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At least 181 records · Page 10

Range filtering for sequential GPS receivers

The filtering of the satellite range and range-rate measurements from single channel sequential Global Positioning System receivers is usually done with an extended Kalman filter which has state variables defined in terms of an orthogonal navigation reference frame. An attractive suboptimal alternative is range-domain filtering, in which the individual satellite measurements are filtered separately before they are combined for the navigation solution. The main advantages of range-domain filtering are decreased processing and storage requirements and simplified tuning. Several range filter mechanization alternatives are presented, along with an innovative approach for combining the filtered range-domain quantities to determine the navigation state estimate. In addition, a method is outlined for incorporating measurements from auxiliary sensors such as altimeters into the navigation state estimation scheme similarly to the satellite measurements. A method is also described for incorporating inertial measurements into the navigation state estimator as a process driver.

Paielli, Russell

Spacecraft attitude determination using a second-order nonlinear filter

The stringent attitude determination accuracy and faster slew maneuver requirements demanded by present-day spacecraft control systems motivate the development of recursive nonlinear filters for attitude estimation. This paper presents the second-order filter development for the estimation of attitude quaternion using three-axis gyro and star tracker measurement data. Performance comparisons have been made by computer simulation of system models and filter mechanization. It is shown that the second-order filter consistently performs better than the extended Kalman filter when the performance index of the root sum square estimation error of the quaternion vector is compared. The second-order filter identifies the gyro drift rates faster than the extended Kalman filter. The uniqueness of this algorithm is the online generation of the time-varying process and measurement noise covariance matrices, derived as a function or the process and measurement nonlinearity, respectively.

Vathsal, S.

Accuracy of telemetry signal power loss in a filter as an estimate for telemetry degradation

When telemetry data is transmitted through a communication link, some degradation in telemetry performance occurs as a result of the imperfect frequency response of the channel. The term telemetry degradation as used here is the increase in received signal power required to offset this filtering. The usual approach to assessing this degradation is to assume that it is equal to the signal power loss in the filtering, which is easily calculated. However, this approach neglects the effects of the nonlinear phase response of the filter, the effect of any reduction of the receiving system noise due to the filter, and intersymbol interference. Here, an exact calculation of the telemetry degradation, which includes all of the above effects, is compared with the signal power loss calculation for RF filtering of NRZ data on a carrier. The signal power loss calculation is found to be a reasonable approximation when the filter follows the point at which the receiving system noise is introduced, especially if the signal power loss is less than 0.5 dB. The signal power loss approximation is less valid when the receiving system noise is not filtered.

Koerner, M. A.

New insights in the numerical reliability properties of existing Kalman filter implementations

The convergence properties of Kalman filter algorithms are investigated analytically. A theoretical error analysis is performed on four types of algorithms, as defined by Anderson and Moore (1979): (1) a conventional Kalman filter, (2) a square-root (SR) covariance filter, (3) the Chandrasekhar SR filter, and (4) an SR information filter. The derivations are given in detail, and numerical results for the flight-path reconstruction problem studied by Verhaegen (1987) are presented in tables and graphs. It is shown that error propagation in algorithms (1) and (2) is sensitive to the condition number of the innovation-signal covariance matrix and the spectral norm of the filter state-transition matrix, whereas other parameters are dominant in (3) and (4). Filter (2) is found to be the most reliable for the class of problems studied.

Verhaegen, M. H.

A superior edge preserving filter with a systematic analysis

A new, adaptive, edge preserving filter for use in image processing is presented. It had superior performance when compared to other filters. Termed the contiguous K-average, it aggregates pixels by examining all pixels contiguous to an existing cluster and adding the pixel closest to the mean of the existing cluster. The process is iterated until K pixels were accumulated. Rather than simply compare the visual results of processing with this operator to other filters, some approaches were developed which allow quantitative evaluation of how well and filter performs. Particular attention is given to the standard deviation of noise within a feature and the stability of imagery under iterative processing. Demonstrations illustrate the performance of several filters to discriminate against noise and retain edges, the effect of filtering as a preprocessing step, and the utility of the contiguous K-average filter when used with remote sensing data.

