Robust multicomponent LFM signals synthesis algorithm based on masked ambiguity function

Jia Su, Haihong Tao, Xuan Rao, Jian Xie, Dawei Song, Cao Zeng

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Wigner distribution (WD) based multiple components linear frequency modulation (LFM) signal synthesis method (SSM) is often adversely affected by cross-terms. Masked WD (MWD) is one of the widely used cross-term suppression techniques in practice due to its simplicity and efficiency. However, the cross-terms are hardly masked out when auto-terms and cross-terms are overlapped (Case I) or the components are very close to each other in the time-frequency (TF) plane (Case II). To solve these problems, we present a robust ambiguity function (AF) based approach for multicomponent signals synthesis. This algorithm consists of two stages. First, a SSM from the AF is proposed according to matrix rearrangement and eigenvalue decomposition. However, the existence of cross-term makes the signal synthesis entirely erroneous. To settle this issue, we present a masked AF (MAF) algorithm based on Radon and its inverse transforms in the second stage. Applying the presented algorithm, multicomponent signals can be synthesized efficiently even in Case I and Case II. Simulation results demonstrate the effectiveness and feasibility of the proposed algorithm.

Original languageEnglish
Pages (from-to)102-109
Number of pages8
JournalDigital Signal Processing: A Review Journal
Volume44
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

Keywords

  • Ambiguity function
  • Multicomponent signals
  • Radon transform
  • Signal decomposition
  • Signal synthesis

Fingerprint

Dive into the research topics of 'Robust multicomponent LFM signals synthesis algorithm based on masked ambiguity function'. Together they form a unique fingerprint.

Cite this