On the efficient computation of range and Doppler data in noise radar

In noise radar, digital signal processing algorithms for implementing the computation of the Cross Ambiguity Function through range correlation and Doppler compensation call for optimized solutions. In fact, to achieve a high coherent processing gain, they often compute a large amount of data beyond the maximum range and/or the maximum radial velocity of interest, adding useless information. A novel, efficient algorithm, called Range Filter Bank, is proposed to implement a scope-tailored computation of range/Doppler data in continuous emission noise radar. Downstream its theoretical analysis, the algorithm has been applied to a real-life case study based on dedicated field experiments, in which good quality kinematic data of a car moving at various speeds have been extracted.