cast the problem into the framework of Kalman-Bucy estimation theory, where velocity and position differences between the two IMU's are used as observations and the IMU parameters of interest become part of the state vector. Instrument quantization and computer roundoff errors are considered as measurement noise, and environmental induced random accelerations are considered as state noise. Typical applications of the technique presented might include the alignment and calibration of IMU's on aircraft carriers, the initialization of rockets or rocket airplanes which are launched from the wing of a mother ship, the alignment and calibration of IMU's which are only used in the latter phases of rocket flight, and for the initialization/updating of SST guidance systems.

In-Flight Alignment and Calibration of Inertial Measurement Units - Part II: Experimental Results

Abstract: This is the second part of a two-part paper which summarizes work pursued by the author in 1967 [2]. The paper describes the application of minimum-variance estimation techniques for in-flight alignment and calibration of an inertial measurement unit (IMU) relative to another IMU and/or some other reference. The first paper [1] formulates the problem, and this paper reports numerical results and analyses. The approach taken is to cast the problem into the framework of Kalman-Bucy estimation theory, where velocity and position differences between the two IMU's are used as observations and the IMU parameters of interest become part of the state vector. Instrument quantization and computer roundoff errors are considered as measurement noise, and environmental induced random accelerations are considered as state noise. In this paper, numerical results for three important IMU error parameter configurations are presented and discussed. The main results of the paper determine the effects of state and observation noise levels and the nominal trajectory on the identifications of the errors for these configurations. A discussion of the minimum number of trajectory maneuvers and of the optimal trajectory maneuvering is given.

Ships inertial navigation storage and retrieval system (sinsars)

Abstract: A system for storing and retrieving the outputs of inertial sensors (accelerometers) and of other appropriate quantities such as EM Log Data (velocity reference), time, gimbal angle information and depth gauge data (depth reference aboard a submarine) of an inertial system, in order to be able to continue navigation with reasonable accuracy at some future time after a system failure without the need of external information to re-initialize the solution of the navigation problem. The system comprises an inertial measuring unit (IMU), a navigation computer, a memory unit, and an electronic switching and timing unit. Sensor information from the inertial measuring unit (IMU) is stored temporarily during non-availability of the navigation computer. The sensors of the inertial measuring unit continue to supply information for storage during the time the navigation computer is inoperative without requiring command and/or control information from the computer. The navigation computer processes the sensor information stored during its failure at a rate faster than that of real time data processing until it has processed all of the stored sensor information. The navigation computer goes into its normal processing mode thereafter. Thus accurate navigation is continued without the submarine coming to the surface for resets (reference information).

Theory of gyro with rotating gimbal and flexural pivots

Abstract: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.

An All‐Earth Inertial Navigation Scheme

Abstract: An approach to global inertial navigation utilizing a grid coordinate system in the polar regions is presented. The scheme presented offers a number of computational advantages in comparison to other methods proposed. The proposed scheme also allows vehicle heading with respect to grid north to be known directly, and vehicle position in Polar Orthographic map coordinates.

Navigation strategy and filter design for solar electric missions

Abstract: Methods which have been proposed to improve the navigation accuracy for the low-thrust space vehicle include modifications to the standard Sequential- and Batch-type orbit determination procedures and the use of inertial measuring units (IMU) which measures directly the acceleration applied to the vehicle. The navigation accuracy obtained using one of the more promising modifications to the orbit determination procedures is compared with a combined IMU-Standard. The unknown accelerations are approximated as both first-order and second-order Gauss-Markov processes. The comparison is based on numerical results obtained in a study of the navigation requirements of a numerically simulated 152-day low-thrust mission to the asteroid Eros. The results obtained in the simulation indicate that the DMC algorithm will yield a significant improvement over the navigation accuracies achieved with previous estimation algorithms. In addition, the DMC algorithms will yield better navigation accuracies than the IMU-Standard Orbit Determination algorithm, except for extremely precise IMU measurements, i.e., gyroplatform alignment .01 deg and accelerometer signal-to-noise ratio .07. Unless these accuracies are achieved, the IMU navigation accuracies are generally unacceptable.

Station-keeping guidance

Abstract: The station-keeping guidance system is described, which is designed to automatically keep one orbiting vehicle within a prescribed zone fixed with respect to another orbiting vehicle. The active vehicle, i.e. the one performing the station-keeping maneuvers, is referred to as the shuttle. The other passive orbiting vehicle is denoted as the workshop. The passive vehicle is assumed to be in a low-eccentricity near-earth orbit. The primary navigation sensor considered is a gimballed tracking radar located on board the shuttle. It provides data on relative range and range rate between the two vehicles. Also measured are the shaft and trunnion axes gimbal angles. An inertial measurement unit (IMU) is provided on board the orbiter. The IMU is used at all times to provide an attitude reference for the vehicle. The IMU accelerometers are used periodically to monitor the velocity-correction burns applied to the shuttle during the station-keeping mode. The guidance system is capable of station-keeping the shuttle in any arbitrary position with respect to the workshop by periodically applying velocity-correction pulses to the shuttle.