12 May 2010 Classification of radar data by detecting and identifying spatial and temporal anomalies
Author Affiliations +
Abstract
For some time, applying the theory of pattern recognition and classification to radar signal processing has been a topic of interest in the field of remote sensing. Efficient operation and target indication is often hindered by the signal background, which can have similar properties with the interesting signal. Because noise and clutter may constitute most part of the response of surveillance radar, aircraft and other interesting targets can be seen as anomalies in the data. We propose an algorithm for detecting these anomalies on a heterogeneous clutter background in each range-Doppler cell, the basic unit in the radar data defined by the resolution in range, angle and Doppler. The analysis is based on the time history of the response in a cell and its correlation to the spatial surroundings. If the newest time window of response in a resolution cell differs statistically from the time history of the cell, the cell is determined anomalous. Normal cells are classified as noise or different type of clutter based on their strength on each Doppler band. Anomalous cells are analyzed using a longer time window, which emulates a longer coherent illumination. Based on the decorrelation behavior of the response in the long time window, the anomalous cells are classified as clutter, an airplane or a helicopter. The algorithm is tested with both experimental and simulated radar data. The experimental radar data has been recorded in a forested landscape.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Minna Väilä, Minna Väilä, Ilkka Venäläinen, Ilkka Venäläinen, Juha Jylhä, Juha Jylhä, Marja Ruotsalainen, Marja Ruotsalainen, Henna Perälä, Henna Perälä, Ari Visa, Ari Visa, } "Classification of radar data by detecting and identifying spatial and temporal anomalies", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76960G (12 May 2010); doi: 10.1117/12.852252; https://doi.org/10.1117/12.852252
PROCEEDINGS
9 PAGES


SHARE
RELATED CONTENT


Back to Top