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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

On Transforming the Specific Force Vector for an ECEF Inertial Navigation System

An inertial measurement unit accumulates the instantaneous specific force applied to the sensor over a small window of time. Importantly, this accumulation occurs in the sensor’s frame, yet the specific force must be mathematically integrated in a different navigation frame, and these two frames may be rotating with respect to each other. Consequently, a correction is needed to not only account for the frame difference but also for the time variation in the frame difference. Many references provide derivations of this correction [1], but the derivation is often abbreviated, and important assumptions are sometimes left unstated. This memo addresses this gap and provides a clear derivation of the specific force transform with all assumptions specifically stated. This derivation is specific to the Earth-centered, Earth-fixed navigation frame, but, hopefully, the derivation is sufficiently clear that readers can apply it to other navigation frames. Generally, notation follows the same format as described in both [1, 2].

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Flight evaluation of differential GPS aided inertial navigation systems

Algorithms are described for integration of Differential Global Positioning System (DGPS) data with Inertial Navigation System (INS) data to provide an integrated DGPS/INS navigation system. The objective is to establish the benefits that can be achieved through various levels of integration of DGPS with INS for precision navigation. An eight state Kalman filter integration was implemented in real-time on a twin turbo-prop transport aircraft to evaluate system performance during terminal approach and landing operations. A fully integrated DGPS/INS system is also presented which models accelerometer and rate-gyro measurement errors plus position, velocity, and attitude errors. The fully integrated system was implemented off-line using range-domain (seventeen-state) and position domain (fifteen-state) Kalman filters. Both filter integration approaches were evaluated using data collected during the flight test. Flight-test data consisted of measurements from a 5 channel Precision Code GPS receiver, a strap-down Inertial Navigation Unit (INU), and GPS satellite differential range corrections from a ground reference station. The aircraft was laser tracked to determine its true position. Results indicate that there is no significant improvement in positioning accuracy with the higher levels of DGPS/INS integration. All three systems provided high-frequency (e.g., 20 Hz) estimates of position and velocity. The fully integrated system provided estimates of inertial sensor errors which may be used to improve INS navigation accuracy should GPS become unavailable, and improved estimates of acceleration, attitude, and body rates which can be used for guidance and control. Precision Code DGPS/INS positioning accuracy (root-mean-square) was 1.0 m cross-track and 3.0 m vertical. (This AGARDograph was sponsored by the Guidance and Control Panel.)

Mcnally, B. David↗
NASA NTRS1983

Flight test results of the strapdown ring laser gyro tetrad inertial navigation system

A helicopter flight test program undertaken to evaluate the performance of Tetrad (a strap down, laser gyro, inertial navigation system) is described. The results of 34 flights show a mean final navigational velocity error of 5.06 knots, with a standard deviation of 3.84 knots; a corresponding mean final position error of 2.66 n. mi., with a standard deviation of 1.48 n. mi.; and a modeled mean position error growth rate for the 34 tests of 1.96 knots, with a standard deviation of 1.09 knots. No laser gyro or accelerometer failures were detected during the flight tests. Off line parity residual studies used simulated failures with the prerecorded flight test and laboratory test data. The airborne Tetrad system's failure--detection logic, exercised during the tests, successfully demonstrated the detection of simulated ""hard'' failures and the system's ability to continue successfully to navigate by removing the simulated faulted sensor from the computations. Tetrad's four ring laser gyros provided reliable and accurate angular rate sensing during the 4 yr of the test program, and no sensor failures were detected during the evaluation of free inertial navigation performance.

Carestia, R. A.↗
NASA NTRS1981

Superconducting tensor gravity gradiometer for satellite geodesy and inertial navigation

A sensitive gravity gradiometer can provide much needed gravity data of the earth and improve the accuracy of inertial navigation. Superconductivity and other properties of materials at low temperatures can be used to obtain a sensitive, low-drift gravity gradiometer; by differencing the outputs of accelerometer pairs using superconducting circuits, it is possible to construct a tensor gravity gradiometer which measures all the in-line and cross components of the tensor simultaneously. Additional superconducting circuits can be provided to determine the linear and angular acceleration vectors. A tensor gravity gradiometer with these features is being developed for satellite geodesy. The device constitutes a complete package of inertial navigation instruments with angular and linear acceleration readouts as well as gravity signals.

Paik, H. J.↗
DOE OSTI2025

Earth-Centered, Earth-Fixed Inertial Navigation System & Error-State Kalman Filter Reference Manual

This is a self-contained reference document that derives the equations necessary to build a combined inertial navigation system and error-state Kalman filter. Coordinate transform, linear time invariant system, inertial sensing, and error-state Kalman filtering theory is built up from first principles. This theory is then leveraged to derive the system equations for two combined inertial navigation system and error-state Kalman filters: (1) a 15-state system modeling white-noise-integrating accelerometer and gyroscope biases, and (2) a 39-state system modeling static and first-order Gauss-Markov accelerometer and gyroscope biases, scale factor errors, and cross-axis sensitivity errors.

42 ENGINEERING↗
NASA NTRS1971

Dynamic errors in strapdown inertial navigation systems

Motion-induced errors in strapdown inertial navigation systems are discussed. The errors generated in single-degree-of-freedom gyros and accelerometers are treated in great detail. These sensor errors are related to errors at the system level and common pulse rebalance techniques are compared. Since instrument single transmission characteristics are found to be important, describing function analysis is applied to nonlinear pulse torqued inertial sensor loops, and the results are compared with simulations. Two means for reducing motion-induced errors are explored: (1) selection of inertial sensor parameters, and (2) active error compensation by measuring the environment, computing the errors generated, and correcting for them.

Source record↗