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- Title
Phase Clustering Based Modulation Classification Algorithm for PSK Signal over Wireless Environment.
- Authors
Qi An; Zi-shu He; Hui-yong Li; Yong-hua Li
- Abstract
Promptitude and accuracy of signals' non-data-aided (NDA) identification is one of the key technology demands in noncooperative wireless communication network, especially in information monitoring and other electronic warfare. Based on this background, this paper proposes a new signal classifier for phase shift keying (PSK) signals. The periodicity of signal's phase is utilized as the assorted character, with which a fractional function is constituted for phase clustering. Classification and the modulation order of intercepted signals can be achieved through its Fast Fourier Transform (FFT) of the phase clustering function. Frequency offset is also considered for practical conditions. The accuracy of frequency offset estimation has a direct impact on its correction. Thus, a feasible solution is supplied. In this paper, an advanced estimator is proposed for estimating the frequency offset and balancing estimation accuracy and range under low signal-to-noise ratio (SNR) conditions. The influence on estimation range brought by themaximum correlation interval is removed through the differential operation of the autocorrelation of the normalized baseband signal raised to the power of Q. Then, a weighted summation is adopted for an effective frequency estimation. Details of equations and relevant simulations are subsequently presented. The estimator proposed can reach an estimation accuracy of 10-4 even when the SNR is as low as -15 dB. Analytical formulas are expressed, and the corresponding simulations illustrate that the classifier proposed is more efficient than its counterparts even at low SNRs.
- Subjects
CLASSIFICATION algorithms; FAST Fourier transforms; MILITARY electronics; HILBERT transform; ELECTRONIC surveillance; SIGNAL-to-noise ratio; PHASE shift keying
- Publication
Mobile Information Systems, 2016, p1
- ISSN
1574-017X
- Publication type
Article
- DOI
10.1155/2016/2398464