Abstract
The traditional signal of opportunity (SOP) positioning system is equipped with dedicated receivers for each type of signal to ensure continuous signal perception. However, it causes a low equipment resources utilization and energy waste. With increasing SOP types, problems become more serious. This paper proposes a new signal perception unit for SOP positioning systems. By extracting the perception function from the positioning system and operating independently, the system can flexibly schedule resources and reduce waste based on the perception results. Through time-frequency joint representation, time-frequency image can be obtained which provides more information for signal recognition, and is difficult for traditional single time/frequency-domain analysis. We also designed a convolutional neural network (CNN) for signal recognition and a negative learning method to correct the overfitting to noisy data. Finally, a prototype system was built using USRP and LabVIEW for a 2.4 GHz frequency band test. The results show that the system can effectively identify Wi-Fi, Bluetooth, and ZigBee signals at the same time, and verified the effectiveness of the proposed signal perception architecture. It can be further promoted to realize SOP perception in almost full frequency domain, and improve the integration and resource utilization efficiency of the SOP positioning system.
Highlights
Global navigation satellite system (GNSS) is the most widely used navigation system
The equipped receiver will increase along with the types of signals, which leads to a series of problems: (1) since the lack of available signal information, all receivers need continue working to ensure the perception of all types signals, even if only no signal exist, which causes high power consumption, and hardware and energy resources waste; (2) different signals in the same frequency band still need multiple devices to complete the signal perception, which does not make full utilization of hardware resources
This paper proposes a new signal perception architecture for signal of opportunity (SOP) positioning system and completed the implementation
Summary
Global navigation satellite system (GNSS) is the most widely used navigation system. It uses satellites to broadcast positioning signals and provides positioning, navigation, and timing services for worldwide users. The equipped receiver will increase along with the types of signals, which leads to a series of problems: (1) since the lack of available signal information, all receivers need continue working to ensure the perception of all types signals, even if only no signal exist, which causes high power consumption, and hardware and energy resources waste; (2) different signals in the same frequency band This section briefly introduces the target signals (Bluetooth, Wi-Fi, ZigBee) in the paper and includes basic information such as channel parameters, transmission power, and access method. After the perception controller completes the configuration of the hardware parameters (center frequency, sampling rate, etc.), USRP starts the signal acquisition whose process includes mixing, AD sampling, data buffering, etc. Typical linear analysis includes STFT, Continuous wavelet transform (CWT), etc., and typical nonlinear analysis includes Wigner-Ville distribution (WVD), Cohen Classes, etc
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