Paper
28 May 1993 Terrain clearance estimation and clutter lock processing for airborne radar
Author Affiliations +
Proceedings Volume 1875, Ultrahigh Resolution Radar; (1993) https://doi.org/10.1117/12.145518
Event: OE/LASE'93: Optics, Electro-Optics, and Laser Applications in Scienceand Engineering, 1993, Los Angeles, CA, United States
Abstract
The signal processing for a down-looking airborne radar requires that the input signal data be compensated for platform motion and terrain variations. Typical examples are a Moving Target Indicator (MTI) function in a surveillance radar where the ground clutter must be maintained around zero Doppler in order to accurately detect moving targets, and a Synthetic Aperture Radar (SAR) where the correct location of the reflectivity of a scatterer depends on maintaining an accurate Doppler centroid for each pixel position. Platform motion compensation can be complicated by a wide elevation beam which intercepts many range cells at each azimuth, forcing the compensation of many range cells with the platform rates. These platform rates are assumed to be available from on-board inertial navigation system (INS), and the motion compensation correction can be obtained using the INS inputs. Processing of ground returns will be further complicated by the lack of reliable terrain information which can introduce significant Doppler errors into the motion compensation. Such errors will have an effect on the motion compensation, hence on the positioning of ground returns in the Doppler domain. Variations due to local topography are impossible to model accurately without prior knowledge of the terrain.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John J. SantaPietro "Terrain clearance estimation and clutter lock processing for airborne radar", Proc. SPIE 1875, Ultrahigh Resolution Radar, (28 May 1993); https://doi.org/10.1117/12.145518
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KEYWORDS
Radar

Doppler effect

Filtering (signal processing)

Motion estimation

Target detection

Digital filtering

Linear filtering

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