Showing papers on "Inertial measurement unit published in 1980"

Integrated-strapdown-air-data sensor system

Abstract: A plurality of inertial measuring unit (IMU) modules (41A, B, C and D) each comprising gyros and accelerometers (61, 65 and 67) for sensing inertial information along two orthogonal axes, are strapdown mounted in an aircraft, preferably such that the sense axes of the IMUs are skewed with respect to one another. Inertial and temperature signals produced by the IMU modules, plus pressure signals produced by a plurality of pressure transducer modules (43A, B and C) and air temperature signals produced by total air temperature sensors (45A and B) are applied to redundant signal processors (47A, B and C). The signal processors convert the raw analog information signals into digital form, error compensate the incoming raw digital data and, then, manipulate the compensated digital data to produce signals suitable for use by the automatic flight control, pilot display and navigation systems of the aircraft. The signal processors include: an interface system comprising a gyro subsystem (47), an accelerometer and air calibration data subsystem (50) and an air data and temperature subsystem (52); a computer (54); an instruction decoder ( 56); and, a clock (58). During computer interrupt intervals raw digital data is fed to the computer (54) by the interface subsystems under the control of the instruction decoder (56). The computer includes a central processing unit that compensates raw digital gyro and accelerometer data to eliminate bias, scale factor, dynamic and temperature errors, as necessary. The central processing unit also modifies the gyro and accelerometer data to compensate for relative misalignment between the sense axes of the gyros and accelerometers and for the skewed orientation of these sense axes relative to the yaw, roll and pitch axes of the aircraft. Further, accelerometer data is transformed from body coordinate form to navigational coordinate form and the result used to determine the velocity and position of the aircraft. Finally, the central processing unit develops initializing alignment signals and develops altitude, speed and corrected temperature and pressure signals.

Inertial measurement underwater tracking system

Abstract: An inertial measurement underwater tracking system which determines range sition onboard an underwater vehicle using inertial navigation techniques. The system uses acoustic telemetry to relay the range position from the vehicle to an operations site. The position data is also recorded onboard the vehicle for post-run analysis. An onboard computer receives the inertial measurements from an inertial measurement unit and computes vehicle position with respect to an initialized reference. An acoustic transmitter receives the measurements, formats the data and transmits it by acoustic telemetry. An underwater hydrophone receives the acoustic telemetry and inputs the data to an acoustic processor to reconstruct the original position data. A range computer processes in real-time the data, and displays and records the time history of vehicle location on the range. After recovery the onboard recorded data is played back into the range computer to provide a maximum accuracy, continuous vehicle-run history.

Design of a developmental dual fail operational redundant strapped down inertial measurement unit

Abstract: An experimental redundant strap-down inertial measurement unit (RSDIMU) is being developed at NASA-Langley as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit consists of four two-degrees-of-freedom (TDOF) tuned-rotor gyros, and four TDOF pendulous accelerometers in a skewed and separable semi-octahedron array. The system will be used to examine failure detection and isolation techniques, redundancy management rules, and optimal threshold levels for various flight configurations. The major characteristics of the RSDIMU hardware and software design, and its use as a research tool are described.

Performance of an Aided Redundant Navigator in Normal and Failure Modes

Abstract: The performance of a redundant strapdown inertia! navigation system in the normal mode, failure mode, and reconfiguration mode is characterized by a single figure-of-merit representing the probability of mission success. A sensitivity matrix derived from a linearized error analysis relates attitude, position, and velocity errors to initial condition errors as well as inertial sensor static and dynamic errors. The implementation of state vector updates is described. Numerical results are presented for an orbit insertion mission. INEARIZED error analyses have frequently been used to obtain a statistical characterization of navigation system performance.lj2 This paper presents a rigorous extension of these techniques to the analysis of the performance .of an aided redundant strapdown inertial navigation system. The formulation of this analysis in terms of the sensitivity of state errors to error sources provides considerable insight into the performance of the redundant system in the normal mode (i.e., in the absence of failures), as well as in any of the operational modes resulting from failures or from failure detection and identification (FDI) decisions which affect the sensor configuration. The design of redundant aided inertial navigation systems affords numerous opportunities to tradeoff system elements in an effort to satisfy performance objectives under various design constraints. The use of the linearized analysis described in this paper in combination with an analysis of FDI performance3 provides the quantitative results which make intelligent tradeoffs possible. The for- mulation of the analysis is sparing of computer resources and inexpensive to use once it has been implemented. The elements of the sensitivity matrices represent the sensitivity of system performance to each of the individual error sources or sensor failures which are modeled as deterministic constants. Using these sensitivity matrices, the statistics of the state errors (or their estimates) can be determined from the statistics of the error sources (or their estimates) at any time. The effects of error sources which are properly modeled as random processes can be evaluated by reformulating the analysis as a conventional covariance analysis4 or by com- puting their effects separately and adding them to the covariance of the state errors obtained from the sensitivity analysis. In the authors' experiences,5 the random errors which are characteristic of navigation quality inertial sensors seldom contribute significantly to overall system performance when all other error sources are considered. Navaid updates are formulated in terms of their effect on the statistics of the error sources rather than in terms of their effect on the sensitivities. This results in a computationally efficient evaluation of the extent to which navigation system performance can be improved, and the effects of system failures mitigated, through the use of navaids. The failure sensitivities, which are computed in the linearized analysis, establish the levels of failures which significantly degrade system performance. These levels represent design requirements for the FDI system. Once the FDI system is designed, the analysis of navigation system performance can be combined with an analysis of FDI per- formance to choose FDI thresholds which maximize the probability of success of the system.6 The remainder of the paper is divided into two major sections. The first section presents the analysis. The recursive equations used to propagate the sensitivity matrices along a nominal trajectory are developed, and the equations used to update the statistics of the state errors are derived. The modifications of these results to account for system failures are then discussed. The second section presents results for an aided redundant strapdown inertial navigation system consisting of five gyros and five accelerometers in a conical array. Star-sensor and ranging measurements are included to indicate the effects of navaid updates on system performance in normal and failure modes.

Linear vibration techniques for measuring the cross axis error coefficient in an accelerometer

Abstract: A relatively recent error term identified for the specific force integrating receiver (SFIR) on the MX Missile Program is called FX1. It is an error in the sensed input axis acceleration caused by a forcing function component of acceleration into the device cross axis (perpendicular to the input axis). Sophisticated SFIR 1 g tumbling tests are currently under dzvelopment at both Honeywell and the Charles Stark Draper Lab (CSDL), but so far they have not demonstrated an accurate enough FX1 to be confidently modeled in the inertial measurement unit (IMU) calibration and alignment procedure. Precision centrifuge testing has also been conducted. On an engineering characterization basis, these centrifuge tests have demonstrated potential, however, the setup is too complex to be considered for acceptance testing. This paper addresses a linear vibrator methology which is under development by Honeywell. Testing and analysis discussed in this paper show that it has potential to be a simple set-up and also can theorectically meet the IMU error budget requirement. The basic problem in this measurement technique is to reduce the disturbances in the test environment to the point that mathematics can produce a reliable estimate of FX1. The precision of the measurement needed is several orders beyond the detectable seismic environment of the test geographic location. The design of a new vibration facility to accomplish the foregoing is discussed in the paper.