Stanley, J. P. | Engineering Papers

NASA NTRS1984

LANDSAT-4 horizon scanner performance evaluation

Representative data spans covering a little more than a year since the LANDSAT-4 launch were analyzed to evaluate the flight performance of the satellite's horizon scanner. High frequency noise was filtered out by 128-point averaging. The effects of Earth oblateness and spacecraft altitude variations are modeled, and residual systematic errors are analyzed. A model for the predicted radiance effects is compared with the flight data and deficiencies in the radiance effects modeling are noted. Correction coefficients are provided for a finite Fourier series representation of the systematic errors in the data. Analysis of the seasonal dependence of the coefficients indicates the effects of some early mission problems with the reference attitudes which were computed by the onboard computer using star trackers and gyro data. The effects of sun and moon interference, unexplained anomalies in the data, and sensor noise characteristics and their power spectrum are described. The variability of full orbit data averages is shown. Plots of the sensor data for all the available data spans are included.

Bilanow, S.↗

NASA NTRS1983

LANDSAT-4 horizon scanner full orbit data averages

Averages taken over full orbit data spans of the pitch and roll residual measurement errors of the two conical Earth sensors operating on the LANDSAT 4 spacecraft are described. The variability of these full orbit averages over representative data throughtout the year is analyzed to demonstrate the long term stability of the sensor measurements. The data analyzed consist of 23 segments of sensor measurements made at 2 to 4 week intervals. Each segment is roughly 24 hours in length. The variation of full orbit average as a function of orbit within a day as a function of day of year is examined. The dependence on day of year is based on association the start date of each segment with the mean full orbit average for the segment. The peak-to-peak and standard deviation values of the averages for each data segment are computed and their variation with day of year are also examined.

Stanley, J. P.↗