Unambiguous acquisition algorithm based on sub‐correlation functions combination for semi‐integer CPM signals

• Published in: Electronics letters Vol. 60; no. 14
• Main Authors: Xie, Mingming, Xue, Rui
• Format: Journal Article
• Language: English
• Published: Wiley 01.07.2024
• Subjects: continuous phase modulation; decomposition; satellite navigation; signal detection; signal reconstruction
• ISSN: 0013-5194; 1350-911X; 1350-911X
• DOI: 10.1049/ell2.13286

Due to the nonlinear nature of continuous phase modulation (CPM), most existing unambiguous acquisition algorithms are ineffective in eliminating the ambiguity threat faced by semi‐integer CPM signals. To address this issue, this letter proposes an unambiguous acquisition algorithm based on sub‐correlation functions combination (SCFC). The main idea of this algorithm is to decompose the first pulse amplitude modulation waveform derived from the Laurent decomposition into sub‐signal waveforms that are appropriate for CPM signals. The final unambiguous function is obtained by combining the autocorrelation function of the received CPM signal with the sub‐correlation functions derived from the sub‐signal waveforms and the received CPM signal. Simulation results demonstrate that the SCFC algorithm can eliminate the ambiguity threat of semi‐integer CPM signals with relatively minor detection loss. Moreover, the proposed algorithm successfully retains a narrow main peak and exhibits superior multipath resistance. This letter introduces a novel unambiguous acquisition algorithm based on sub‐correlation functions for semi‐integer CPM signals. This algorithm further decomposes the first phase amplitude modulation waveform after Laurent decomposition to obtain sub‐signal waveforms suitable for semi‐integer CPM signals. This new algorithm can eliminate the side peaks and false lock points of semi‐integer CPM signals at the expense of minor detection performance loss while maintaining a narrow main peak.