Coherently integrated cubic phase function for multiple LFM signals analysis

The cubic phase function (CPF) based estimator is efficient in estimating the parameters for mono-component linear frequency-modulated (LFM) signals. However, it suffers from cross-terms and spurious peaks when dealing with multi-component LFM signals. Aimed at this identifiability problem, a coherently integrated CPF (CICPF) algorithm is proposed to enhance the auto-terms and suppress spurious peaks. Comparisons with several existing algorithms are made, which show that the CICPF not only solve the identifiability problem for multi-component LFM signals, but also acquires high anti-noise performance.