Holladay, Kenneth W.

Design of optimal binary phase and amplitude filters for maximization of correlation peak sharpness

Current binary-phase filters used for optical correlation are usually assumed to have uniform amplitude transmission. Here, a new type of filter is studied, the binary-phase-and-amplitude filter. If binary phase values of 0 and pi are assumed, the amplitude transmittance values of this type of filter can be optimized to maximize the peak sharpness. For a polarization-encoded binary-phase filter this can be translated into optimization of the rotation angle of the output polarizer following the filter-spatial-light modulator. An analytic expression is presented for the optimum polarizer angle and thus for the optimum binary-phase-and-amplitude filter design.

Downie, John D.

Stability and performance of notch filter control for unbalance response

Many current applications of magnetic bearings for rotating machinery employ notch filters in the feedback control loop to reduce the synchronous forces transmitted through the bearings. The capabilities and limitations of notch filter control are investigated. First, a rigid rotor is examined with some classical root locus techniques. Notch filter control is shown to result in conditional stability whenever complete synchronous attenuation is required. Next, a nondimensional parametric symmetric flexible three mass rotor model is constructed. An examination of this model for several test cases illustrates the limited attenuation possible with notch filters at and near the system critical speeds when the bearing damping is low. The notch filter's alteration of the feedback loop is shown to cause stability problems which limits performance. Poor transient response may also result. A high speed compressor is then examined as a candidate for notch filter control. A collocated 22 mass station model with lead-lag control is used. The analysis confirms the reduction in stability robustness that can occur with notch filter control. It is concluded that other methods of synchronous vibration control yield greater performance without compromising stability.

Knospe, C. R.

Analysis of digital matched filtering schemes for digital receiver applications using simulation methods

The next generation of digital receivers for NASA's Deep Space Network is composed of in-phase and quadrature-phase channels. The authors have modeled and simulated a quadrature-phase baseband channel that includes a low-pass filter and a digital matched filter. The simulation is used to study the performance of the three schemes of digital matched filtering that use digital weighted integrate-and-dump filters. Using three methods for calculating the near-optimum matched filter weight coefficients, the simulation results are analyzed for the NRZ and Manchester data formats. The performances of the digital matched filters are studied in the presence of a timing error between the demodulated symbols and the integrate-and-dump filters.

Gevargiz, J. M.

Implementation of a modal filter on a five meter truss structure

Modal filtering is a spatial filtering technique which uses a weighted sum of a number of response measurements to extract the modal coordinates of the system from the physical response coordinates. No moving average or autoregressive calculations are required to implement the modal filter thus the modal coordinates may be calculated in real time. For practical implementation of the modal filter, the number and location of response locations must be chosen carefully. A modal filter is implemented on a five meter model space truss as a case study. The modal coordinates are extracted in real time using Hewlett Packard 3565 data acquisition and processig hardware. The effect of the number and location of response measurements on the performance of the modal filter is investigated. Applications of the modal filter to modal control and fast parameter identification are also discussed.

Shelly, S.

Thermal control design of the Lightning Mapper Sensor narrow-band spectral filter

The performance of the Lightning Mapper Sensor is dependent on the temperature shifts of its narrowband spectral filter. To perform over a 10 degree FOV with an 0.8 nm bandwidth, the filter must be 15 cm in diameter and mounted externally to the telescope optics. The filter thermal control required a filter design optimized for minimum bandpass shift with temperature, a thermal analysis of substrate materials for maximum temperature uniformity, and a thermal radiation analysis to determine the parameter sensitivity of the radiation shield for the filter, the filter thermal recovery time after occultation, and heater power to maintain filter performance in the earth-staring geosynchronous environment.

Flannery, Martin R.

