The impact of step selection in NLMS algorithm on low velocity target detecting for passive radar

Normalized Least-Mean Squares (NLMS) algorithm is widely used in cancelling the direct path and multi-path interferences in the passive coherent location (PCL) radar systems. The value of the step size in the NLMS algorithm impacts on the output of the canceller, which leads to different performance of the target detection. This paper analyses the impacts of different step size on low velocity target detecting and proposes that the larger step size results in the gain loss of the low velocity target in the cross ambiguity function (CAP) of passive radar. And a novel target detection algorithm with variable threshold in the CAP is proposed, which can be used to detect the low velocity targets and high velocity targets at the same time even if the CAP surface has a big notch. The validity of the algorithm is verified by both the simulative and experimental results.