Walter Scott, Jr. College of Engineering

Graduate Exam Abstract

Mattia Vaccarono
Ph.D. Final
Apr 28, 2023, 9:30 am - 11:30 am
Coexistence of Weather Radars and Telecommunication Systems: a Model To Identify Interfering Sources during the Telecommunication Authorization Process and a New Mitigation Tool based on Interfering Signal Features
Abstract: Electromagnetic spectrum is a finite resource. Weather radars are one of the many sources which operate electromagnetic waves. The availability of spectrum bands that can be assigned to a specific user is limited. Consequently, the electromagnetic spectrum is shared by different application in the same frequency band. This is the specific case of C-band weather radars, which operate in the 5.6GHz band, sharing the same frequencies with Radio Local Area Networks, Wireless Local Area Networks and HiperLAN systems. These telecommunication systems are continuously increasing in rural areas as broadband Internet access points. The coexistence of C-band weather radar and such systems is nowadays a primary topic in the weather radar community. The amount of interferences received by weather radars are affecting the data quality, especially for polarimetric observations.

Electromagnetic interferences may also appear at higher frequencies, such as the X-band located around 9.3GHz. These frequencies are operated by weather radars in urban areas for hydrological purposes. The dense radar network deployed in Dallas Fort Worth area and the mobile radar managed by Arpa Piemonte operate at X-band and they receive interfering signals. These signals have been detected during a in field measurement campaign using both the mobile weather radar and a vector signal analyzer able to perform real time analysis up to 50GHz.

A new algorithm to identify the likely interfering sources is discussed, which can be used by the National Regulatory Authorities or Regional Agencies, such as the Physics and Industrial Risk Department of Arpa Piemonte, Italy, in charge of the telecommunication authorization processes. The model may be applied to a tower transmitting at the same frequency of a given radar and in case of likely interference, mitigation strategies could be set during the tower installation, i.e. changing the antenna direction or tilt.

Over the years, many RFI removal and mitigation tools have been discussed in the literature, but only few are currently implemented on operational weather radars. This work, instead, aims to implement a new removal tools that can be easily implemented by National Weather Services. The electromagnetic interference may be removed at different levels: from the raw IQ data to the processed radar product, such as reflectivity maps that are shown to general public. In order to make possible the interference removal also to those National Weather Services, or radar management services, which are not able to act on the radar signal processor to implement deeper mitigation tools, a first removal tool based on image processing is shown. This method does not require the access to the radar signal processor, but it does not mitigate the effect of interference overlapped to weather echoes. Furthermore, based on the interfering signals features, a new mitigation tool has been developed. The interfering signals are removed before IQ are processed to obtain radar moments. The proposed method has been tested with good performances in clear air echoes at both C and X-bands. A study case has been selected to evaluate the performances during light rain. The proposed mitigation tool is applied to the raw IQ data to remove interfering signals and to reconstruct the removed data. The radar reflectivity is computed from the processed IQ data and it is compared to the operational radar Z product. The interfering signals are properly removed and the missing data in the pulses are computed by smoothing from adjacent range gates and pulses. Actually, removing only the interfering signals the proposed tool is able to preserve the meteorological echoes which lead to a better estimate of the reflectivity values, especially in case of weak echoes (i.e.light rain, drizzle or ice-phase phenomena).
Adviser: V. Chandrasekar
Co-Adviser: N/A
Non-ECE Member: Ketul Popat
Member 3: Anura Jayasumana
Addional Members: Margaret Cheney
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Program of Study:
ATS 601
ATS 620
CIVE 577
ECE 512
ECE 742
ECE 795
ECE 799
GSTR 600