Development of a low pass far infrared filter for Lunar Observer horizon sensor application

A study was conducted to (1) determine the feasibility of design and fabrication of a low pass filter with a relatively sharp cut-on at higher wavelengths (i.e. 30-40 microns), using metallic mesh technique; and (2) investigate whether the combination of this filter and a suitable IR detector, as a part of a Lunar Observer (LO) horizon sensor, is capable of detecting radiation emanating from two blackbody sources kept at temperatures simulating space and the surface temperature of dark or lit sides of the moon. Various designs of multilayer metallic mesh filters with different mesh parameters and substrate thicknesses were simulated. Using mesh parameters corresponding to the optimum four-layer filter design, a filter was fabricated on a 6.35 micron thick mylar substrate. The transmission curve of the fabricated filter is very close to what the simulation predicted. Room temperature signal level tests were performed on the combination of filter-detector assemblies. The data obtained from these tests indicate that the assembly can detect temperature differences as low as few degrees K between two black bodies.

Mobasser, Sohrab

Thin film filter lifetesting results in the extreme ultraviolet

We present the results of the thin film filter lifetesting program conducted as part of the NASA Extreme Ultraviolet Explorer (EUVE) satellite mission. This lifetesting program is designed to monitor changes in the transmission and mechanical properties of the EUVE filters over the lifetime of the mission (fabrication, assembly, launch and operation). Witness test filters were fabricated from thin film foils identical to those used in the flight filters. The witness filters have been examined and calibrated periodically over the past seven years. The filters have been examined for evidence of pinholing, mechanical degradation, and oxidation. Absolute transmissions of the flight and witness filters have been measured in the extreme ultraviolet (EUV) over six orders of magnitude at numerous wavelengths using the Berkeley EUV Calibration Facility.

Vedder, P. W.

The application of the reduced order model Kalman filter to motion estimation of degraded image sequences

Motion estimation is a field of great interest because of its many applications in areas such as robotics and image coding. The optic flow method is one such scheme which, although fairly accurate, is prone to error in the presence of noise. This thesis describes the use of the reduced order model Kalman filter (ROMKF) in reducing errors in displacement estimation due to degradation of the sequence. The implementation of filtering and motion estimation algorithms on the SUN workstation is also discussed. Results from preliminary testing were used to determine the degrees of freedom available for the ROMKF in the SUN software. The tests indicated that increasing the state to the left leads to slight improvement over the minimum state case. Therefore, the software uses the minimum model, with the option of adding states to the left only. The ROMKF was then used in conjunction with a hierarchical pel recursive motion estimation algorithm. Applying the ROMKF to the degraded displacements themselves generally yielded slight improvements in cases with noise degradation and noise plus blur. Filtering the images of the degraded sequence prior to motion estimation was less effective in these cases. Both methods performed badly in the case of blur alone, resulting in increased displacement errors. This is thought to be due in part to filter artifacts. Some improvements were obtained by varying the filter parameters when filtering the displacements directly. This result suggests that further study in varying filter parameters may lead to better results. The results of this thesis indicate that the ROMKF can play a part in reducing motion estimation errors from degraded sequences. However, more work needs to be done before the use of the ROMKF can be a practical solution.

Simpson, Elizabeth C.

Kalman filter estimation of attitude and gyro bias with the QUEST observation model

