DocumentCode :
1939139
Title :
The Detection and Recognition of DS-SS Signals Using Higher-Order Statistical Processing
Author :
Zu, Yunxiao
Author_Institution :
Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun.
Volume :
3
fYear :
2006
fDate :
16-20 2006
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
Type :
conf
DOI :
10.1109/ICOSP.2006.345805
Filename :
4129251
Link To Document :
بازگشت