{"title":"A novel unambiguous acquisition algorithm based on decomposition and reconstruction of sub-correlation functions for semi-integer CPM signals","authors":"Rui Xue, Mingming Xie","doi":"10.1016/j.dsp.2025.105564","DOIUrl":null,"url":null,"abstract":"<div><div>Continuous phase modulation (CPM) with a semi-integer modulation index greater than 1 exhibits spectral splitting, superior tracking performance, and compatibility. However, the multiple side peaks in the autocorrelation function (ACF) of the semi-integer CPM signals introduce ambiguity threats in signal acquisition. Therefore, a novel unambiguous acquisition algorithm based on decomposition and reconstruction of sub-correlation functions (DRSCF) is proposed for semi-integer CPM signals. The algorithm further decomposes the first pulse amplitude modulation waveform after Laurent decomposition to obtain sub-signal waveforms suitable for CPM signals and reconstructs the unambiguous correlation function by a nonlinear combination of sub-correlation functions. Subsequently, energy loss compensation is performed using ACF. Theoretical analysis and simulation results show that the proposed DRSCF algorithm effectively eliminates the ambiguity threat in the of semi-integer CPM signals at the expense of some detection performance loss, and maintaining the narrow correlation peak.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"168 ","pages":"Article 105564"},"PeriodicalIF":3.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S105120042500586X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Continuous phase modulation (CPM) with a semi-integer modulation index greater than 1 exhibits spectral splitting, superior tracking performance, and compatibility. However, the multiple side peaks in the autocorrelation function (ACF) of the semi-integer CPM signals introduce ambiguity threats in signal acquisition. Therefore, a novel unambiguous acquisition algorithm based on decomposition and reconstruction of sub-correlation functions (DRSCF) is proposed for semi-integer CPM signals. The algorithm further decomposes the first pulse amplitude modulation waveform after Laurent decomposition to obtain sub-signal waveforms suitable for CPM signals and reconstructs the unambiguous correlation function by a nonlinear combination of sub-correlation functions. Subsequently, energy loss compensation is performed using ACF. Theoretical analysis and simulation results show that the proposed DRSCF algorithm effectively eliminates the ambiguity threat in the of semi-integer CPM signals at the expense of some detection performance loss, and maintaining the narrow correlation peak.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,