Dsss Signal Detection And Estimation,

Direct-sequence spread spectrum transmitters (DS-SS) use a periodical pseudo-random sequence (PN sequence) to modulate the baseband signal, and exploit the modulated signal to control the phase of carrier wave. Because DS signals show many advantages such as anti-jamming capability, low probability of interception, multiple access capability and so on, direct sequence spread spectrum signals have been widely applied for secure communications and mobile communications known as Code Division Multiple Access System.As a brand-new communication system for anti-interference, spread spread communication system has the characteristic of pseudo-random, DS signals are always transmitted in low Signal-to-Noise environment, which has two kinds of specialties, one is that DS signals are difficult to find; on the other hand, even though DS signals are detected, if the receiver doesn't know the priori information of spread sequence, it is impossible to recover the original signal. Classical signal detection and estimation theory can not give effective detection and estimation methods. The solution for DS signal demodulation should make full use of their difference in such field as time field, frequency field, power spectrum, cepstrum, spectrum correlation, high order spectrum and time-frequency field to distinguish DS signals from other communication signals and noise.The detection of DS-SS signals has been an important task in anti-jamming domain. In this paper, we study frequency doubler,spectrum correlation, and auto-correlation detection methods, and provide theory analysis and simulations of these algorithms. Above three methods can be used to detect the DS signals in low signal noise ratio, and estimate the parameters, such as the chip rate and carrier frequency.Chaos, as a random yet deterministic process in nonlinear dynamical system, is widely used in chaotic communications, chaotic control and chaotic life science. In this paper, the characters of chaotic spread spectrum sequences in chaotic communications are analyzed, including chaotic property, auto-correlation property and cross-correlation property. We also study the characters of conventional spread spectrum sequences, and compare respective advantages and disadvantages. Matlab simulation results are provided to compare their performance, which show chaos spread spectrum sequences are better than conventional ones in term of both correlation and quantity. As spread spectrum codes, Chaos sequences are more suitable for realistic spread spectrum communication systems. Finally, we study the detection method of chaotic spread spectrum sequences.