PROJECT TITLE :

A Novel Two-Dimensional Sparse-Weight NLMS Filtering Scheme for Passive Bistatic Radar

ABSTRACT:

In passive bistatic radars, weak target echoes may often be masked by direct path interference, multipath components, and robust target echoes, creating weak target detection a challenging downside. The standard 1-D adaptive cancelation algorithms, like the normalized least mean sq. (NLMS), cannot effectively suppress strong target echoes when their Doppler frequencies spread. Likewise, the continual distribution of the NLMS weight vector will not match the sparse characteristics of strong multipath parts and target echoes, so ensuing in degraded cancelation performance. Motivated by this reality, a novel two-D sparse-weight NLMS filtering theme is proposed by extending the NLMS to a a pair of-D structure, in that the weight vector is sparsely distributed and adaptively adjusted based on the sparse sturdy multipath elements and target echoes.


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