Showing papers on "GPS/INS published in 1980"

Accurate Time and Frequency Transfer During Common-View of a GPS Satellite

Abstract: Summary First, Clock A and a GPS receiver are used to Even though the GPS is primarily a navigation deduce from a GPS sate1 1 ite' s ephemeris, from system, if two clocks at known coordinates A and B clock .A's location, and from received GPS time are in common-view of a single GPS satellite, receivers at these two clock sites may coinciden- decoded from the same satellite, the time differtally receive transmitted GPS clock times. By ence (Clock A - GPS time). This method is the subtracting the received times of arrivals as measured by clocks A and B at the two sites while simplest and least accurate (estimated to be compensating for the propagation delays, one has better than about 100 ns with respect to GPS an accurate measure of the time difference between time),2 but has global coverage, is in the receiveclock A and clock B. When all of the error contributions are only mode, requires no other data, yields receiver

Optimal Processing of GPS Signals

Abstract: This paper formulates a Kalman estimator as an optimal tracker/navigator for GPS. The approach is motivated by considering the signal and navigation processing performed by a GPS set not as separate functions, but as a single integrated function. The practical realization of this integrated tracker/navigator is discussed, and simulation results are presented which permit comparison of its performance with that of more conventional, partitioned designs.

Accurate INS Transfer Alignment Using a Monitor Gyro and External Navigation Measurements

Abstract: A particular alignment mechanization for a nonmaneuvering vehicle is described which uses a monitor gyro to estimate the slave inertial navigation system (INS) equivalent east gyro drift rate and thus improves azimuth alignment. A state-space model of the dynamic system with measurements is developed. Results of covariance simulations employing Kalman filter estimation are presented for two master INS position update scenarios, one involving frequent and very accurate updates and the other including infrequent and coarse updates. The ef fects of position updates and the monitor gyro on the quality of transfer alignment are demonstrated and analyzed.

Novel Method for Data Compression in Recursive INS Error Estimation

Abstract: In this work a new data compression method is presented which is applicable to systems whose observables are a linear combination of only a part of the system states. This characteristic is quite common in applied problems, especially in inertial navigation systems (INS). As a result, the formulation of the Kalman filter can be revised to yield a peculiar form for the covariance and state update which is the foundation of the new data compression method. The computations, according to this method, are divided into fast and slow rates. At the fast rate, which is determined by the availability of the measured data, a reduced-order Kalman filter is propagated and updated. The full-order system is propagated and updated only at a slow rate chosen by the designer. Utilizing the peculiar Kalman filter form of this case, the full-order system update is performed on the basis of the output of the reduced-order filter at each slow rate update time. Results of the application of this new data compression method to an INS are presented.

Integration of multi-sensor navigation data using optimal estimation techniques

Abstract: Optimal filtering and smoothing algorithms are used to obtain precise aircraft position, velocity and attitude information for remote sensing applications by post-flight processing of navigation data collected by several sensors. The data from an Inertial Navigation System (INS) is differenced with data obtained from other sensors which may include photogrammetric resections, a microwave ranging system, a barometric altimeter, a radar altimeter, a laser radar, a VLF/OMEGA navigation system and doppler radar to construct error measurements. The measurements are prefiltered to compress the data and are then processed through a Kalman filter to produce estimates of the time-correlated sensor errors. The filtered error estimates are smoothed by processing backwards in time and used to correct the INS data. The track recovery program uses the UDUT covariance factorized form of the filter algorithm and is capable of processing data from any subset of sensors. The residual errors observed in processing real data collected in a number of field tests are less than 1 meter in position and less than 0.03 degrees in attitude.

Using optimal estimation teceniques

Abstract: Optimal filtering and smoothing algorithms are used to obtain precise aircraft position, velocity and attitude information for remote sensing applications by postflight processing of navigation data collected by several sensors. The data from an Inertial Navigation System (INS) is differenced with data obtained from other sensors which may include photogrammetric resections, a microwave ranging system, a baranetric altimeter, a radar altimeter, a laser radar, a VLF/OHEGA navigation system and doppler radar to construct error measurements. The measurements are prefiltered to compress the data and are then processed through a Kalman filter to produce estimates of the time-correlated sensor errors. The filtered error estimates are smoothed by processing backwards in time and used to correct the INS data. The track recovery program uses the UDUT covariance factorited form of the filter algorithm and is The residual errors observed in processing real data capable of processing data from any subset of sensors. collected in a number of field tests are less than 1 meter in position and less than 0.03 degrees in attitude.