A General framework for adaptive radar detection based on fast and slow-time preprocessing

Saraç, Uğur Berkay
This thesis is about the design of an adaptive radar detector under heterogeneous clutter environment using a small number of secondary data, which is at the same time robust to Doppler mismatch. To this end, the observations taken from heterogeneous clutter environment are first processed with a specially designed fast-time preprocessing matrix, cleansing the target contamination in the secondary range cells. Using these clean secondary data, the covariance matrix of the clutter is estimated via the parametric spectral estimation method proposed by Burg. Using this clutter space and the target space in which the targets are assumed to be in Generalized Eigenspace operation, a reduced dimension space which includes the target space and escapes the clutter space is found. After the observations which are purified in the fast-time dimension are projected in this newfound space, the detection mechanism is activated using the reduced dimension Kelly detector. In this thesis, all steps described here are explained in detail and the performance of the proposed detector is evaluated and compared with the other detectors in the literature by using the MATLAB simulation results.
Citation Formats
U. B. Saraç, “A General framework for adaptive radar detection based on fast and slow-time preprocessing,” Thesis (M.S.) -- Graduate School of Natural and Applied Sciences. Electrical and Electronics Engineering., 2019.