Statistical-uncertainty-based adaptive filtering of lidar signals
- Department of Mechanical and Aerospace Engineering, University of California, Irvine, Irvine, California 92697-3975 (United States)
- Experimental Atmospheric and Climate Physics, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States)
- Department of Civil and Environmental Engineering, University of Iowa, Iowa City, Iowa 52242 (United States)
An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H{sub 2}O and the N{sub 2} photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America.
- OSTI ID:
- 20216172
- Journal Information:
- Applied Optics, Vol. 39, Issue 5; Other Information: PBD: 10 Feb 2000; ISSN 0003-6935
- Country of Publication:
- United States
- Language:
- English
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