The loss function for the Wahba attitude estimation problem employs unit vector observations with scalar weights. It is usually associated with the QUEST observation model, where the actual sensor noise is assumed the same for all components of the observed vector, regardless of the position in the field of view. The QUEST model has the great advantage of being sensor-independent except for the scalar parameter that characterizes the sensor errors. Although efficient algorithms for solving the Wahba problem exist, extending these algorithms to estimate gyro biases or sensor alignments has had mixed success. However, it is straightforward to estimate bias and alignment parameters with a Kalman filter. This paper investigates the use of an extended Kalman filter for the attitude and gyro bias that incorporates the QUEST observation model, to be referred to as the Unit Vector Filter (UVF). The UVF results are compared with those from a more conventional filter, the Real-Time Sequential Filter (RTSF), for which the residual is the two-dimensional projection of the unit vector onto the plane perpendicular to the sensor boresight. The RTSF is similar in design to that used by Multimission Modular Spacecraft for onboard attitude determination. An apparent obstacle to the use of unit vectors as measurements is their singular noise covariance matrix. Shuster has shown that this problem should not affect filter performance. The UVF and RTSF are tested using actual flight data from the Extreme Ultraviolet Explorer (EUVE). It is found that these filters generate nearly identical attitude and gyro bias estimates, thus validating the use of unit vectors and the QUEST noise model.

Sedlak, J.

On the uniqueness of linear moving-average filters for the solar wind-auroral geomagnetic activity coupling

The relation between the solar wind input to the magetosphere, VB(sub South), and the auroral geomagnetic index AL is modeled with two linear moving-average filtering methods: linear prediction filters and a driven harmonic oscillator in the form of an electric circuit. Although the response of the three-parameter oscillator is simpler than the filter's, the methods yield similar linear timescales and values of the prediction-observation correlation and the prediction Chi(exp 2). Further the filter responses obtained by the two methods are similar in their long-term features. In these aspects the circuit model is equivalent to linear prediction filtering. This poses the question of uniqueness and proper interpretation of detailed features of the filters such as response peaks. Finally, the variation of timescales and filter responses with the AL activity level is discussed.

Vassiliadis, D.

A computational fluid dynamics simulation of the hypersonic flight of the Pegasus(TM) vehicle using an artificial viscosity model and a nonlinear filtering method

The computational fluid dynamics code, PARC3D, is tested to see if its use of non-physical artificial dissipation affects the accuracy of its results. This is accomplished by simulating a shock-laminar boundary layer interaction and several hypersonic flight conditions of the Pegasus(TM) launch vehicle using full artificial dissipation, low artificial dissipation, and the Engquist filter. Before the filter is applied to the PARC3D code, it is validated in one-dimensional and two-dimensional form in a MacCormack scheme against the Riemann and convergent duct problem. For this explicit scheme, the filter shows great improvements in accuracy and computational time as opposed to the nonfiltered solutions. However, for the implicit PARC3D code it is found that the best estimate of the Pegasus experimental heat fluxes and surface pressures is the simulation utilizing low artificial dissipation and no filter. The filter does improve accuracy over the artificially dissipative case but at a computational expense greater than that achieved by the low artificial dissipation case which has no computational time penalty and shows better results. For the shock-boundary layer simulation, the filter does well in terms of accuracy for a strong impingement shock but not as well for weaker shock strengths. Furthermore, for the latter problem the filter reduces the required computational time to convergence by 18.7 percent.

Mendoza, John Cadiz

A Custom Robotic System for Inspecting HEPA Filters in the Payload Changeout Room at the NASA Kennedy Space Center

In this paper, the prime objective is to describe a custom 4-dof (degree-of-freedom) robotic arm capable of autonomously or telerobotically performing systematic HEPA filter inspection and certification in the Shuttle Launch Pad Payload Changeout Rooms (PCR's) on pads A and B at the Kennedy Space Center, Florida. This HEPA filter inspection robot (HFIR) has been designed to be easily deployable and is equipped with the necessary sensory devices, control hardware, software and man-machine interfaces needed to implement HEPA filter inspection reliably and efficiently without damaging the filters or colliding with existing PCR structures or filters. The main purpose of the HFIR is to implement an automated positioning system to move special inspection sensors in pre-defined or manual patterns for the purpose of verifying filter integrity and efficiency. This will ultimately relieve NASA Payload Operations from significant problems associated with time, cost and personnel safety, impacts realized during non-automated PCR HFIR filter certification.

Spencer, James E., Jr.

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

Downie, John D.