Segmented discrete polynomial‐phase transform with coprime sampling

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.

[1]  X. Xia An efficient frequency-determination algorithm from multiple undersampled waveforms , 2000, IEEE Signal Processing Letters.

[2]  Tao Shan,et al.  A fast algorithm for multi-component LFM signal analysis exploiting segmented DPT and SDFrFT , 2015, 2015 IEEE Radar Conference (RadarCon).

[3]  Yimin Zhang,et al.  Detection of weak astronomical signals with frequency-hopping interference suppression , 2018, Digit. Signal Process..

[4]  Yimin Zhang,et al.  Generalized Coprime Array Configurations for Direction-of-Arrival Estimation , 2015, IEEE Transactions on Signal Processing.

[5]  I. Djurovic,et al.  Integrated Cubic Phase Function for Linear FM Signal Analysis , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Benjamin Friedlander,et al.  The discrete polynomial-phase transform , 1995, IEEE Trans. Signal Process..

[7]  Xiang-Gen Xia,et al.  A Closed-Form Robust Chinese Remainder Theorem and Its Performance Analysis , 2010, IEEE Transactions on Signal Processing.

[8]  P. P. Vaidyanathan,et al.  Sparse Sensing With Co-Prime Samplers and Arrays , 2011, IEEE Transactions on Signal Processing.

[9]  Sergio Barbarossa,et al.  Analysis of multicomponent LFM signals by a combined Wigner-Hough transform , 1995, IEEE Trans. Signal Process..

[10]  Peter O'Shea,et al.  A fast algorithm for estimating the parameters of a quadratic FM signal , 2004, IEEE Transactions on Signal Processing.