Title :
The Detection and Recognition of DS-SS Signals Using Higher-Order Statistical Processing
Author_Institution :
Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun.
Abstract :
In this paper the triple correlation function (TCF) of m-sequence, the partial triple correlation function of m-sequence and its peak feature are studied and described firstly. Then a detection method and a recognition standard of m-sequence are proposed based on the peak feature of the partial TCF using higher-order statistical processing and detection theory. It is testified by simulation that the peak feature of the partial TCF is the same as that of the TCF during the corresponding intercepted section. With the peak feature m-sequence can be distinguished from 0-1 binary sequence and random noise sequence. So this is can be used to detect and recognize the direct sequence spread spectrum signals. The detection method and the recognition standard of m-sequence have been proved available by the simulation
Keywords :
higher order statistics; m-sequences; pseudonoise codes; random noise; random sequences; signal detection; spread spectrum communication; DS-SS signals; binary sequence; direct sequence spread spectrum signals; higher-order statistical processing; m-sequence; random noise sequence; signal detection; signal recognition; triple correlation function; Binary sequences; Gold; Linear feedback shift registers; Signal processing; Spread spectrum communication; Testing;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345805