Title :
Multiscale adaptive estimation for fusing interferometric radar and laser altimeter data
Author :
Slatton, K. Clint ; Crawford, Melba ; Evans, Brian L.
Author_Institution :
Center for Space Res., Texas Univ., Austin, TX, USA
Abstract :
Interferometric synthetic aperture radar (INSAR) data are fused with laser altimeter (LIDAR) data to produce improved estimates of bare-surface topography and vegetation heights. The data from both sensors are first transformed into estimates of surface elevations and vegetation heights to obtain linear measurement-state relations. A spatially-adaptive multiscale estimation framework is then used to combine the data, which were acquired at different resolutions. The estimation is performed in scale and space via a set of Kalman filters. It yields better error characteristics than the nonadaptive multiscale filter and accommodates non-stationarity in the image data
Keywords :
Kalman filters; adaptive estimation; geophysical signal processing; optical radar; radar altimetry; radar imaging; radiowave interferometry; remote sensing by laser beam; remote sensing by radar; sensor fusion; synthetic aperture radar; terrain mapping; topography (Earth); vegetation mapping; INSAR data; Kalman filters; LIDAR data; bare-surface topography; data fusion; error characteristics; interferometric synthetic aperture radar data; laser altimeter data; linear measurement-state relations; nonstationarity; spatially-adaptive multiscale estimation framework; surface elevations; vegetation heights; Adaptive estimation; Inverse problems; Kalman filters; Laser radar; Noise measurement; Radar scattering; Spatial resolution; Surface topography; Synthetic aperture radar interferometry; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.976667