A computer implemented method for performing a noise removal operation on a signal (S) acquired by a sensor obtaining a denoised signal (x(t)), said noise removal operation including a Singular Spectrum Analysis (SSA), said Singular Spectrum Analysis (SSA) including considering said acquired signal (S) as one dimensional series of given length (T), then performing an iterative procedure (210, 220, 230, 240; 340) comprising at each iteration an operation of construction of a trajectory matrix (X) on a window of said one dimensional series of given length (T) having a respective window length (L), transforming said trajectory matrix (X) in a form (XX T ) to which single value decomposition is applicable, an operation of singular value decomposition on said transformed matrix (XX T ) computing eigenvalues and eigenvectors of said transformed matrix (XX T ), an operation of selection (240; 340) of eigenvectors among the eigenvectors of said transformed matrix (XX T ), after said iterative procedure performing an operation of reconstruction of a one dimensional series corresponding to said denoised signal based on said selected among said eigenvectors, wherein said iterative procedure is performed starting from a given window length (L) value, in particular a value of three, and said selection of eigenvectors comprises calculating the root mean square value between the current and previous eigenvalue in said set of eigenvalues, calculating a minimum and its position of said root mean square values halting the iterations if said minimum is lower than a determined threshold value (ε), in particular lower than 1, otherwise increasing the window length (L) value and returning to the operation of construction of a trajectory matrix (X). said Singular Spectrum Analysis (SSA) including considering said acquired signal (S) as one dimensional series of given length (T), then performing an iterative procedure (210, 220, 230, 240; 340) comprising at each iteration an operation of construction of a trajectory matrix (X) on a window of said one dimensional series of given length (T) having a respective window length (L), transforming said trajectory matrix (X) in a form (XX T ) to which single value decomposition is applicable, an operation of singular value decomposition on said transformed matrix (XX T ) computing eigenvalues and eigenvectors of said transformed matrix (XX T ), an operation of selection (240; 340) of eigenvectors among the eigenvectors of said transformed matrix (XX T ), an operation of construction of a trajectory matrix (X) on a window of said one dimensional series of given length (T) having a respective window length (L), transforming said trajectory matrix (X) in a form (XX T ) to which single value decomposition is applicable, an operation of singular value decomposition on said transformed matrix (XX T ) computing eigenvalues and eigenvectors of said transformed matrix (XX T ), an operation of selection (240; 340) of eigenvectors among the eigenvectors of said transformed matrix (XX T ), after said iterative procedure performing an operation of reconstruction of a one dimensional series corresponding to said denoised signal based on said selected among said eigenvectors, wherein said iterative procedure is performed starting from a given window length (L) value, in particular a value of three, and said selection of eigenvectors comprises calculating the root mean square value between the current and previous eigenvalue in said set of eigenvalues, calculating a minimum and its position of said root mean square values halting the iterations if said minimum is lower than a determined threshold value (ε), in particular lower than 1, otherwise increasing the window length (L) value and returning to the operation of construction of a trajectory matrix (X). <EOS>