Barge Science Van IMU Data
This dataset contains high-frequency (10Hz) data from the GX5-45 IMU on the Barge Science vans. The data are all raw binary files.
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This dataset contains high-frequency (10Hz) data from the GX5-45 IMU on the Barge Science vans. The data are all raw binary files.
CSM IMU course alignmenment to ATM sensors for AAP
A redundant inertial measuring unit (IMU) incorporating six strapdown laser gyros and six accelerometers, arranged so that sensitive axes are normal to the faces of a dodecahedron, provides enhanced reliability with reduced hardware weight. Software monitoring of sensor outputs senses failure of sensors and the system is designed for triple redundancy, with built-in test equipment. Attention is centered on redundancy and fail-safe features, and on the closed-path ring laser gyro arrangement.
A computer program implements a thrust impulse measurement (TIM) filter, which processes data on changes in velocity and attitude of a spacecraft to estimate the small impulsive forces and torques exerted by the thrusters of the spacecraft reaction control system (RCS). The velocity-change data are obtained from line-of-sight-velocity data from Doppler measurements made from the Earth. The attitude-change data are the telemetered from an inertial measurement unit (IMU) aboard the spacecraft. The TIM filter estimates the threeaxis thrust vector for each RCS thruster, thereby enabling reduction of cumulative navigation error attributable to inaccurate prediction of thrust vectors. The filter has been augmented with a simple mathematical model to compensate for large temperature fluctuations in the spacecraft thruster catalyst bed in order to estimate thrust more accurately at deadbanding cold-firing levels. Also, rigorous consider-covariance estimation is applied in the TIM to account for the expected uncertainty in the moment of inertia and the location of the center of gravity of the spacecraft. The TIM filter was built with, and depends upon, a sigma-point consider-filter algorithm implemented in a Python-language computer program.
This software performs two functions: (1) taking stereo image pairs as input, it computes stereo disparity maps from them by cross-correlation to achieve 3D (three-dimensional) perception; (2) taking a sequence of stereo image pairs as input, it tracks features in the image sequence to estimate the motion of the cameras between successive image pairs. A real-time stereo vision system with IMU (inertial measurement unit)-assisted visual odometry was implemented on a single 750 MHz/520 MHz OMAP3530 SoC (system on chip) from TI (Texas Instruments). Frame rates of 46 fps (frames per second) were achieved at QVGA (Quarter Video Graphics Array i.e. 320 240), or 8 fps at VGA (Video Graphics Array 640 480) resolutions, while simultaneously tracking up to 200 features, taking full advantage of the OMAP3530's integer DSP (digital signal processor) and floating point ARM processors. This is a substantial advancement over previous work as the stereo implementation produces 146 Mde/s (millions of disparities evaluated per second) in 2.5W, yielding a stereo energy efficiency of 58.8 Mde/J, which is 3.75 better than prior DSP stereo while providing more functionality.
The continued advancement of small satellite-based science missions requires the solution to a number of important technical challenges. Of particular note is that small satellite missions are characterized by tight constraints on cost, mass, power, and volume that make them unable to fly the high-quality Inertial Measurement Units (IMUs) required for orbital missions demanding precise orientation and positioning. Instead, small satellite missions typically fly low-cost Micro-Electro-Mechanical System (MEMS) IMUs. Unfortunately, the performance characteristics of these MEMS IMUs make them ineffectual in many spaceflight applications when employed in a single IMU system configuration.
Various methods and apparatuses are provided for calibrating a three-axis IMU sensor package using a single-axis rate table. In one embodiment, a method includes adjusting an x-axis position of a sensor by rotating an inner assembly along the circumference of the inner surface of the circular frame, adjusting a y-axis position of the sensor by rotating a portion of the inner assembly, spinning the single-axis rate table to generate z-axis rotation of the apparatus which results in simultaneous stimulation of all three axes of the sensor assembly, and obtaining measurements from the sensor corresponding to the x-axis position, the y-axis position, and the z-axis rotation of the apparatus.
- Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, limb lengths are determined by motion capture or manual measurement. - A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. - When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. - Calculated limb lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. - This method was investigated as a possible away to obtain scaling information in data collections where IMUs are worn, but optical motion capture may not always be available, such as inside spacesuits or during crew exercise on the International Space Station.
