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Conrad, B.

Publications and source records attributed to Conrad, B..

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Flight evaluation of advanced navigation techniques for general aviation using frequency scanning

Experiments on an automatic multisensor navigation concept are being conducted in a Cessna 402B. The test system consists of VOR, DME, and air data sensors controlled by a Hewlett Packard 9820A electronic calculator which processes the data and, by means of a four-state Kalman filter, outputs position and ground and wind velocities to a map display. Novel features which make such a system potentially low-cost include frequency-scanning operation of a single VOR receiver and a single DME transceiver and use of a shed-vortex true airspeed sensor. Results obtained during flight in a local area where six to eight DME NAVAIDS were receivable yielded better than 1/4-mile accuracy.

Jackson, C. T., Jr.↗
NASA NTRS1975

Evaluation of several navigation algorithms for application to general aviation

Using data obtained in flight, three position determining algorithms for use by general aviation aircraft were evaluated representing increasing software requirements. These were a DME only, DME/air data and blended DME/air data. Although each step represented additional software with resultant increase in position accuracy, all could be performed on a programmable electronic desk calculator. Results from the computation of aircraft position using the three algorithms are presented. The algorithms employed can be extended to accept VOR, TACAN bearing, ADF, or other NAVAID Data. To obtain the flight data an experimental system was configured and flown on a general aviation aircraft. Principal hardware elements (all with low-cost potential) were a programmable calculator, a single DME receiver (multiplexed for multiple DME use) and a low-cost air speed sensor (shed-vortex principle). The flight test demonstrated satisfactory performance of these principal elements.

Conrad, B.↗
NASA NTRS1973

New mechanization equations for aided inertial navigation systems

Inertial navigation equations are developed which use area navigation (RNAV) waypoints and runway references as coodinate centers. The formulation is designed for aided inertial navigation systems and gives a high numerical accuracy through all phases of flight. A new formulation of the error equations for inertial navigation systems is also presented. This new formulation reduces numerical calculations in the use of Kalman filters for aided inertial navigation systems.

Schmidt, S. F.↗
NASA NTRS1973

Flight results from a study of aided inertial navigation applied to landing operations

An evaluation is presented of the approach and landing performance of a Kalman filter aided inertial navigation system using flight data obtained from a series of approaches and landings of the CV-340 aircraft at an instrumented test area. A description of the flight test is given, in which data recorded included: (1) accelerometer signals from the platform of an INS; (2) three ranges from the Ames-Cubic Precision Ranging System; and (3) radar and barometric altimeter signals. The method of system evaluation employed was postflight processing of the recorded data using a Kalman filter which was designed for use on the XDS920 computer onboard the CV-340 aircraft. Results shown include comparisons between the trajectories as estimated by the Kalman filter aided system and as determined from cinetheodolite data. Data start initialization of the Kalman filter, operation at a practical data rate, postflight modeling of sensor errors and operation under the adverse condition of bad data are illustrated.

Mcgee, L. A.↗
NASA NTRS1973

Washout circuit design for multi-degrees-of-freedom moving base simulators.

A mathematical framework is presented for designing logic to accept motion-dependent parameters from a simulation, attenuating them ('washing them out'), and generating appropriately limited drive signals. This framework is sufficiently general to encompass six-degree-of-freedom simulators with large motion capability. Emphasis is placed on preserving certain motion cue relations (such as those that would be observed in coordinated flight). Strategies for simulating side forces via tilts are shown. Finally, several specific circuits are shown. These circuits have proven to be readily adaptable to a variety of moving-base simulators.

Conrad, B.↗
NASA NTRS1972

A comparison of the effects of small nonlinearities on several estimation schemes.

A variety of techniques are available for estimating the states of nonlinear dynamic systems from noisy data. These procedures are generally equivalent when applied to linear systems. This paper investigates the difference between several of these procedures in the presence of small dynamic and observational nonlinearities. In particular, it examines one least square batch processing algorithm, and three recursive algorithms similar to the Kalman filter. To first order, all the estimators have the same covariance. Expressions for the means, however, show that each estimator has a different bias. The examples presented show that the biases can be a strong function of such parameters as initial covariances and number of data points being considered.

Conrad, B.↗
NASA NTRS1971

State estimation with small nonlinearities

A variety of techniques is available for estimating the states of nonlinear dynamic systems from noisy data. The differences among several of these procedures in the presence of small dynamic and observational nonlinearities are investigated. Four discrete estimation algorithms are analyzed. The first is a strictly least square estimator, while the others are recursive algorithms similar to the Kalman filter used for estimating the states of linear systems. A group of analytic expressions is developed for the mean and covariance of the error in each of these estimators so that they may be compared without lengthy Monte Carlo simulations. The covariance expressions show that, to first order, all the estimators have the same covariance. Expressions for the means show that each estimator has a different bias. Several examples are carried out demonstrating that the relative magnitudes of the bias errors in the various estimators can be a strong function of such parameters as initial covariances and number of data points. Under some circumstances, more complicated algorithms can have larger biases than smaller ones.

Conrad, B.↗