Estimating Symbol Duration of Long-Code Direct Sequence Spread Spectrum Signals at a Low Signal-to-Noise Ratio
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Estimating Symbol Duration of Long‑Code Direct Sequence Spread Spectrum Signals at a Low Signal‑to‑Noise Ratio Zhi‑Tao Huang1 · Jiang‑Hai Liang1 · Xiang Wang1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Several existing spreading sequence estimation algorithms of long code direct-sequence spread spectrum (LC-DSSS) signals require prior knowledge of the symbol duration, but research on symbol duration estimation techniques of LC-DSSS signals are rare currently. In this paper, we proposed a method of estimating symbol duration for LC-DSSS signals. On the basis of the missing data model, a set of sample covariance matrices are constructed from the received signal with a set of window durations. Subsequently, the diagonals that contain noise component are removed from the sample covariance matrices to eliminate the effects of the noise and then squared Frobenius norm is performed on the sample covariance matrices to eliminate the effects of the long code. After analyzing the second-order statistical characteristic of the squared Frobenius norm of the sample covariance matrices, a symbol duration estimator of LC-DSSS signals is derived. Numerical experiments demonstrate that the proposed estimator provides satisfactory estimation performance of the symbol duration for LC-DSSS signals at low signal-to-noise ratio, even in multiple access interference scenario and multipath fading scenario. Compared to the existing estimators, the proposed estimator exhibits superior performance. Keywords Digital signal processing · Spread spectrum communication · Parameter estimation
1 Introduction Direct sequence spread spectrum (DSSS) signals are widely used in military and civilian applications owing to their properties of coverting message transmission and capabilities of resistance to jamming [1]. For the purpose of coverting message transmission and resistance to jamming, the transmitted symbols are modulated by a pseudo random spreading sequence in DSSS systems. To recover the symbols, the DSSS receiver uses the same spreading sequence to demodulate the signals. In this sense, recovering symbol * Jiang‑Hai Liang [email protected] 1
State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha, Hunan, People’s Republic of China
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at the receiver requires perfect knowledge of the spreading sequence in DSSS system [2]. In the non-cooperative applications such as spectrum surveillance and source localisation, owing to have no knowledge of the spreading sequence used by the transmitter, we need to estimate the spreading sequence in a blind manner. Existing spreading sequence estimation algorithms [3–7] of long code (LC) DSSS signal require prior knowledge of the symbol duration. However, it is a challenge to blindly estimate the symbol duration, because DSSS signal is in general a hidden transmission in the noise. For the short code (SC) DSSS sinal
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