Performance characteristics of a signal detection scheme and its estimation method applicable to M-to-M communication System

Author(s):  
Kanshiro Kashiki ◽  
I-Te Lin ◽  
Tomoki Sada ◽  
Toshihiko Komine ◽  
Shingo Watanabe
2019 ◽  
Vol 11 (1) ◽  
pp. 542-548
Author(s):  
Wenlong Tang ◽  
Hao Cha ◽  
Min Wei ◽  
Bin Tian ◽  
Xichuang Ren

Abstract This paper proposes a new refractivity profile estimation method based on the use of AIS signal power and quantum-behaved particle swarm optimization (QPSO) algorithm to solve the inverse problem. Automatic identification system (AIS) is a maritime navigation safety communication system that operates in the very high frequency mobile band and was developed primarily for collision avoidance. Since AIS is a one-way communication system which does not need to consider the target echo signal, it can estimate the atmospheric refractivity profile more accurately. Estimating atmospheric refractivity profiles from AIS signal power is a complex nonlinear optimization problem, the QPSO algorithm is adopted to search for the optimal solution from various refractivity parameters, and the inversion results are compared with those of the particle swarm optimization algorithm to validate the superiority of the QPSO algorithm. In order to test the anti-noise ability of the QPSO algorithm, the synthetic AIS signal power with different Gaussian noise levels is utilized to invert the surface-based duct. Simulation results indicate that the QPSO algorithm can invert the surface-based duct using AIS signal power accurately, which verify the feasibility of the new atmospheric refractivity estimation method based on the automatic identification system.


2012 ◽  
Vol 66 (4) ◽  
pp. 479-500 ◽  
Author(s):  
P. Huang ◽  
Y. Pi ◽  
I. Progri

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz.


IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 14543-14547 ◽  
Author(s):  
Chang-Hee Kang ◽  
Won-Seok Lee ◽  
Young-Hwan You ◽  
Hyoung-Kyu Song

2006 ◽  
Vol 06 (04) ◽  
pp. L339-L347 ◽  
Author(s):  
MICHAEL BUSCHERMÖHLE ◽  
ULRIKE FEUDEL ◽  
GEORG M. KLUMP ◽  
MARK A. BEE ◽  
JAN A. FREUND

Signal detection in fluctuating background noise is a common problem in diverse fields of research and technology. It has been shown in hearing research that the detection of signals in noise that is correlated in amplitude across the frequency spectrum (comodulated) can be improved compared to uncorrelated background noise. We show that the mechanism leading to this effect is a general phenomenon which may be utilized in other areas where signal detection in comodulated noise needs to be done with a limited frequency resolution. Our model is based on neurophysiological experiments. The proposed signal detection scheme evaluates a fluctuating envelope, the statistics of which depend on the correlation structure across the spectrum of the noise. In our model, signal detection does not require a sophisticated neuronal network but can be accomplished through the encoding of the compressed stimulus envelope in the firing rate of neurons in the auditory system.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 123514-123523 ◽  
Author(s):  
Yuanjian Qiao ◽  
Jun Li ◽  
Bo He ◽  
Wenxin Li ◽  
Tongliang Xin

Sign in / Sign up

Export Citation Format

Share Document