| The direct sequence spread spectrum (DSSS) signal has been widely used in these years for its advantage of anti-jamming capability, good confidentiality and low power spectrum density. It has wide usage in mobile communications, radar, navigation and orientation. Since the DSSS signal is always transmitted in seriously noisy environment, the DSSS signal detection with low signal-to-noise ratio is an important content of DSSS electronic countermeasures. Normally, the signal detection in this situation is non-cooperative and lacks adequate prior information; therefore, it is a type of blind detection or approximate blind detection.To solve this problem, this thesis will focus on investigation of the following detection methods based on the features of the DSSS signal and with the binary-phase-shift-keying DSSS (DSSS/BPSK) signal as an example.1. The power spectrum of the DSSS/BPSK signal is discussed and the detection performance in each power spectrum estimation method is compared in terms of nonparametric methods, parametric methods and subspace methods in power spectrum estimation.2. The characteristics of pseudorandom spread spectrum sequence in the DSSS/BPSK signal exhibit the essential difference between the DSSS/BPSK signal and other conventional signals in communications. By making use of the characteristics of pseudorandom spread spectrum sequence in time-domain, this thesis has studied the time-domain correlation detection method of the DSSS/BPSK signal and proposed the time-domain difference-accumulation detection method of the DSSS/BPSK signal. On this basis, the wavelet decomposition established on the time-domain correlation detection method provides a feasible scheme that improves performance, in a situation when it is impossible to design the pre-filter because the frequency band of the useful signal is unknown.3. The power spectrum and autocorrelation can be concluded to the second-order statistics. As an extension, the high-order statistics of the DSSS/BPSK signal is... |
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