Forward Looking Radar: Interference Modelling, Characterization, and Suppression

ISBN: 1288228562

Author: Caldwell, James T

Condition: New

This research characterizes forward looking radar performance while noting differences with traditionally examined side looking radar. The target detection problem for forward looking radar is extremely difficult due to the severe, heterogeneous, and range dependent ground clutter. Consequently, forward looking radar detection represents an important but overlooked topic because of the increased difficulty compared to side looking radar. This void must be filled since most fighter aircraft use forward looking radar, making this topic intensely interesting to the Air Force. After characterizing forward looking radar performance, basic radar concepts along with advanced adaptive interference suppression techniques improve the output Signal-to-Interference-plus-Noise Ratio (SINR) and target detection rates using fixed false alarm for linear arrays. However, target detection probabilities and output SINR do not improve enough. Although the methods considered are adaptive in azimuth and Doppler, effective range ambiguous clutter mitigation requires elevation adaptivity, a feature not offered by linear arrays. The research continues by examining planar arrays. Elevation adaptivity combined with azimuth and Doppler adaptivity allows suppressing range ambiguous clutter and significantly increasing output SINR, detection probability, and max-imum detection range. Specifically, three-dimensional Space-Time Adaptive Processing (3DSTAP) techniques with adaptivity in elevation, azimuth, and Doppler achieve detection probability improvements of over 10 dB in required input SINR compared to two-dimensional (2D) STAP processing. Additionally, 3D STAP improves detection probability versus input SINR curves over 30 dB when compared to 2D conventional processing techniques. As a result, forward looking radars using 3D STAP have the capacity to detect targets that conventional processing might miss.