학술논문

Adaptive Acquisition of PN Code using Automatic Censoring CFAR Outlier Detection in Multipath Fading Mobile Channels
Document Type
Conference
Source
2020 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP) Communications, Control Systems and Signal Processing (CCSSP), 2020 1st International Conference on. :2-7 May, 2020
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Synchronization
Fading channels
Signal resolution
Microsoft Windows
Detectors
Noise measurement
Correlation
MAD
DS/SS
PN sequence
CFAR processor
CMLD
OS
and ACCA-ODV
Multipath
Language
Abstract
This paper describes a robust method of auto-adaptive pseudo noise (PN) code acquisition for mobile systems, when communicating in multipath environment. The proposed method is built on the Constant False Alarm Rate (CFAR) algorithm, which is referred to here as Median Absolute Deviation (MAD)-CFAR. The new method does not need any prior information of the background situations, and employs the Median Absolute Deviation (MAD) test to detect the multipath signals (outliers) in the ranked cells for the full reference window. Once these multipath signals are automatically identified and censored, the remaining ranked cells are taken to form a homogeneous reference window (HRW) free of outliers to calculate the adaptive threshold. Monte Carlo simulations show that the new approach has a good detection performance, while competitors present a poor performance to varying degrees. Thus proving the efficiency and superiority of the new method in a multipath environment.