Segmented discrete polynomial-phase transform with coprime sampling

Abstract

Segmented discrete polynomial-phase transform (DPT) integrates input signals to enable detection and parameter estimation of weak linear frequency modulated (LFM) signals. However, conventional DPT approaches suffer from a low unambiguously detectable range of the chirp rates because the segmentation effectively reduces the sampling rate between adjacent segments. To enable unique detection of LFM signals with a high chirp rate estimation, the authors propose the use of multiple segmentation sets where the respective segment lengths are governed by a coprime relationship. As such, the ambiguity of the estimated chirp rates that arise from a single segmentation set is eliminated through the fusion of the multiple segmentation sets using the Chinese Remainder Theorem. The effectiveness of the proposed method for the estimation of LFM signals with a high chirp rate is validated by simulation results.

Keywords

• parameter estimation
• polynomials
• signal detection
• frequency modulation
• signal sampling
• transforms
• coprime sampling
• parameter estimation
• low unambiguously detectable range
• single segmentation set
• LFM signal detection
• chirp rate estimation
• DPT approaches
• segmented discrete polynomial-phase transform
• linear frequency modulated signal detection
• Chinese remainder theorem