Research On Signal Detection Algorithm In Short Wave Communication

This thesis researches the signal stream detection in strong background noise environment. It is inevitable that the communication system is disturbed, especially the short wave communication, its signal is easily disturbed by the noise. In the communication and broadcast system, the noise deeply decreases the quality of speech, and increases tiredness to the worker. The intention of signal detection is that detecting the speech or morse signal, obliterating the noise signal from the signal stream and improving the working environment.Endpoint detection of speech is a important branch of the speech signal processing. The traditional detection algorithm, based on zero-crossing or energy , will not acquire ideal effect when the Signal-to-Noise is low or the signal is weaker. Therefore, to resolve the real problem in the real environment that all kinds of random noise and speech signal exit together, some new algorithm must be put forward.At the first, the thesis introduces the types of noise, speech signal and morse signal character. Then illustrate all kinds of noise and put forward exact algorithm to separate the noise and speech or morse signal. Account for the complexity of real noise, we integrate the wavelet transform and high-order statistics and advance a new algorithm, the algorithm can separate the speech signal and the non-Gaussian noise, and the experimentation shows that the algorithm is effective and utilitarian.On the basis of the character of the speech and the background noise, the thesis brings forward the algorithm that based on the statistic of wavelet transform coefficient, bispectrum and the complex number spectrum variance to detect the speech signal. The statistic of wavelet transform coefficient algorithm can solve the periodic noise, high-energy noise and some non-Guassian noise simply and efficaciously; bispectrum can acquire more information from the original signalthan power-spectrum, detect more information except from range and restrain the guassian noise. Short-time speech signal can be considered as stationary and with periodic non-Guassian signal, so we can make use of bispectrum to obtain the speech character and separate the speech and noise; complex number spectrum variance algorithm is put forward based on the deeply observing speech data, it is a new algorithm, experience show that it is simple, effective and utilitarian.Morse telegraph code is a single period and regular signal, its character is obvious, the combination of dot, line, space are used to denote the letter, number, punctuation, sign. And its typical character is discontinuous in time-space and in spectrum-space.On the basis of the essential character of morse signal's periodicity and periodic frequency discontinuity. The thesis applies the complex number spectrum variance algorithm to detection periodic signal and the frequency. Then, in according with the character of Fourier Transform, we obtain the corresponding transform coefficient and analyze them. Combining unitariness with threshold, we obtain the discontinuity character of morse signal and detect it.The DSP chip of TI corporation is high-powered. The thesis introduces its superiority in high-speed computer at length and the basic structure and the hardware resource. At last, we design the circuit to realize the algorithm.