Autofocusing of SAR images based on parameters estimated from the PHAF
Signal Processing
Analysis of Multicomponent Polynomial Phase Signals
IEEE Transactions on Signal Processing
Iterative frequency estimation by interpolation on Fourier coefficients
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Product high-order ambiguity function for multicomponentpolynomial-phase signal modeling
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Estimation and classification of polynomial-phase signals
IEEE Transactions on Information Theory
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The problem of non-stationary interference suppression in direct sequence spread-spectrum (DS-SS) systems is considered. The phase of interference is approximated by a polynomial within the considered interval. According to the local polynomial Fourier transform (LPFT) principle, the received signal is dechirped by using the obtained phase approximation and the interference is, in turn, suppressed by excising the corrupted low-pass frequency band. For the estimation of polynomial coefficients, we use the product high-order ambiguity function (PHAF), known for its capability to successfully resolve components of a multicomponent polynomial-phase signal (PPS). The proposed method can suppress interferences with both polynomial and non-polynomial phase. In addition, it can suppress both monocomponent and multicomponent interferences. The simulations show that the proposed method outperforms time-frequency (TF) methods, that successfully deal with multicomponent interferences, in terms of the error probability and computational complexity.