The Orion flight software’s parity algorithm runs onboard to verify all three OIMUs (Orion Inertial Measurement Units) are sensing relatively uniform rate and acceleration and to quickly identify any unit which is in significant disagreement with the other two units. During the Artemis-I Wet Dress Rehearsal tests and Launch Countdowns, one of the three OIMUs regularly reported an anomalous parity signature for a brief period of time during sensor warm up. This paper will review this anomalous performance on the pad and review flight data with the intent to supplement the findings of the initial root cause investigation. Outside of this start up behavior, initial investigation into Artemis I flight data did not reveal any behavior of the OIMUs outside of preflight expectations. Flight data from any significant parity events and relevant IMU calibrations will be presented. A brief discussion of impacts to future Artemis mission operations strategy will be provided.
Inertial measurement units (IMUs) can be vital for vehicle attitude and position estimation in unmanned aerial vehicles (UAVs). Degradation in these units could result in incorrect position estimates that are utilized in vehicle control, trajectory prediction, and other critical systems; however, the modes and effects of degradation in these IMUs are not well understood. In order to quantify the risk posed by degradation in these sensors, a study was conducted on the types of IMUs prevalent in the commercial market, their known failure modes, and the applicability to health monitoring methods for risk reduction and increased safety in an increasingly autonomous airspace. First, use cases and failure modes of the various types and reliability of commercially available IMUs were reviewed, and knowledge gaps and issues in the field were identified. Noting that inexpensive and lightweight MEMS (Microelectromechanical Systems) IMUs are some of the most commonly used but least reliable sensors in sUAS (small Unmanned Aerial Systems), five inexpensive MEMS IMUs were chosen for a performance evaluation study, selected from the Pixhawk autopilot systems, hobby sUAS, and prior NASA experimental studies. For each of these IMUs, a 10-minute bias test and a 12-hour drift test were performed for the accelerometers in a benchtop setting, using a BeagleBone Black for data collection. Using these results, the sensors’ performance is compared to their reported specifications, and the utility of implementing diagnostic methods for MEMS IMUs for research and commercial applications is evaluated. The paper concludes with a planned study for the evaluation of vibration-induced degradation for the selected sensors.
Manual completion of lunar orbit insertion burn with inertial measuring unit drifting about pitch axis
A failure detection and isolation philosophy applicable to multiple off-the-shelf gimbaled IMUs are discussed. The equations developed are implemented and evaluated with actual shuttle trajectory simulations. The results of these simulations are presented for both powered and unpowered flight phases and at operational levels of four, three, and two IMUs. A multiple system checkout philosophy is developed and simulation results presented. The final task develops a laboratory test plan and defines the hardware and software requirements to implement an actual multiple system and evaluate the interim study results for space shuttle application.
The test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The subjects discussed are: (1) test philosophy and limitations, (2) test sequence, (3) equipment specifications, (4) general operating procedures, (5) calibration procedures, (6) alignment test phase, and (7) navigation test phase. The data and analysis requirements are analyzed.
The general test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The inertial unit contains six gyros and three orthogonal accelerometers. The software incorporates failure detection and correction logic and a land vehicle navigation program. The principal objective of the test is a demonstration of the practicability, reliability, and performance of the inertial measuring unit with failure detection and correction in operational environments.
The design of each system component is described. Emphasis is placed on functional requirements unique in this system, including data bus communication, data bus transmitters and receivers, and ternary-to-binary torquing decision logic. Mechanization drawings are presented.
A redundant gimballed inertial system is described. System requirements and mechanization methods are defined and hardware and software development is described. Failure detection and isolation algorithms are presented and technology achievements described. Application of the system as a test tool for shuttle avionics concepts is outlined.
Performance data for the sequential probability ratio test (SPRT) during shuttle entry are presented. Current modeling constants and failure thresholds are included for the full mission 3B from entry through landing trajectory. Minimum 100 percent detection/isolation failure levels and a discussion of the effects of failure direction are presented. Finally, a limited comparison of failures introduced at trajectory initiation shows that the SPRT algorithm performs slightly worse than the data tracking test.
There are six cases considered: (1) no updates made during the flight, (2) one ground update in the vertical components only at the first practice separation minus 15 minutes, (3) one ground update in all components at the first practice separation minus 5 minutes, (4) updates 2 and 3 applied successively, (5) Case 4 plus an update in all components at the second separation attempt minus 3 minutes, and (6) one ground update at first separation attempt minus 5 minutes and a second update at second separation minus two minutes. The mission control simulation program, GROPER, was run using as radar input a tape containing radar derived state vectors for the trajectory.