Optimized multirate filter banks for radar pulse compression

Fast convolution based on an FFT (fast Fourier transform) with blocksize B of at least twice the matched filter length L has been known for quite some time. With increasing blocksize, the limited numerical accuracy of fixed point hardware and the growing latency in heavily pipelined FFT processors become serious problems. The authors propose a novel structure, consisting of a multirate filter bank with analysis and synthesis filters based on an FFT of a much smaller size B ≈ √L and B channel filters with very sparse coefficients, so that for high time-bandwidth products the computational complexity becomes even smaller than for the standard fast convolution method. Applying a least-squares optimization algorithm on the sparse set of channel filter coefficients minimizes the sidelobes of the matched filter output signal.