Altitude Bias Research Articles

Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data

This study evaluated three bias correction methods of systematic biases in column-averaged dry-air mole fraction of water vapor (XH2O) data retrieved from Greenhouse Gases Observing Satellite (GOSAT) Short-Wavelength Infrared (SWIR) observations compared with ground-based data from the Total Carbon Column Observing Network (TCCON). They included an empirically multilinear regression method, altitude bias correction method, and combination of altitude and empirical correction for three cases defined by the temporal and spatial collocation around TCCON site. The results showed that large altitude differences between GOSAT observation points and TCCON instruments are the main cause of bias, and the altitude bias correction method is the most effective bias correction method. The lowest biases result from GOSAT SWIR XH2O data within a 0.5° 0.5° latitude longitude box centered at each TCCON site matched with TCCON XH2O data averaged over ±15 min of the GOSAT overpass time. Considering land data, the global bias changed from −1.3 ± 9.3% to −2.2 ± 8.5%, and station bias from −2.3 ± 9.0% to −1.7 ± 8.4%. In mixed land and ocean data, global bias and station bias changed from −0.3 ± 7.6% and −1.9 ± 7.1% to −0.8 ± 7.2% and −2.3 ± 6.8%, respectively, after bias correction. The results also confirmed that the fine spatial and temporal collocation criteria are necessary in bias correction methods.

Complete Systematic Error Model of SSR for Sensor Registration in ATC Surveillance Networks.

In this paper, a complete and rigorous mathematical model for secondary surveillance radar systematic errors (biases) is developed. The model takes into account the physical effects systematically affecting the measurement processes. The azimuth biases are calculated from the physical error of the antenna calibration and the errors of the angle determination dispositive. Distance bias is calculated from the delay of the signal produced by the refractivity index of the atmosphere, and from clock errors, while the altitude bias is calculated taking into account the atmosphere conditions (pressure and temperature). It will be shown, using simulated and real data, that adapting a classical bias estimation process to use the complete parametrized model results in improved accuracy in the bias estimation.

Nonlinear adaptive filtering in terrain-referenced navigation

Nonlinear adaptive estimation is applied to terrain-referenced navigation in three dimensions. In this scheme, a bank of parallel filters is initialized with different altitude hypotheses, where each filter represents a discrete (gridded) approximation to the Bayes minimum variance estimator. The importance weight of each filter is recursively updated using the measurement residuals. The altitude bias estimate is found from a weighted sum of the filter hypotheses. Numerical simulations with synthetic data indicate that an altitude bias can be accurately estimated without the use of three-dimensional grids. The computational simplicity and parallel nature of the filter may make it suitable for estimation of additional parameters such as horizontal velocity components.

고도를 고정한 GNSS 위치 결정 기법에서 고도 오차의 영향

This paper analyzed the precision and accuracy of the altitude-aided GNSS using the altitude information from digital map. The precision of altitude-aided GNSS is analysed using the theoretically derived DOP. It is confirmed that the precision of altitude-aided GNSS is superior to the general 3D positioning method. It is also shown that the DOP of altitude-aided GNSS is independent of altitude bias error while the accuracy was influenced by the altitude bias error. Furthermore, it is shown that, since the altitude bias error influenced differently to each pseudorange measurement, the effect of the altitude bias error is more serious than clock bias error which does not influence position error at all. The results are evaluated by the simulation using the commercial RF simulator and GPS receiver. It confirmed that altitude-aided GNSS could improve not only precision but also accuracy if the altitude bias error are small. These results are expected to be easily applied for the performance improvement to the land and maritime applications.

Marine latitude/altitude OH distributions: Comparison of Pacific Ocean observations with models

Reported here are tropical/subtropical Pacific basin OH observational data presented in a latitude/altitude geographical grid. They cover two seasons of the year (spring and fall) that reflect the timing of NASA's PEM‐Tropics A (1996) and B (1999) field programs. Two different OH sensors were used to collect these data, and each instrument was mounted on a different aircraft platform (i.e., NASA's P‐3B and DC‐8). Collectively, these chemical snapshots of the central Pacific have revealed several interesting trends. Only modest decreases (factors of 2 to 3) were found in the levels of OH with increasing altitude (0–12 km). Similarly, only modest variations were found (factors of 1.5 to 3.5) when the data were examined as a function of latitude (30°N to 30°S). Using simultaneously recorded data for CO, O3, H2O, NO, and NMHCs, comparisons with current models were also carried out. For three out of four data subsets, the results revealed a high level of correspondence. On average, the box model results agreed with the observations within a factor of 1.5. The comparison with the three‐dimensional model results was found to be only slightly worse. Overall, these results suggest that current model mechanisms capture the major photochemical processes controlling OH quite well and thus provide a reasonably good representation of OH levels for tropical marine environments. They also indicate that the two OH sensors employed during the PEM‐Tropics B study generally saw similar OH levels when sampling a similar tropical marine environment. However, a modest altitude bias appears to exist between these instruments. More rigorous instrument intercomparison activity would therefore seem to be justified. Further comparisons of model predictions with observations are also recommended for nontropical marine environments as well as those involving highly elevated levels of reactive non‐methane hydrocarbons.

