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.
