Title :
Analysis of Weak Echo Signal Based on RBF Neural Network in Non-Cooperative Passive Detection
Author :
Zhao Danfeng ; Xu Cong ; Zhang Yang
Author_Institution :
Inf. & Commun. Sch., Harbin Eng. Univ., Harbin
Abstract :
Because of some advantages obtained from non-cooperative passive detection system, such as anti-surveillance, anti-interference, anti-stealth, anti-radiation missile and so on, it will become a crucial trend of radar systems in the future. The key problem in this system is the detection of weak echo signal, which is submerged in interference and noise. In this paper, the echo signal in non-cooperative passive detection exploiting FM radio signal as illuminator is proved to be chaotic. The RBF neural network is adopted to predict the chaotic time series. A new conception is proposed to detect weak signal.
Keywords :
FM radar; passive radar; prediction theory; radar computing; radar detection; radar signal processing; radial basis function networks; radiofrequency interference; time series; FM radio signal; RBF neural network; chaotic time series prediction; noncooperative passive detection system; radar system; radio interference; radio noise; weak echo signal detection; Chaos; Chaotic communication; Delay effects; Fractals; Kernel; Neural networks; Passive radar; Radar detection; Signal analysis; Signal processing;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
DOI :
10.1109/WiCom.2008.492