Diurnal asymmetry of surface temperature trends over India

Diurnal asymmetry of the recent surface warming, reported for several continental areas, is believed to be related to changes in cloudiness, humidity, atmospheric circulation patterns, winds and soil moisture. This paper presents linear trend analyses of maximum and minimum temperature data at 121 stations in India during the period 1901–87. While the mean temperature trends over India are similar to the global and hemispheric trends, there are marked differences in their diurnal manifestation from those reported for other areas. The increase in the mean temperatures over India is almost solely contributed by the maximum temperatures, with the minimum temperatures remaining practically trendless, leading to an increase in the diurnal range of temperatures. These trends do not show any significant urban or altitude bias. There are some differences in the trends on smaller spatial and temporal scales, but the increase of maximum temperature is predominant over a major part of India, particularly in winter and post‐monsoon seasons.

An empirical determination of the effects of sea state bias on SEASAT altimetry

A simple linear empirical model has been developed to allow the user of SEASAT altimetry data to correct the altitude measurements for sea state bias effects. This bias is the result of two separate effects: one relating to instrumental effects and the other relating to a bias in the electromagnetic mean sea level relative to the geometric mean sea level. The electromagnetic bias is caused by the fact that the troughs of the ocean waves reflect the altimeter signal more strongly than the crests, thus causing the altimeter‐determined mean sea level to shift toward the wave troughs. An additional, but independent, instrument‐related bias is introduced because height corrections applied in the ground processor are not sufficient to compensate for simplifying assumptions made for the processor aboard SEASAT. This altitude bias also is predominately wave height dependent and directed toward the wave trough. The sum of these two effects is referred to as sea state bias. After applying appropriate corrections to the altimetry data, an empirical model for the sea state bias is obtained by differencing significant wave height and height measurements from coincident ground tracks. Ignoring small temporal variations in surface topography, the height differences on a given track should be zero; consequently, any residual height difference is attributed to sea state bias. The height differences are minimized by solving for the coefficient of a linear relationship between height differences and wave height differences that minimize the height differences. It is concluded that, for the altimeter data released by the Jet Propulsion Laboratory, 7% of the value of significant wave height should be subtracted from the SEASAT height measurements to correct for sea state bias. This correction reduced biases in the SEASAT data by more than 50% in the 36 cases examined here.

The average impulse responce of a rough surface and its applications

This paper is concerned with the theoretical model for short pulse scattering from a statistically random planar surface with particular application to current state of the art radar altimetry. A short review of the assumptions inherent in the convolutional model is presented. Simplified expressions are obtained for both the impulse response and the average backscattered power for near normal incidence under the assumptions common to satellite radar altimetry systems. In particular, it is shown that the conventional two-dimensional surface integration can be reduced to a closed form solution. Two applications of these results are presented relative to radar altimetry, namely, radar antenna pointing angle determination and altitude bias correction for pointing angle and surface roughness effects. It is also shown that these results have direct application to the analysis of the two frequency system proposed by Weissman, and a possible combined long pulse altimeter and two frequency system is suggested.

The average impulse response of a rough surface and its applications

This paper is concerned with the theoretical model for short pulse scattering from a statistically random planar surface with particular application to current state of the art radar altimetry, A short review of the assumptions inherent in the convolational model is presented. Simplified expressions are obtained for both the impulse response and the average backscattered power for near normal incidence under the assumptions common to satellite radar altimetry systems. In particular, it is shown that the conventional two-dimensional surface integration can be reduced to a closed form solution. Two applications of these results are presented relative to radar altimetry, namely, radar antenna pointing angle determination and altitude bias correction for pointing angle and surface roughness effects. It is also shown that these results have direct application to the analysis of the two frequency system proposed by Weissman, and a possible combined long pulse altimeter and two frequency system is suggested.