Stagger period estimation algorithm for multiple sets of radar pulses

Abstract

To apply the Ramanujan filter bank based on the compressed sensing theory to the period estimation of multiple sets of radar pulses, alternatives to period data and the Ramanujan Subspace are proposed in this study. First, the rationality of alternatives to the TOA (time of arrival) model is illustrated by comparing the advantages and disadvantages of the time-point model and the TOA model. Next, by clarifying the zero-sum energy property of the Ramanujan Subspace, the possibility of finding an alternative to the discrete Fourier transform sequence with smaller data is proved. On this basis, a new algorithm for estimating the stagger period of mixed pulses is proposed, which introduces the initial phase of the stagger pulses. The results of the experiments show that the algorithm can accurately estimate the hidden stagger periods of mixed pulses, and it is adept at dealing with false and missing mixed pulses.