Total Variation Compressive Sensing for Extended Targets in MIMO Radar

The problem of extended target cross-section estimation has been considered. A two-step method based on the Total Variation Compressive Sensing theory has been proposed to solve it. First, a coarse estimation of the target cross-section is performed with classical beamforming methods, and then Compressive Sensing algorithms have been applied...

Robust Feature Extraction Algorithm for analysis of Radar Targets using Multi-Object Tracking on Range Velocity Space

In this thesis, we propose, a Robust data extraction algorithm capable of extracting reliable target features of multiple moving targets of different classes over all channels of an S-Band Doppler Polarimetric Radar PARSAX. The proposed algorithm is capable of generating a time series data by tracking, clusters of detections - representing...

Diversity considerations in wideband radar detection of migrating targets in clutter

Wideband radars have been proposed for detection of moving targets, with unique capability of non-ambiguous detection due to range migration. Moreover, frequency diversity has long been used for mitigating the fading effects caused by target and clutter fluctuations. The real benefits of wideband radars are difficult to analyze, since they...